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www.HydrocarbonProcessing.com

JANUARY 2010

HPIMPACT SPECIALREPORT TECHNOLOGY

GAS PROCESSINGGAS PROCESSINGDEVELOPMENTSDEVELOPMENTS

Innovations improveInnovations improvegas treatinggas treating

Continued strugglesContinued strugglesfor US refinersfor US refiners

The EU’s Emissions The EU’s Emissions Trading SchemeTrading Scheme

When carbon captureWhen carbon capturemakes sensemakes sense

Managing equipmentManaging equipmentcosts and incidentscosts and incidents

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JANUARY 2010 • VOL. 89 NO. 1

SPECIAL REPORT: GAS PROCESSING DEVELOPMENTS

29 Advanced mercury removal technologiesNew technologies can cost-effectively treat ‘wet’ and ‘dry’ natural gaswhile protecting cryogenic equipmentN. Eckersley

37 A unique natural gas processing success storyCost-effective expansion created high reliability operationsC. Baker and T. Barnette

39 Equilibrium considerations in choosinga gas treating aminePursue these guidelines to understand solubilityS. A. Bedell

43 Designing a selective MDEA tail-gas treating unitFollowing these protocols will enhance sulfur recovery efficiencyS. Nagpal

Cover Darwin LNG, located at Wickham Point, Darwin Australia began operation in 2006. This 3.7 MTPA facility, which employs the ConocoPhillips Optimized Cascade Process, established new design benchmarks for LNG facilities by being the first to apply high efficiency aeroderivative gas turbines and the first to use inlet air humidification to enhance production during periods of low humidity.

HPIMPACT 15 Struggles for US refiners

expected to continue

17 The EU’s ETS at a glance

COLUMNS 9 HPIN RELIABILITY

More about unreliability, global procurement and you

11 HPIN EUROPEDuh! Business as usual will not be good for the HPI

13 HPINTEGRATION STRATEGIESApplying tuneable diode laser spectroscopy to help reduce energy consumption

82 HPIN WATER MANAGEMENTWastewater discharge permits; What should you know?

ENVIRONMENT

49 When does carbon capturemake sense?Here are several options in which carbon capture can providecost-effective solutionsS. Ferguson

MAINTENANCE/RELIABILITY

55 Managing costs and incidents in industrial plant equipmentUse this method to allogate limited maintenance resources to the most critical equipmentM. Gardella, E. Egusquiza, X. Escaler and A. Goti

PLANT SAFETY AND ENVIRONMENT

63 Designing for pressure safety valves in supercritical serviceUse this rigorous method to prevent over-sizingR. C. Doane

PIPING

69 New explicit friction factor equation for turbulent flow in smooth pipesA simple, explicit and high-accuracy equation is presentedA. Sasan-Amiri

INSTRUMENTATION

71 Implement a constrained optimal control in a conventional level controller—Part 1Novel tuning method enables a conventional PI controller to explicitly handle the three important operational constraints of a liquid level loop in an optimal manner as well as copes with a broad range of level control from tight to averaging controlM. Lee, J. Shin and J. Lee

ENGINEERING CASE HISTORIES

77 Case 54: Is it motor vibrationor some other cause?It’s not always the motor causing the vibrationT. Sofronas

DEPARTMENTS7 HPIN BRIEF • 15 HPIMPACT • 19 HPINNOVATIONS •23 HPIN CONSTRUCTION • 24 INDUSTRY FORECAST FORUM •25 LETTERS TO THE EDITOR • 27 HPI CONSTRUCTION BOXSCORE UPDATE •78 HPI MARKETPLACE • 81 ADVERTISER INDEX

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� Select 151 at www.HydrocarbonProcessing.com/RS

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HPIN BRIEFBILLY THINNES, NEWS EDITOR

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HYDROCARBON PROCESSING JANUARY 2010 I 7

■ IEA speaks upin Copenhagen

During the United Nations Climate Change Conference in Copenhagen, Denmark, the International Energy Agency shared its blueprint on achiev-ing ambitious climate change goals while encouraging new investment for clean energy.

With energy accounting for 84% of global CO2 emissions, the IEA said it had analyzed what needs to be done to limit the long-term concentration of greenhouse gases in the atmosphere to 450 parts per million (ppm) of CO2 equivalent, in line with a 2°C increase in global temperature. The IEA believes that, unless new measures are taken, global energy-related CO2 emissions will reach 40 Gigatons (Gt) by 2030 (the world stood at 29 Gt in 2007) and con-tinue rising thereafter, whereas climate stabilization requires emissions to peak around 2020 and then decline.

According to the IEA, the world needs to retire a significant portion of today’s coal-fired electricity plants by 2030. These early closures around the world would equal today’s total coal-based power generation in Japan, the EU and the US. Around 60% of global electric-ity production in 2030 would need to come from a mix of renewables (37%), nuclear (18%) and plants fitted with carbon capture and storage (5%).

The bulk of the emissions reduction could be delivered by energy efficiency, accounting for over half of total abate-ment by 2030 in the IEA 450 Scenario. According to the IEA, energy efficiency is necessary for the deployment of the more expensive, low-carbon energy supply as it helps lowering demand first. IEA said that the additional invest-ment can be recouped by end users through lower energy bills; for industry, the additional $8.3 trillion of required investment would lead to $8.6 trillion in savings between now and 2030. HP

Foster Wheeler AG’s Global Engineering and Construction Group plans to work with PetroAlgae to develop commercial solutions that will allow existing oil refineries to convert micro-crop biomass into fuels that are functionally compatible with petroleum-based fuels in the current market. For refineries, the solutions are expected to evolve from the large-scale processing of PetroAlgae’s micro-crop biomass into green fuels. The two firms intend to create end-to-end market solutions for the large-scale production of green gasoline, diesel, jet fuel and specialty chemicals.

A recent report from Companiesandmarkets.com shows that Latin America’s thirst for oil has grown this decade. The region consumed 6.9 million bpd in 2001 and its appetite was expected to reach an estimated 7.7 million bpd by the end of 2009. For 2010, the region should have an average consumption of 7.9 million bpd, rising to approximately 8.6 million bpd by 2013. While consumption in Latin America grew from 2001–2009, overall oil production was flat and trending downward. The region pro-duced 10.3 million bpd in 2001, while, in 2009, it averaged an estimated 9.6 million bpd. The report sees this number rising to 10.8 million bpd by 2014. Meanwhile, oil exports have been slipping because demand growth has exceeded the pace of supply expansion. In 2001, the region was exporting an average 3.4 million bpd. The total is expected to fall to 1.9 million bpd by the end of 2009 and then is forecast to recover to 2.2 million bpd in 2014. Companiesandmarkets.com says the principal exporters will be Mexico, Venezuela, Ecuador and Brazil.

Caltex is planning to close its Kurnell refinery in Sydney, Australia. The closure signals a “cost efficiency drive” and is in response to flat earnings in 2009. “Global refiner margins remained under pressure in the second half of 2009 because of depressed demand and the expected growth in global surplus refinery capacity,” a report from Caltex said. Another contributing factor for closure was the stronger Australian dollar and higher crude oil prices that caused a precipitous drop in Caltex’s refining margins. Caltex’s margins fell to an average of about $2.60 a barrel in the second half of 2009, compared with an average of $9 in the first half. The company believes the refinery is ripe for closing because it manufactures outmoded lubricant products and faces declining feedstock sources. The closure date has yet to be announced.

Chevron Corp. recently released its budget for 2010. The company plans a $21.6 billion capital and exploratory spending program for 2010, a 5% decrease from projected 2009 expenditures. About 80% of the 2010 spending program is for upstream oil and gas exploration and production projects worldwide. Another 16% is associated with the company's downstream businesses that manufacture, transport and sell gasoline, diesel fuel and other refined products. Capital spending of $3.4 billion in 2010 is budgeted for global downstream operations. Included in the budget is $1.6 billion for projects in the US, primarily for refinery projects. Outlays in 2010 include projects in the company's refineries in Mississippi and California. The company's 50%-owned GS Caltex affiliate is also expected to continue development work on the upgrading of its Yeosu refin-ing complex in South Korea. In support of projects to commercialize the company's large natural gas resource base, downstream expenditures will be made in 2010 on gas-to-liquids manufacturing facilities.

Mission NewEnergy Ltd. has a five-year agreement to supply Valero with up to 60 million gpy of Jatropha-extracted biodiesel. Valero has the right to double that amount to 120 million gpy and to extend the term by an additional five years. The agreement represents gross revenue potential to Mission of over $3.5 bil-lion based on prevailing market prices, maximum volume and contract life. The first product shipment under the agreement is expected to occur during the second quarter of calendar year 2010. HP


HEINZ P. BLOCH, RELIABILITY/EQUIPMENT EDITOR

HPIN RELIABILITY

[email protected]


We quite obviously believe that reading is the key to profes-sional growth and that Mark Twain was right in stating that the man who refuses to read is no different from the illiterate person who cannot read. We also know that, while technical texts can be pricey, a book costing $100 will often alert its reader to the solu-tion to a million-dollar problem. In that case, the return on the investment would be 10,000:1. And so, it makes a huge amount of sense to put reading in your training plans and to have either a budgetary item or subsidy for books at your refinery. Reading and reliability improvements are related and should never be separated. A recent column alluded to the reliability professional’s job of identifying critical parts and to write detailed specifications that then facilitate their global procurement.

Coping with global procurement. Unless proven oth-erwise, you should assume that the lowest bidder utilizes neither quality control nor exacting specifications. Perhaps this explains why an entity is the lowest bidder. Again, you must provide and sometimes personally write a specification for these critical parts. Once critical spare parts (even the ones originating from vendors accepting your specifications and professing to have quality con-trol) are delivered to your facility, the job is far from finished. You must add value by personally verifying the full specification compliance of these parts. Alternatively, take responsibility by arranging for competent inspectors that verify specification com-pliance of the critical spare parts received. These parts should be accepted by the storeroom clerk only after compliance has been verified. The clerk can then proceed to tag and preserve the parts for future use.

As to the misguided direction where some in the HPI are headed, we recently received a very strong message from a well-known asset management consultant. After visiting a major refinery, he consid-ered its management system completely broken. He expressed the view that, due to past failures, decision makers now seem afraid to make any decision that carries even a whiff of risk—so they do nothing! He met a young reliability engineer who had poured heart and soul into a project, submitted it to the plant manager and heard nothing—not even the simple courtesy of an acknowledgment! The consultant was struck by this refinery’s bewilderment why so many of the young men and women who should be its lifeblood and future were quitting their jobs. Those who remained seemed to have the attitude, “just tell me what you want, manager, and I will get myself involved somehow.” Of course, the manager doesn’t have a clue, so nothing of substance gets done at that location.

Then there are the many recurring accountability issues men-tioned by the asset management consultant. In one review meeting a reliability engineer was asked why he thought he had to spend so much time in the plant during turnarounds watching things like gasket replacements. His answer? “Because I’m held directly responsible even though the fault may be solely attributable to the

carelessness of a mechanic. The mechanic will not be held account-able, but I will be.” Word spreads, and we heard rumors that, in 2007, not a single graduating engineer accepted the employment offer made by one particular major oil company.

Shunning cheap temporary fixes. A huge problem at one refinery seems to be its constant pursuit of cheap temporary fixes. Managers at this location have no discernible concept of the bigger overall picture and have enunciated neither sound strategy nor any-thing resembling long-term improvement. At one location, a highly experienced management consultant judged as totally inoperable the functional asset hierarchy on which all cost and reliability data are based. Upon being briefed about the issue, the refinery managers considered corrective action “too difficult” and elected to again do nothing but maintain a very precarious status quo.

Which gets us back to the original point and where global pro-curement involves all kinds of service providers. Once we identify the most successful service providers, we must ascertain that they will continue to add value every step of the way. They will join us in viewing every maintenance event as an opportunity to upgrade. Upgrading means strengthening the weakest link in the compo-nent chain whenever cost-justified. It will make the operator’s life easier and will open wide the (presently very narrow) door to operator-driven reliability (ODR). Conscientious upgrading will have merit beyond that of traditional maintenance.

Whatever your job function, you can make a big difference and be an effective change agent. Start by understanding or personally defining critical spare parts and take it upon yourself to describe them in an appropriate purchase specification. Read what others have done in this regard, how they persevered and excelled not just recently, but decades ago. Other facilities became best-practices companies by having professional employees totally involved—these employees took the lead in advancing the reliability improve-ment process. They were among the first to view every maintenance event as an opportunity to upgrade components and machines and initiated action where it was both feasible and cost-justified.

If you are not a manager, write down what you have found in the various books and articles and discuss it with your manager. If he doesn’t take action, find someone who will. And if you are a manager, do something about the critical situation we have accurately described in this column. A bit of introspection will let you know who you really are. Make adjustments in your course, which is another way of asking you to either lead, follow, or move out of the way. HP

More about unreliability, global procurement and you

The author is HP’s Reliability/Equipment editor. A practicing engineer and ASME Life Fellow with close to 50 years of industrial experience, he advises process plants on maintenance cost-reduction and reliability upgrade issues. Of his 17 textbooks on reliability improvement subjects, 11 are still in print and are being updated periodically. His 2nd edition, Practical Lubrication for Industrial Facilities, was released in May 2009.

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TIM LLOYD WRIGHT, EUROPEAN EDITOR

HPIN EUROPE

[email protected]


Where the common ground between my best friends in engineer-ing and I becomes a parkland with fireworks is when we share the “aha moments.” I suspect it’s from that curious, excited child in my friends that they confide new ways of seeing things, such as saving energy in their plants, or sharing a conventional wisdom or two.

Conventional wisdoms can be both oppressive and hugely diver-sionary. For example, the English were laying steel cables from a small beach in Southwest Cornwall to Newfoundland and the Antipodes even as Marconi was having his “aha moments” with an antenna at Pondhu station on a nearby hillside. Yes, it turns out that there was a scornful relative of the “aha moment” for a sad lot of investors in this epic-age, deep-sea, transglobal telegram cable project. Let’s call it the “Duh! experience.”

The golden age of ‘Duh’! We live in a golden age of these “duh” moments; just think subprime. The stupidity of stacking up derivatives on the back of people encouraged to lie about their creditworthiness is enormous, and with, hindsight, it stops one in one’s tracks. After the fact, there’s this rush of common sense, like air entering a vacuum. In the sphere of energy and sustainability, the Dubai crisis ticks all the boxes of a “Duh! experience.”

Déjà vu all over again. At first, I get it. The United Arab Emirates, the world’s second largest emitter of carbon dioxide (CO2) from energy per capita, decides to diversify its economy. The “resource curse” tells us that not much good comes from having too much oil in centralized hands.

But for Dubai to diversify by building a long-haul tourist des-tination and business hub with the most carbon-intensive attrac-tions and accommodations imaginable, and at a time like this? Consider that, since 2003 and with the worst dry period on record locally, Australia has been desperately struggling to drought-proof its desert and even its pastoral communities. The sandy, city state of Dubai, meanwhile, has produced the innovative chilled swim-ming pool, a shopping mall ski resort and desalinated irrigation for a golf course.

Holiday destinations. I do know people who’ve taken a vacation in the Middle East, but this idea hasn’t exactly tickled my family’s fancy. Inspired by Ron Oxburgh, the former non-executive chairman of Shell, my family hasn’t traveled on vacation by air since early 2006. Along with 63% of the European citizens, we’re convinced that climate change is a “very serious” issue.1 With a family goal to reduce our carbon footprint, even short-haul flights are the worst CO2 budget busters there are. I’m not saying that Dubai’s going to weep for not having the Wrights to stay, but we’re not on our own over here.

Carbon-busting initiatives. In the UK recently, whole cities have been signing up to the new “10:10” campaign, sponsored by the makers of the Age of Stupid documentary. It encourages individuals, companies and cities to reduce their greenhouse gas emissions by 10% in 2010. The front benches of the governing and opposition parties in the UK have already signed up.

So what’s this got to do with the hydrocarbon processing indus-try (HPI)? Well, from what I admit is a particularly European perspective, and from an oil industry worker living in a coun-

try that still aims to eradicate oil largely from private transport and home heating by 2020, I think part of our industry (the HPI), if not all, is heading for one of these “Duh! experiences.”

The International Energy Agency (IEA), financed by the OECD to warn

on energy security and climate change, says that a delay of just a few years in enacting a massive decarbonization of the energy industry could render a safe outcome for the world’s population “completely out of reach.” If everything even vaguely on the table for Copenhagen had been enacted, we’d still be in line for a scenario that calls for significantly more than a 2°C increase in global temperatures—the level at which it is hoped would avoid a dangerous outcome.

And yet, major energy companies, large refiners and other vested interests are still trying to stop the US and Australia from participating in any meaningful way, with their pump-top leaflets, questionable rallies and constructed controversies. Well, they can have business as usual. OECD oil demand will continue to fall from its peak in 2005 because the costs are just so burden-some. But sea levels, says the IEA, will eventually shut down every coastal refiner under its business as usual, or “reference scenario.” (As if that was all we would lose!)

And for the bright engineers who love the “aha moment” of solv-ing real problems, the shame is they don’t get to. The $10.5 trillion of new investment to achieve the IEA’s alternative scenario, and to keep projected warming to below 2°C, is a journey full of real challenge.

It’s a journey that would reunite engineering with the enlight-enment project set when the institutes and great academies were being formed, which is of making the world a better place for all humanity. HP

LITERATURE CITED 1 Eurobarometer Survey, December 2, 2009.

The author is HP’s European Editor. He has been active as a reporter and confer-ence chair in the European downstream industry since 1997, before which he was a feature writer and reporter for the UK broadsheet press and BBC radio. Mr. Wright lives in Sweden and is the founder of a local climate and sustainability initiative.

Duh! Business as usual will not be good for the HPI

■ Business as usual is not

an option anymore for the

HPI or modern industry.


PAULA HOLLYWOOD, CONTRIBUTING EDITOR

HPINTEGRATION STRATEGIES

[email protected]


Applying tuneable diode laser spectroscopyto help reduce energy consumption

According to the US Department of Energy, industry accounts for about a third of all energy used in the US. Despite the recent drop in energy prices, energy remains the second leading cost pres-sure (behind only raw materials) affecting manufacturers. Some of the biggest culprits are incinerators, crackers, process heaters and other energy-intensive combustion-based equipment.

The harsh operating conditions associated with combustion analysis applications can eat up a sensor in no time, resulting in inaccurate and unreliable sensor measurements. This can make it nearly impossible to control these processes adequately. However, new analysis techniques, such as tuneable diode laser spectroscopy (TDLS), can improve efficiency, maximize throughput, reduce emissions and improve safety in combustion analysis applications. ABB, Siemens, Vaisala and Yokogawa all offer TDLS technology for process measurements.

Reduce energy consumption. Most energy-intensive operations, such as those found in a refinery or chemical plant, experience considerable variability in energy consumption due to changing operating conditions, equipment degradation, fluc-tuating market conditions and inefficient control strategies. As a result, plants typically consume more energy than necessary, yet are unable to improve efficiency due to the inability to collect and analyze real-time performance data. Frequently, the goals of opti-mizing efficiency and maximizing throughput are at odds with the need to reduce emissions and ensure plant and personnel safety. Effective energy management is essential for a “triple bottom line” business strategy that addresses social, economic and environmen-tal concerns. TDLS contributes to a triple bottom line strategy by helping increase throughput and reduce energy costs, while supporting safe and environmentally responsible operations.

Advanced process control (APC) systems require sensitive and accurate process measurements in real time, or near-real time. APC reduces process variability and inefficiency, improves product quality and provides for more stable operations. With few exceptions, current process analytical techniques lack the speed, accuracy and sensitivity to provide reliable measurements for APC. Online optimization goes beyond APC to optimize a process based on an economic objective function. This is becom-ing more important in applications where profitability depends

upon improving quality while maximizing material utilization and minimizing energy usage.

Historically, obtaining reliable quality measurements in time to impact control has been an issue in combustion control applica-tions. The current best practice utilizes a zirconia sensor for point measurement of oxygen. In applications requiring multiple mea-surements, point measurement cannot provide a representative sample, making it both error-prone and potentially dangerous. Pro-cess oxygen measurement requires samples to be extracted and then transported to an analyzer for conditioning and analysis. This slows response time, adds cost and degrades measurement accuracy.

TDLS in combustion analysis. Inefficient combustion can be attributed to the air/fuel ratio. Too much excess air (air rich) results in efficiency loss and increased NOx emissions, while too little excess air (fuel rich) is downright dangerous. Carbon monoxide measurement provides an indication of fuel-rich conditions, while oxygen measure-ment indicate air-rich conditions. The optimum control point is the lowest possible excess air value that does not cause the system to enter into an unsafe condition or violate emissions limits.

TDLS technology is an innovative measurement technique that utilizes semiconductor lasers to detect a variety of gases at trace levels in the part-per-million (ppm) or part-per-billion (ppb) range. Tuneable lasers, which enable miniaturization of transmis-sion and receiving units, provide highly sensitive, quantitative measurements with fast response times without the need for reca-libration. The lasers can be tuned to detect specific constituents independent of process gas concentrations.

TDLS enables high-performance measurements in real time, even in challenging process environments. Exact performance specifications may vary somewhat according to supplier; however, the benefits are universal (Table 1).

To date, the most widely reported application of TDLS has been for combustion control. However, the technology poten-tially offers much wider applicability. In refineries, it can monitor CO, CH4 and O2 in burner flameout applications, and identify process tube leaks.

Energy can be the largest component of a manufacturer’s cost structure. Despite the recent drop in energy prices, costs are expected to trend upward over the long term. A willingness to apply state-of-the-art technologies can have a significant impact on the success of energy management programs. Technologies, such as TDLS, that can improve performance and provide quick ROI, can have a significant impact on the bottom line. HP

The author, a senior analyst at the ARC Advising Group in Dedham, Massachusetts, has nearly 30 years’ experience in the areas of sales and product marketing in industrial field instruments that utilize a vast array of technologies including magnetic, Coriolis, radar, electrochemistry, capacitance and ultrasonic.

TABLE 1. Features and benefits of TDLS technology

Feature Benefit

In-situ analysis Sample conditioning not required

Fast response Real-time data for APC

Tuneable laser Interference-free analysis

Non-contact sensor Suitable for operation in harsh environments

Optical sensor Low maintenance



HPIMPACT

Struggles for US refiners expected to continue

In a recent refining industry piece, Deutsche Bank analysts took a gander at the US refining industry and wondered if the worst has passed for refiners. In short, they think not. ConocoPhillips CEO Jim Mulva told the analysts that the company will not engage in any refinery sales, with the hope that the market for refiners will turn around over the next two years. If there is no market improvement, Mr. Mulva said ConocoPhillips would simply shutter the refineries in ques-tion. Deutsche Bank sees this as good news for independents, “if they can last that long.” The report also said that Mr. Mulva is consid-ering “canceling both a major Saudi refinery

project at Yanbu and a major refinery upgrade at Wilhelmshaven in Europe.”

The Deutsche Bank analysts agree with this train of thought, given that current US utilization rates are at 80% and demand continues to be down (Fig. 1), with total products demand at its lowest level at the end of October since 1998. “The brave are getting long with the idea that things cannot get any worse—we disagree and have cited the example of secularly challenged indus-tries, such as newspapers versus the Internet, to support this idea,” the report said. “The bull argument is that oil demand recovers (it is not, despite third quarter GDP growth) and that will cause OPEC to increase pro-duction (they already have) and that causes wider heavy-light to widen (it has not).”

While the current 80% utilization rate has resulted in less backlog of refined prod-ucts inventory (Fig. 3), the analysts are still concerned with oversupply, especially when factoring in inventory at sea. Still, recent refinery shutdowns may assist in chipping away at excess distillate inventory (Fig. 4). “Sunoco announced that it would indefi-nitely idle Eagle Point, New Jersey; while Valero announced in early September that it would extend the Aruba shutdown, con-tinue its Corpus Christi, Texas, coker and FCC shutdown and run other cokers at reduced rates until the coking economics outlook improves,” the report said. Other recent decisions that may help with inven-tory management include Valero’s decision to permanently close its refinery in Delaware

BILLY THINNES, NEWS EDITOR

[email protected]

18,000

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kb/d

5-yr historical range 2009 2008

Source: Deutsche Bank, EIA

US oil product demand. Demand at the end of October was at its lowest level since October 1998.

FIG. 1

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20

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US distillate inventories appear over-supplied.FIG. 3

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3,200

3,600

4,000

4,400

4,800

kb/d

US distillate demand for 2009 did not paint a pretty picture.

FIG. 2

65

70

75

80%

85

90

95

100

Jan

Jan

Jan

Feb

Feb

Mar

Mar Apr

Apr

May

May Jun

Jun

Jul

Jul

Jul

Aug

Aug

Sep

Sep

Oct

Oct

Nov

Nov

Dec

Dec

5-yr historical range 2009 2008 2007


When comparing US refining utilization from 2007–2009, it should be noted that recent refinery shutdowns could help the current situation.

FIG. 4

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City, Delaware, and Marathon’s scheduled downtime for early 2010 at its refinery in Garyville, Louisiana.

The EU’s ETS at a glanceCarbon trading, carbon taxing and other

forms of regulating greenhouse gases have been hot topics of conversation of late. Since it appears that these concepts will be domi-nating thought and affecting business plans for companies in the HPI into the foresee-able future, it is not a bad idea to examine the most established cap-and-trade system currently in existence, the one marshaled into form by the European Union (EU). The EU’s Emissions Trading Scheme (ETS) is basically a commodities market—a mar-ket-based policy tool that sets a cap on CO2 emissions from specific sectors. Analysts from Orbeo (www.orbeo.com) have studied the ETS extensively and have been briefing interested parties on their findings. Orbeo reports that ETS sources covered by the pro-gram receive (or purchase through auctions) emissions allowances. Flexibility is allowed;

plants can buy and sell allowances on a

market according to needs. Carbon offsets and carbon credits are flexibility mecha-nisms that lower the cost of compliance to cap-and-trade. Carbon credits are generated from emissions-reducing projects and can be used in addition to allowances (generally up to a limit) in a cap and trade program.

Emissions of CO2 by industry in Europe are capped by quotas, known as European Union Allowances (EUAs), and handed out at the individual plant level. The CO2 price that emerges reflects the cost of reduction the emissions. Carbon credits are allowed, such as the Certified Emission Reductions (CER) granted by the UN, for emission reductions achieved in emerging countries. The evolution of this price in the future will depend on the industry constraints. Higher emission reduction objectives thus mean a higher CO2 price.

Updated EU ETS balances. According to Orbeo, EU ETS emission forecasts should be revised down by 40 Mt for 2009, and overall by 2% to 3% in the following years, to account for slow recovery from the global

recession. CER issuances should stand at 1.3 Gt, which assumes significant acceleration. For 2009, expected issuance volumes sink down to 155 Mt. Orbeo believes the system is still slightly short to 2012 (133 Mt).

First implications. It is now confirmed that the EU ETS will exist to 2020 and beyond. Thus, there will be one continuous trading period, with full EUA banking from Phase II (2008–2012) to Phase III (2012 plus) ensured. Orbeo predicts a large increase in auctioned volumes. In Phase III, there will be new rules on auctioning. Utilities will see 100% auctioning from 2013, with exemp-tions for power plants in countries where more than one-third of power is produced from a single fossil-fuel source and income per capita is less than half of the EU average. Sectors with low carbon leakage risk will see 20% auctioning in 2013 increasing to 70% through 2020, with full auctioning from 2027 onward. Sectors with high carbon leakage risk are to have 100% of allowances distributed for free. This free distribution is based on 10% of the best available technol-ogy benchmark in 2007–2008 and should cover 80% to 90% of sector needs. HP

Imports mb/d (left-hand scale)Imports as % of production (right-hand scale)

0500

1,0001,5002,0002,5003,0003,5004,0004,5005,000

Jan-

06

Jun-

06

Dec-

06

Jun-

07

Dec-

07

May

-08

Nov-

08

May

-09

Oct-

09

10

%

1214161820222426

Impo

rts

mb/

d


US product imports 2006–2009: Imports as a percentage of US product production trended downward in 2009.

FIG. 5

0500

1,0001,500

2,0002,5003,000

3,5004,000

4,5005,000

EUA

2006

Trad

ed v

olum

es 2

006-

2008

in M

T

2007 2008

Secondary CERPrimary CER/ERUOther markets

Source: SG Commodities Research

Carbon markets traded volumes from 2006–2008.FIG. 6

0

15

30

45

60

75

90

105

2006

Tota

l EU

ETS

and

CDM

tran

sact

ion

valu

es in

€ b

illio

n

2007 2008Source: SG Commodities Research

EUASecondary CERPrimary CEROther markets

Total EU ETS and Clean Development Mechanism (CDM) transaction values.

FIG. 8

26%

30%6%

8%

3%

11%

9%7%

EUA exchangeEUA OTC clearedEUA OTCPrimary CER/ERUSecondary CER exchangeSecondary CER OTC clearedSecondary CER OTCOther markets

Source: SG Commodities Research

World traded carbon volumes in 2008 by market segment.FIG. 7

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HPINNOVATIONS


SELECTED BY HYDROCARBON PROCESSING EDITORS

[email protected]

Pressure-relief software awarded first US patent

Farris Engineering Services, a business unit of Curtiss-Wright Flow Control Com-pany, has announced that its iPRSM prod-uct, claimed to be a revolutionary software for pressure-relief system management, has been awarded a US patent, with a second application approved for award. The product has a unique Web-based design and contains innovative impact analysis capabilities.

iPRSM is a multifunctional software package for designing, auditing and docu-menting the pressure-relieving capability of process systems in the petroleum, petro-chemical, hydrocarbon processing, refin-ing and power-generation industries. The software supports process system engineers in maximizing the safety of personnel, pro-cesses and facilities; minimizing operational interruptions and losses related to overpres-sure and documenting changes to pressure relief systems.

“By standardizing pressure-relief system design and audit methodology, monitoring pressure conditions and identifying poten-tial problems, iPRSM makes compliance activities efficient for various industries,” says Josh Kolenc, vice president, software engineering. “From a cost perspective, it also reduces the risk of equipment repair, downtime and lost production.”

Web-based for system integrity. The patented Web-based product allows iPRSM to be deployed companywide for design and sizing of overpressure equipment, safety and change management, and regu-latory documentation. With many users of the product at multiple locations being able to view and work on the process system in real time, iPRSM protects the system’s integrity by preventing the duplication of engineering changes or implementing con-flicting changes.

When applied to evergreen system design, iPRSM can integrate equipment, instruments, piping and pressure-relief devices across multiple locations to cre-ate a protected system. Applied to exist-ing systems, iPRSM creates a centralized engineering drawing/document repository, a pressure-relief database that includes as-operating data from all sites, and a task list for addressing concerns.

Impact analysis tool supports changes. iPRSM’s Impact Analysis Tool allows modeling of code or engineering changes at any stage in the process life cycle, from design through full operation. When as-operating data and the planned alteration to the system configuration are input, iPRSM identifies the protected system and the various relief scenarios that could be affected by that change prior to its implementation. iPRSM can then vali-date the adequacy of the safety relief sys-tem under the new conditions or identify necessary adjustments.

“The Impact Analysis Tool, combined with iPRSM’s other capabilities helps ensure that process plants effectively meet the requirements of 29 CFR 1910.119 in a very cost-effective manner,” Kolenc explains.

iPRSM also has the capability of recreat-ing previous system conditions that were in effect prior to upgrades or other changes to equipment, flow or pressures. This feature simplifies troubleshooting and assists in documenting the history and sequence of changes to the process system.


First software to mapthe automation genome

PAS, a global supplier of Operations and Automation Effectiveness software and services, announces the immediate release of Integrity automation genome software. This unique software maps the automation genome, comprising the data-bases, programs, displays, and intercon-nections within and among all automation systems in a plant, including distributed control systems, SCADA systems, safety instrumented systems, data historians, advanced process controls and instrumen-tation databases.

By mapping a plant’s automation genome, Integrity software creates new possibilities for fundamentally transform-ing the productivity and safety perfor-mance of industrial plants. By identifying configuration defects and safety vulner-abilities, costly operational problems can be resolved quickly or avoided entirely. Tracking and historization of configu-ration changes ensures that the value of automation systems does not deteriorate over time. Users can access Integrity’s vast knowledge base through the graphical interfaces of their existing DCS and his-torian workstations.

Integrity Software also serves as a knowledge retention and collaboration platform that captures implicit knowl-edge, contextualizes it, and makes it acces-sible. This ensures that knowledge from experienced personnel is made available to everyone who needs it. Additionally, as e-mail has become a primary means of exchanging significant plant information, Integrity software includes the ability to tag and incorporate important e-mails in the knowledge base.

One of the “killer” applications of the new Integrity automation genome software is the Disaster Recovery module that pro-vides a mechanism for automatic backup and archiving of system and database files, documenting restoration procedures, and creating object-to-file associations.

In the event of a natural or man-made disaster, it aids in system recovery, restoring corrupted files, or providing the facility to roll back to a point in time.


New virtual reality training solution commercially available

Invensys Operations Management, a global provider of technology systems, soft-ware solutions and consulting services to the process and manufacturing industries, has announced the commercial availability of its new EYESim virtual reality immersive training solution. The first industrial virtual reality training solution based on first-prin-ciples simulation and augmented reality, EYESim technology enables engineers and operators to see and safely interact with the plant and the processes they control.

As HP editors, we hear about new products,

patents, software, processes, services, etc.,

that are true industry innovations—a cut

above the typical product offerings. This sec-

tion enables us to highlight these significant

developments. For more information from

these companies, please go to our Website

at www.HydrocarbonProcessing.com/rs and

select the reader service number.

HPINNOVATIONS

Using and applying gaming and other skill sets most familiar to younger employ-ees, the EYESim solution also appeals to employees new to the engineering and plant workplace, as well as experienced engineers. It combines virtual reality technologies with high-fidelity process and control simulation, computer-based maintenance and documentation manage-ment, and other applications to provide a highly realistic and safe training environ-ment for improving operating efficiency and skills. Simulations are driven by the company’s DYNSIM high-fidelity process simulator, FSIM Plus software, I/A Series control system emulation and other com-patible programs.

“The increasing complexity of plants, combined with a changing workforce, demands next-generation tools that can safely and interactively train new opera-tors and engineers without putting them, the community or the environment at risk,” said Tobias Scheele, vice president, advanced applications, Invensys Opera-tions Management. “This system provides a stable, realistic environment for practicing

routine operational and maintenance func-tions, as well as rarely performed volatile tasks such as plant shutdowns. In addition, using computer models of real equipment allows endless experimentation without ever taking the equipment offline, mitigat-ing risk to production as well.”

By merging virtual plant imagery with screens from asset management or other application software, the Invensys solution creates a computer-generated representa-tion of either a real or proposed process plant. Using a stereoscopic headset, trainees enter a completely immersive environment in which they can move throughout the plant. Such freedom is possible because the virtual environment is rendered at 60 frames per second, significantly faster than what can be achieved by traditional, non-real-time rendering.

EYESim technology is geared toward the energy, chemical, oil and gas, and other vital process industries as they face knowl-edge management, training and retention challenges brought on by an aging and dwindling industry workforce.


New capabilityimproves performance

Emerson Process Management has inte-grated machinery protection and predic-tion of critical mechanical equipment with its DeltaV digital automation system. This new capability directly supports users’ goals for improved availability and performance. As turbomachinery and mechanical equip-ment condition deteriorates, performance and throughput decrease and unplanned shutdowns become more probable. When plant operators have visibility to the per-formance of their high-stakes assets, they can make process adjustments and reduce process disruptions.

In traditional control systems, integra-tion is complex and expensive, requiring Modbus and system expertise as well as specific machinery knowledge. Typical machinery protection systems can require more than 2,000 steps and up to five days to complete the integration process. With this many steps, network issues, additional testing time and nuisance alarms are easily introduced. The barriers to undertaking integration are prohibitive, even though

Why can we say this already at the beginning

of the year?

2010 was a very

ww

w.h

oerb

iger

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HPINNOVATIONS

the payback from better information for operators is significant.

Emerson’s integrated machinery pro-tection and prediction solution, a key component of the PlantWeb digital plant architecture, easily connects to the Del-taV system in three simple steps that take less than 10 minutes. Asset parameters are scanned, selected and imported into the DeltaV system from AMS Suite predictive maintenance software and the CSI 6500 Machinery Health Monitor. After import, the DeltaV alarm banner is automatically populated and the system is fully config-ured with function blocks that can be fur-ther used in control strategies.

Integration in the operator interface also includes templates for vibration bar graphs, vibration values and auto highlighters to enable any DeltaV operator graphic to come alive with valuable operator machin-ery health information.

“The benefits of combining process information and machinery health have long been understood, but this is the first time the two have been integrated automat-ically and so extensively for engineering,

operations and reliability personnel,” said Craig Llewellyn, president of Emerson’s Asset Optimization division.

Emerson also provides PlantWeb Ser-vices to help users design, install, and implement machinery protection and prediction. With these new capabilities, the DeltaV system provides an integrated solution for process control, process safety, machinery protection and prediction.


Asset management expertise creates valuable new capabilities

Emerson Process Management and Meridium announced a unique partner-ship to deliver enhanced asset management capabilities to their customers in the pro-cess industries. By combining the power of Emerson’s PlantWeb predictive intelligence with Meridium’s advanced analytics and decision support technology, customers can now more effectively manage and maintain their most critical production assets.

Emerson and Meridium have been work-ing together for several months to develop the new AMS Suite: Asset Portal v4.0 powered by

Meridium. The new product provides inte-gration in realtime to other AMS Suite appli-cations to link asset diagnostics with business metrics and key performance indicators. Built upon Meridium’s Asset Performance Man-agement Framework, the AMS Asset Portal v4.0 includes pre-defined analysis, views and reports of AMS Suite information. Power-ful query, reporting, and graphing capabili-ties enable users to perform custom analysis. Select Meridium application modules are also available for use with AMS Asset Portal. These options provide advanced metrics and scorecards, data management collected using handheld devices, and integration with com-puterized maintenance management systems such as SAP PM and IBM MAXIMO.

Also announced was Emerson’s PlantWeb Services offering to cost-effectively design, implement and quantify the business benefits of asset strategies for users. Meridium’s best-practice deployment models are available as part of the PlantWeb Services offering. The solution extends to mechanical equipment, instruments, control valves, electrical switch-gear, process equipment and fixed assets.


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South AmericaBG Group has a joint venture agree-

ment with Petroleo Brasileiro SA focused on developing floating liquefied natural gas (FLNG) as an additional option to commer-cialize the associated natural gas reserves in the Santos Basin offshore Brazil. Under the agreement, FEED contracts will be awarded for a new FLNG vessel. The vessel will oper-ate close to the planned Santos Basin floating production, storage and off-loading (FPSO) vessels. The vessel will process and liquefy the associated natural gas from the pre-salt fields before offloading to LNG ships.

The FLNG processing capacity is antici-pated to be up to 14 million cubic meters per day of associated gas. The 3 million tpy of LNG produced would be shipped either to Petrobras-operated regasification termi-nals at Pecém and Guanabara Bay to supply the Brazilian domestic market or exported to other global markets.

CB&I has a contract valued in excess of $1.4 billion with Refinería de Carta-gena SA (REFICAR) for the engineering, procurement services and construction of a new refinery with processing capacity of 165,000 bpd, adjacent to REFICAR’s refinery in Cartagena, Colombia. CB&I’s scope also includes revamping the existing 80,000-bpd refinery. The overall project aims to relieve regional refining constraints and enable REFICAR to produce ultra-low-sulfur gasoline and diesel from heavy crude. CB&I will provide project management and the engineering, procurement services, fabrication and construction for the new refinery, including the following major components: crude and vacuum distillation; fluid catalytic cracker naphtha hydrotreater; diesel hydrotreater; hydrocracker; hydro-gen plant; sulfur plant; delayed coker; and power generation. The project is scheduled for completion in 2012.

EuropeABB has an order worth $26 million

from Hellenic Petroleum SA to provide an integrated power and automation system for the upgrade of Hellenic Petroleum’s Elefsina refinery, west of Athens, Greece. ABB will design, supply, install and commission the electrical and automation system to power the

refinery. The turnkey electrical solution aims to strengthen the reliability and quality of power supply to the refinery, while improving energy efficiency and reducing overall elec-tricity consumption and costs. The project is expected to be completed by 2010.

ABB will supply medium-voltage equip-ment including the latest gas-insulated switchgear and air-insulated switchgear. ABB will also install intelligent low-volt-age switchgear as well as a fully automated power management and load shedding sys-tem based on the company’s automation platform and compatible communication networks. Integrating the electrical and automation system on ABB’s common plat-form provides additional benefits includ-ing reduced maintenance, engineering and overall life-cycle costs.

The Shaw Group Inc. has a contract with Petkim Petrochemical Holding AS to provide engineering and procurement services and additional study work for an ethylene plant capacity expansion in Aliaga, Turkey. Shaw built the original 300-ktpy

plant in 1986 and performed basic engi-neering for the previous capacity revamp to 520 ktpy in 1999. The new expansion will increase ethylene production capacity by approximately 10%.

Middle EastSamsung Engineering has a $2.73 bil-

lion contract from Abu Dhabi Oil Refin-ing Co. for utilities and offsite work on the Ruwais refinery expansion project (RRE). Samsung’s work is set for mechanical com-pletion by April 2013 and is expected to supply utilities into the complex to help produce an additional 400,000 barrels of oil. Samsung Engineering will perform engi-neering, procurement and construction on a lump-sum turnkey basis. The investment for the RRE project exceeds $10 billion, and is to be executed mainly by Korean contrac-tors, including SK E&C and GS E&C.

Technip has a lump-sum turnkey EPC contract from Abu Dhabi Gas Industries Ltd. (GASCO) worth approximately $415 million for a project to revamp existing facil-ities to support an increase in oil production from the new Abu Dhabi Co. for Onshore Oil Operations facilities and accommodate up to 150 million scfd of additional associ-ated gas from the existing Asab, Shah and Sahil oil fields. Technip is responsible for the installation of a new booster compres-sion station, transfer lines, debottlenecking of existing ASAB 0 facilities and diverting feed flow from ASAB 0 to ASAB I/II by installing a new compressor, transfer lines and other associated facilities. This project will be executed by Technip’s operating cen-ter in Abu Dhabi, United Arab Emirates. The first phase will be completed during third quarter 2012 and the remaining phase during second quarter 2013.

Asia-PacificShell Chemicals Ltd. recently had a

successful startup of its new monoethylene glycol (MEG) unit at the Shell Eastern Pet-rochemicals complex in Jurong Island, Sin-gapore. The capacity is 750,000 tpy of MEG. The complex also includes a new 800,000-tpy ethylene cracker, a butadiene plant and modifications to Shell’s Bukom refinery, which are planned to start up in early 2010.

TREND ANALYSIS FORECASTINGHydrocarbon Processing maintains an extensive database of historical HPI proj-ect information. Current project activity is published three times a year in the HPI Construction Boxscore. When a project is completed, it is removed from current listings and retained in a database. The database is a 35-year compilation of proj-ects by type, operating company, licen-sor, engineering/constructor, location, etc. Many companies use the historical data for trending or sales forecasting.

The historical information is available in comma-delimited or Excel® and can be cus-tom sorted to suit your needs. The cost of the sort depends on the size and complex-ity of the sort you request and whether a customized program must be written. You can focus on a narrow request such as the history of a particular type of project or you can obtain the entire 35-year Boxscore database, or portions thereof.

Simply send a clear description of the data you need and you will receive a prompt cost quotation. Contact:

Lee NicholsP. O. Box 2608

Houston, Texas, 77252-2608Fax: 713-525-4626

e-mail: [email protected].

INDUSTRY FORECAST FORUM

24

In early December, Hydrocarbon Process-ing’s editors and a panel of experts convened a forum to discuss the outlook for the HPI into 2010 and beyond. The forum took place at the Omni Hotel in Houston, Texas, and was thick with audience participation, nuanced positions and well-researched pre-dictions. One of the featured presentations was by Bill Sanderson, president and CEO of Purvin & Gertz. He said that he expects global economic growth to resume, with

his outlook for US GDP growth to increase 2.5% to 3% in 2010. Challenges to this prediction, he said, would be the strength of the dollar and inflation.

“We don’t expect to be back to where we were in 2007 until 2011,” Mr. Sanderson said. “We’ve lost several years of growth and it had a significant effect on capacity utili-zation. Looking forward, we see continued growth in diesel gas oil demand combined with flat petroleum gasoline demand.”

Demand for bottom of the barrel prod-ucts like residual fuel has been declining for a long time globally because of displacement by natural gas and efficiency improvements. However, Mr. Sanderson noted that bun-ker fuel for long distance marine travel has increased due to the growth of the global economy which propels the need to ship goods around the world. With that in mind, he said that global bunker fuel growth will offset the decline in residual fuel.

Prices and margins. Mr. Sanderson stressed an analysis of the feedstock slate to determine future prices and margins. An important part of profitability is the conver-sion part of the refinery that converts resids from heavy products to light products.

“We’ve got ourselves into a situation where the difference between light and heavy products is quite narrow. The reverse will happen when we have to increase pro-duction. That incremental production increase will be the heavier grades of crude oil,” Mr. Sanderson said.

Rounding out his remarks, Mr. Sanderson reiterated that recovery starts in 2010, with Asia leading the way. He also said to expect increased production from OPEC and refin-ery closures in US and Europe. The specter of closure looms large especially for weaker facilities. In short, margins will recover for refiners but 2010 will be a tough year.

Other featured speakers at the forum included Kimberly Bowers of Valero, Michaela Greenan of Ernst & Young and Pierre Latour of Clifftent, Inc. Hydrocarbon Processing’s editors also revealed research from the HPI 2010 Market Data Book (to order, visit www.gulfpub.com). For more in depth profiles of each speaker’s remarks and pictures from the event, please visit our blog at www.hydrocarbonprocessing.com/hpinformer. HP

Bill Sanderson of Purvin & Gertz was a featured speaker at Gulf Publishing Company’s Industry Forecast Forum.

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LETTERS TO THE EDITOR


[email protected]

Advocating the abandonment of MPC

Regarding Zak Friedman’s three “HPIn Control” columns on APC designs for minimum maintenance in the June (p. 90), July (p. 13) and August (p. 13) 2009 issues of Hydrocarbon Processing, I fully agree with Mr. Friedman’s suggestions to prune multi-variable controller (MPC) matrices in order to mitigate maintenance and operations difficulties. In many cases, I would go a step further and consider abandoning the MPC altogether in favor of revisiting what can be accomplished with well-designed DCS-level regulatory controls. In a surpris-ing number of cases, this will result in more optimal and robust performance, while the demands of MPC go away altogether.

This may sound like strong medicine to the MPC generation, but, in my opinion, the downside of MPC over the past 20 years has gone greatly under-reported. In recent years, concerns are finding voice regarding “maintenance” and “sustainability” issues, but a closer look will often reveal that many MPC applications have been problematic all along, not withstanding the great tradition of “successful” project completion rituals.

Typical distillation column regulatory controls are well depicted by Mr. Friedman’s Fig. 1 (July issue), with the addition of a

steam-to-feed ratio control, a high-pressure safety override and replacement of the top temperature controller with a pressure-com-pensated temperature or a more sophisticated inferential where warranted. This fundamen-tal configuration is often rearranged to fit the particular column, but overall it is a good starting point, and often a finishing point, for many column control designs. MPC, whether spartan, as Mr. Friedman recommends, or fully dandified, as is the industry norm, has little if anything more to contribute, except expense and operational complexity.

Utilizing column pressure as an MV is a good example of something MPC design-ers habitually do, but which rarely works in practice. Pressure is not a suitable handle for composition control. I agree with its viabil-ity on paper, but in practice I’ve never met a process engineer or operator who agreed with throttling pressure like a valve for com-position control. Column pressure is best kept constant to preserve the composition profile on which the other controls depend. At most, pressure can float gradually on the overhead condenser to capture the benefits of minimized pressure or gracefully handle a cooling limitation. Also, pressure should normally override reboiler heat on high column pressure, with a setting typically 5–10 PSIG above the regulatory setpoint

and below any safety function setting. All of this is inherent in conventionally config-ured regulatory controls, including smooth response to saturated reflux or pressure con-trol valves. No MPC required.

While MPC remains a sound and often tantalizing technology in principle, its practical applicability and rate of success is not nearly what popular wisdom might have you believe. I would hazard a guess that only 10–20% of all MPCs are earn-ing money by doing something regulatory controls can’t do better, and that means a whole lot of unnecessary MPC activity is going on. The best thing many companies can do for their process control budget, especially in these lean times, is to prune whole MPCs, not individual models, and to re-allocate the liberated resources to DCS-level work, an area that has received altogether too much lip service throughout the MPC era.

Allan G. Kern, P. E.

Author’s responseMr. Kern has a valid point about the

balance between APC complexity, main-tainability and potential versus real bene-fits. The quest to simplify APC should also consider what can be done by advanced regulatory control. When the applica-tion dynamics and constraints are simple, advanced regulatory control can deliver benefits. It is important to remember, how-ever, that when an application has mul-tiple constraints and complex dynamics, implementing it in the DCS does not make it simple and maintainable. Simplify the problem definition first, and then choose the appropriate application platform.

Y. Zak Friedman

Hydrocarbon Processing welcomes and encourages feedback from its readers. Send your comments to:

Hydrocarbon ProcessingAttention: Letters to the editorP.O. Box 2608Houston, Texas [email protected]

To instrumentair distributionnetwork

PCV

PSVATM

ATM

AlarmVibration

monitoringsystem

Plant shutdown

Airreceiver

Airdryer

Air intakefilter

Trip

Trip

Blow offvalve

M

Local controlpanel (LCP)

Scrubber

Cooler

PT

PSLL

XE

XT

Load/unload

Compressor package diagram.FIG. 1

CorrectionThere were two mistakes on page 44 of the November 2009 article, “Avoid confusion when performing safety integrity levels.” The correct Fig. 1 is shown here. Also, the subheading “Methodology No. 1” should have referred to the information in Table 3. Hydrocarbon Processing regrets the errors.


HPI CONSTRUCTION BOXSCORE UPDATE Company Plant Site Project Capacity Est. Cost Status Licensor Engineering Constructor

27

UNITED STATESCalifornia BlueFire Ethanol Lancaster Biorefinery, Ethanol 3.7 MMgpy E 2010 BlueFire Ethanol Colorado ClearFuels Commerce City Biorefinery 20 tpd 37 E 2010 Rentech Florida INEOS Bio JV Vero Beach Biorefinery, Ethanol 8 Mgpy 100 F 2011 KBR Hawaii Ensyn Corp Kapolei Biorefinery None 32 F 2010 UOP|Ensyn Corp Illinois Haldor Topsøe Des Plaines Biorefinery 25 tpd 35 P 2011 Haldor Topsøe|ConocoPhillips Haldor Topsøe Louisiana BioEnergy LLC Lake Providence Biorefinery, Ethanol 110 Mgpy 139 U 2011 BioEnergy LLC Michigan American Process Inc Alpena Bio-ethanol 890 Mgpy 28 F 2011 Mississippi BlueFire Ethanol Fulton Biorefinery, Ethanol 19 MMgpy 311 E 2012 New Mexico Sapphire Energy Columbus Biorefinery 60 bpd 189 E 2012 Sapphire Energy Oregon ZeaChem Inc Boardman Biorefinery, Ethanol 250 Mgpy 73 E 2010 ZeaChem Inc Texas Algenol Biofuels Freeport Biorefinery, Ethanol 100 Mgpy 59 F 2011 Dow Chem

LATIN AMERICABrazil Petrobras\BG Group Santos LNG Floating (FLNG) 14 MMm3/d S Colombia Reficar Cartagena Refinery, Heavy Ends RE 85 Mbpd 1400 F

EUROPEGreece Hellenic Petroleum SA Elefsina Power Supply System RE None 26 E 2010 ABB

ASIA/PACIFICChina Henan Jinkai Chemical Group Henan Ammonia TO 2000 m-tpd U 2012 ACSA ACSA ACSA China Yanchang Petroleum Group Shaanxi Cracker, DCC BY 590 kty F 2013 Shaw SEIC China Xinjiang Yili Coal Chemical Xinjiang Ammonia TO 1000 m-tpd U 2012 ACSA ACSA ACSA Papua New Guinea InterOil Gulf Province Gas Stripping Unit None S 2012 Papua New Guinea Esso Highlands PNG LNG Kutubu Gas Treating None E 2014 CB&I|Clough Papua New Guinea InterOil/Petromin/Pacific LNG JV Napa Napa LNG Liquefaction Plant 8 MMtpy 7000 F 2015 Papua New Guinea InterOil/Petromin/Pacific LNG JV Napa Napa Storage Train, LNG (1) 4 MMtpy 7000 F 2015 Papua New Guinea InterOil/Petromin/Pacific LNG JV Napa Napa Storage Train, LNG (2) 4 MMtpy 7000 F 2015 Singapore Linde Gas Singapore Singapore CO2 Liquefaction Plant 100 tpd 30 C 2009 Linde Gas Singapore

MIDDLE EASTUnited Arab Emirates GASCO Abu Dhabi Compressor None 415 E 2013 Technip United Arab Emirates GASCO Abu Dhabi Utilities RE None 415 E 2013 Technip United Arab Emirates FERTIL Ruwais Ammonia 2 Mtpd 1200 E 2013 Uhde Samsung Eng United Arab Emirates Abu Dhabi Oil Refining Co (TAKREER) Ruwais Offsites None 2730 E 2013 Samsung Eng United Arab Emirates FERTIL Ruwais Urea 3.5 Mtpd 1200 E 2013 Uhde Samsung Eng United Arab Emirates Abu Dhabi Oil Refining Co (TAKREER) Ruwais Utilities None 2730 E 2013 Samsung Eng Yemen Total Balhaf LNG Liquefaction Plant 6.7 MMtpy 3200 C 2009

See http://www.HydrocarbonProcessing.com/bxsymbols for licensor, engineering and construction companies’ abbreviations,along with the complete update of the HPI Construction Boxscore.

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GAS PROCESSING DEVELOPMENTS SPECIALREPORT


Advanced mercury removal technologiesNew technologies can cost-effectively treat ‘wet’ and ‘dry’ natural gas while protecting cryogenic equipment

N. ECKERSLEY, UOP LLC, A Honeywell Company, Des Plaines, Illinois

M ercury is present in many of the world’s natural gas fields. Process plants with brazed aluminum heat exchangers, including liquefied natural gas (LNG) facilities and

nitrogen-rejection units, are particularly susceptible to corrosive attack by mercury. More awareness on the part of gas processors is necessary to assure better protection of their assets and to address environmental concerns by removing mercury. At present, mer-cury levels have increased from 30 μg/Nm3 or 40 μg/Nm3 to levels exceeding 1,000 μg/Nm3 in the Pacific Rim.

PROCESSING SOLUTIONSIn supplying purification solutions to the gas-processing indus-

try, a number of approaches for mercury removal have been devel-oped. Several process options using both regenerable and non-regenerable fixed-bed technologies are available. The protection of aluminum heat exchangers can be accomplished by using a layer of silver-containing molecular sieve inside the dehydration vessels. The active silver forms an amalgam with any mercury present, and its zeolitic substrate adsorbs moisture in the treated gas. This approach offers flexibility in being regenerable, as the mercury-containing gas is bypassed around any cryogenic equipment. If necessary, condensed mercury can be collected, and the mercury-entrained gas treated with a small non-regenerable guard bed.

Another approach uses non-regenerative metal sulfides to remove mercury from the raw gas upstream of the dryers and the amine unit. Utilizing larger vessels, this approach also protects the brazed-aluminum heat exchanger and ensures less mercury contamination in and around the process plant.

A comparison of mercury-removal processes will be described via several case histories that examine regenerative zeolitic and non-regenerable metal sulfide-based solutions. Plant-specific drivers for each approach will be discussed as well as the efficacy for each technology.

Contaminants of concern. Process systems designed to purify hydrocarbon feed streams are commonly used in the natu-ral gas (NG) industry and are becoming increasingly impor-tant. Historically, NG components such as sulfur, carbon dioxide (CO2) and water (H2O) have been effectively removed by using regenerable molecular sieves, non-regenerable fixed-bed absor-bents, membrane systems and amines.

Mercury is a naturally occurring element found in small but measurable concentrations in many oil and gas fields. This metal

is most frequently detected in its elemental form and is prevalent in NG processing and LNG facilities. Due to advances in detec-tion systems, mercury can now be accurately measured down to nanogram levels in the case of gases and to parts per billion (ppb) levels in liquid hydrocarbons.

Metal embrittlement issues. Mercury, when present, can cause severe and catastrophic corrosion of aluminum heat exchangers, which are commonly used in gas-plant cryogenic systems. Deposition of liquid elemental mercury in heat exchang-ers can compromise their structural integrity. One mechanism is referred to as liquid-metal embrittlement (LME). LME has been responsible for a number of failures of aluminum heat exchangers over the past 40 years. LME can cause crack initiation and propa-gation within such equipment, particularly in the proximity of a weld.1 Several examples of mercury causing equipment failure in gas processing facilities have been documented in North America, North Africa and, more recently, in Asia Pacific.2 Understanding the effects associated with LME is particularly important as it is difficult to detect prior to failure.

To avoid potential equipment failure, tight limits have been placed on allowable mercury levels in NG passing through alu-minum heat exchangers. The current typical level of mercury removal commonly required is 10 nanograms/Nm3 of NG passing to the cryogenic section of a processing plant. This specification can be achieved by using two types of mercury-removal technol-ogy, located immediately upstream of the cryogenic unit:

• Regenerable molecular sieve• Non-regenerable absorbent• Molecular sieve plus non-regenerable absorbent.

Mercury removal process options. These options meet the required mercury specifications and each offers operational advantages. The molecular sieve option relies on a portion of the dryer vessel containing a silver impregnated molecular sieve, which forms an amalgam with mercury. During the heating cycle of the drying vessel, the mercury is desorbed into a regeneration stream and bypassed around downstream cryogenic equipment.

Rather than removing mercury at a point immediately upstream of the cryogenic unit, some operators have opted to purify gas as it enters the plant. In this case, the heat-exchanger mercury specifica-tion can be met using a larger, fixed-bed mercury-removal absor-bent to treat raw gas as it enters the facility.

GAS PROCESSING DEVELOPMENTSSPECIALREPORT

30 I JANUARY 2010 HYDROCARBON PROCESSING

A recent variation in using either a silver-impregnated molecu-lar sieve or a non-regenerable absorbent now combines the two approaches. Installing a small vessel of non-regenerable absorbent to treat desorbed mercury from the molecular sieve unit perma-nently removes any mercury from the sales gas. Recognizing and understanding the drivers involved in the decision-making process when selecting the best available technology is the key and often varies markedly from plant to plant.

Analysis and typical global levels. Table 1 lists the results from a number of mercury surveys conducted over the years on a diverse range of product streams found in Asia-Pacific, Europe, North and South America, Middle East and Africa.

Analyzing the NG feeds. Mercury surveys were conducted using two different analysis systems:

• Cold vapor atomic fluorescence spectroscopy• Atomic absorption spectroscopy with Zeeman correction.The cold vapor atomic fluorescence spectroscopy is typically

used to measure mercury in gases and the atomic absorption spectroscopy has been used to measure mercury in both gaseous and liquid streams. Accurately measuring mercury in the field presents a complex challenge and requires a significant degree of analytical understanding, including not only sample analysis but also sample collection. Metallic sample collection containers should be avoided when considering liquid samples since mercury will readily plate out on metal surfaces. Sample line conditioning is crucial, since mobile mercury will accumulate on the inner wall pipe-work. The presence of different mercury species and other chemical interference can also impact the measurements.

Non-regenerable absorbent technology. In addition to forming amalgams with several metals, mercury is very mobile and will adsorb onto pipeline surfaces and other equipment com-monly found in gas processing plants. Mercury can then desorb back into gas streams, passing through contaminated pipelines, and prolonged periods can elapse between the installation of an upstream mercury removal unit (MRU) and the complete purg-ing of a pipeline.3

MRUs have been developed to take advantage of the affinity that the contaminant has with certain surfaces. Both metallic and carbon-based sorbents have been developed to remove mercury from a variety of hydrocarbon feeds. Collectively, these systems can be termed “non-regenerable” as opposed to regenerable molecular sieves. Non-regenerable sorbents contain sulfur, pres-ent as metal sulfide in the case of metallic systems and impreg-nated sulfur in the case of carbon. Potassium iodide promoted activated carbon has also been used but is much less common in NG processing.

Although sulfur-promoted activated carbon MRUs have pre-vailed in gas processing plants, these units have recently been superseded by metal-sulfide systems, for several reasons. Sulfur-promoted carbon is only effective in treating dry gas. The exten-sive micro-porous nature of activated carbon means that capillary condensation is a problem when operating at or close to the dew point of a gas.4

Sulfur-promoted carbon is also prone to sulfur dissolution when exposed to “wet” gas streams. This leaching of sulfur off the carbon leads to sulfur slip from the MRU, potentially damaging downstream equipment and reducing useful mercury capacity. The presence of water in the gas to be treated has been shown

to elongate the reaction zone (mass transfer zone) resulting in mercury slip over and above the required outlet specification. At the same time, more gas processors are requesting that mercury removal takes place either at the well head or close to the front of the gas plant, where the gas can be “wet.” The objective is to prevent mercury migration to various locations within a gas plant and to avoid any subsequent partitioning into processed NG and condensate streams.5

The handling of mercury-contaminated pipe-work, which is classified as hazardous waste must be considered in the context of existing occupational health guidelines. Although mercury has a high boiling point, it also has a relatively high vapor pressure. This combined with its inherent toxicity means that extreme caution is required when handling mercury contaminated pipe-work. The American Conference of Governmental Industrial Hygien-ists (ACGIH) has assigned mercury vapor a threshold limit value (TLV) of 0.025 mg/m3 of air as a time-weighted average (TWA) for a normal 8-hour workday and a 40-hour workweek.6 This TLV has itself halved since 1991, when the previous assigned level was 0.05 mg/m3.

When “up-front” mercury removal is required on raw gas, the challenge becomes one of how to treat NG that is not necessarily “bone-dry.” In cases where a carbon-based MRU is positioned on raw moist gas, the effective utilization of the carbon is compro-mised. Co-adsorption of moisture into the micro-porous carbon substrate proceeds, leading to a decline in mercury removal. The length of the mass transfer zone of an adsorbent is an indication of the rate of reaction the adsorbent has with the target contami-nant. As little as 3 wt% to 4 wt% water adsorbed onto the carbon MRU extends the mass transfer zone of the adsorbent by 12%.4 In addition, since sulfur (S) is soluble in liquid hydrocarbons, the presence of liquid hydrocarbon in natural gas leads to dissolution of sulfur from the carbon. This loss of active sulfur diminishes mercury (Hg) removal capacity of the activated carbon, thus shortening the service life of the bed. The reaction between Hg and S is stoichiometrically 1:1 according to:

Hg S HgS+ →

A 100% utilization of active S results in the removal of 1 mole of mercury for every mole of sulfur. Table 2 looks at the effects of entrained liquids on mercury adsorption capacity in an NG application using a sulfur-promoted activated carbon MRU. The achieved lifetime of the carbon MRU was half that of the estimated lifetime quoted by the supplier.

The degree of liquid adsorbed onto carbon during the life of the MRU is shown in terms of total wt% volatiles (200°C). Layer 1 represents carbon recovered from the inlet portion of the bed and layers 2, 3 and 4 represent subsequent layers. Clearly,

TABLE 1. Reported elemental mercury levels detected in natural gas

Region Mercury concentration / µg/Nm3

North Africa 1–100

North America 1–20

South America 1–105

Southeast Asia 10–2,000

Middle East 1–10

Europe 1–50

Source and survey from UOP




the carbon has co-adsorbed a significant quantity of liquid (20%–30%) from the raw NG causing its shortened service life. This is not surprising since activated carbon has long been used in hydrocarbon dew point control because it has a high affinity with C4+ in NG.

The total wt% of active sulfur was measured on each layer of discharged carbon. While sulfur levels on newly installed activated carbon are typically 10 wt% to 18 wt%, the levels on spent mate-rials were measured at 6 wt% to 9 wt%. To measure the mercury removal efficiency of supplied carbon, the percentage of utilized sulfur was also measured on a molar basis. The percentage of sulfur utilized in the equilibrium section of the vessel (layers 1, 2 and 3) was measured at approximately 4 wt%. By comparison, on a dry NG without the attendant issues of liquid entrainment, this percentage utilization would be expected to be >10 wt%. The data confirms that sulfided carbon is prone to sulfur dissolution and micro-pore blocking when treating wet gas.

Apart from the basic requirement to ensure that adequate mercury removal can be achieved on gases at or close to their dew points, from the point of capital expenditure, it is important to ensure that MRU reactor volumes are minimized where possible. This is particularly important when positioning an MRU offshore where spatial constraints are critical. The contact times required by sulfided-carbon products often lead to a larger than practical MRU footprint. The drive to reduce capital budgets and avoid large volumes of spent material has led to gas processors examin-ing technologies other than sulfided carbon.

After carbon is discharged from an MRU, it is usually sent to a specialized plant where mercury is reclaimed via vacuum distil-lation. There is no useful purpose for the remaining carbon and it undergoes high-temperature incineration.

A better solution. A range of non-regenerable absorbents has been developed to improve on existing MRU technologies. Gas streams contain-ing thousands of micrograms of mercury can be successfully treated using advanced new absorbents. Instead of carbon, transition metal oxides and sulfides are utilized. The active component of the advanced absor-bents is a metallic sulfide, and the products are supplied either in their oxide form and are sulfided in-situ by the gas to be treated or are supplied pre-sulfided.

After their useful life, the discharged absorbents can have the mercury removed via vacuum distillation and sold into specialist applications for re-use. Since the remaining active metal is compatible with metal recycling programs, it is sent for recovery via a smelting process and then sold back onto the open market. This process ensures that the MRU product is handled in an environmentally friendly way.7 The absor-bents have been developed to treat wet and dry gases, without the same wet-gas limitations of other non-regenerable products. Fig. 1 shows a commonly suggested flow-scheme location for the advanced absorbent. This process product range is successfully treating liquid hydrocarbon streams in addition to gaseous fluids. Sulfur is anchored to the metallic substrate, preventing subsequent dissolution and slippage onto downstream equipment.

Hg removal via regenerable molecular sieves. Remov-ing mercury using molecular sieve technology represents a novel and well-established approach in protecting cryogenic equip-ment. Using two different types of molecular sieve within the dehydration section of a gas plant, it is possible to ensure that the NG is dry and mercury-free prior to entering the cryogenic unit. Since the configuration and operating procedure of the dryers is unaffected by installing this two sieve system, ease of operation is assured. The silver-promoted molecular sieve, designed to remove mercury in addition to water, is capable of passing through thou-sands of regeneration cycles over the course of a long service life. Contaminant removal proceeds via temperature swing adsorption, with mercury forming a silver amalgam across the molecular sieve structure and then desorbing when hot gas is passed through the dehydration vessel. The mercury-containing regeneration gas is safely bypassed around the cryogenic unit.

Removing mercury using silver-promoted molecular sieve in existing dehydration vessels ensures that capital expenditure is

TABLE 2. Impact of liquids on mercury removal using activated carbon in the gas phase

Total Total S, Total Hg,Bed volatiles, wt% wt% Hg/S Hg/S Sulfurposition (200°C) wt% (dry basis) (dry basis) weight basis molar basis utilization %

Layer 1 21.1 7.02 1.89 0.27 0.0429 4.29

Layer 2 21.0 6.57 1.71 0.26 0.0414 4.14

Layer 3 26.8 8.32 2.12 0.25 0.0406 4.06

Layer 4 24.4 7.97 0.29 0.04 0.0057 0.57

Rawnatural gas

CO2 removalDryers

Feed-gasseparator

Non-regenerableabsorbent

Molecularsieves

A flow scheme for treating wet gas up-stream of process equipment using advanced absorbents.

FIG. 1

Rawnatural gas

CO2 removalDryers

Feed-gasseparator

Molecularsieves

Advancedadsorbent

A flow scheme for removal of mercury using regenerable silver-promoted molecular sieves.

FIG. 2

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reduced to a minimum without the need for an additional MRU. Due to smaller quantities of the silver-promoted molecular sieve adsorbent required, plants adopting this technology can load and re-load the adsorbent quickly without any associated increase in system pressure drop. Fig. 2 represents a typical flow scheme for the silver-promoted molecular sieve adsorbents. Spent and prop-erly regenerated adsorbent is mercury-free upon reactor discharge and since it passes the EPA Toxicity Characteristic Leaching Pro-cedure (TCLP) test, it is classified as non-hazardous waste for disposal purposes.8

To ensure the removal of mercury from sales gas and to protect plant cryogenic equipment, some gas plant operators have taken mercury removal with silver-promoted molecular sieves one step further. By installing a vessel of advanced non-regenerable mer-cury absorbent on the regeneration stream from the molecular sieve drying unit, mercury is effectively removed and captured. Fig. 3 represents a combined approach toward mercury removal using both advanced molecular sieve and absorbent technologies. Since the regeneration gas stream has a low flowrate (typically 10% of the inlet gas), the volume of the vessel containing the non-regenerable absorbent is small. This results in a cost-effective way of removing mercury, without the high capital expenditure associated with installing a larger absorbent vessel upstream.

Clearly, there are several ways to remove mercury from NG processing plants. Capital expenditure limitations, equipment protection requirements and environmental factors must all be considered. Both non-regenerable absorbents and molecular sieve technology can be used to handle a very broad range of mercury levels and process scenarios.

CASE STUDIESThese case studies illustrate factors involved when selecting

a mercury-removal system that is most applicable for a given processing situation:

Case 1: PTT Thailand. The PTT GSP-5 gas plant located at Map Ta Phut, Rayong, Thailand, was commissioned and started up in 2004. The onshore facility processes raw gas via a pipeline from offshore gas fields in the Gulf of Thailand. The raw gas entering GSP-5 is conditioned to remove CO2, H2O and Hg, and the total gas flow treated is 530 MMscfd. The MRU is designed to protect a natural gas liquids (NGLs) recovery plant, incorporating a cryogenic unit that includes a brazed aluminum heat exchanger.

The initial charge of mercury-removal adsorbent used from plant startup was sulfur impregnated activated carbon.

The gas plant MRU configuration consists of two parallel reactors, each designed to process 265 MMscfd of gas. The MRU is located upstream of the amine plant and the dryers, and is positioned to treat raw gas as it enters the facility. Historically, the gas entering the MRU contained some liquid hydrocarbon with a triethylene glycol carry-over component. The initial charge of activated carbon experienced a premature mercury breakthrough after two years in service. Table 3 provides a summary of the MRU process conditions. After the activated carbon was discharged from the reactors, the MRU was refilled with the non-regenerable advanced absorbent. Fig. 4 shows the new installation with the parallel flow reactors at GSP-5.

Since the change-over was commissioned, the plant has con-tinuously recorded effluent mercury levels below the required specification and maintained the start-of-run pressure drop, which was a priority for the customer. This successful performance has been achieved despite treating a liquid-entrained, water-saturated natural gas. Fig. 5 details the actual mercury influent and effluent levels at the GSP-5 facility in the first year following the startup of the new MRU. Despite fluctuating mercury inlet levels, the new absorbent continues to meet desired effluent specifications.

Case 2: Gasco Abu Dhabi. The original Adnoc (now Gasco) Habshan gas plant, located in Abu Dhabi, was built in 1983 to process Thamama gas from the nearby Bab and Asab fields. Following the completion of two major development projects (OGD-1 in 1996 and OGD-II in 2001), the plant now

TABLE 3. PTT GSP-5 MRU process conditions

Gas treated Natural gas

Gas flowrate, MMscfd 265

Operating pressure, Kg/cm2 48

Operating temperature, °C 18

Hg influent range, µg/Nm3 50–200

Hg effluent specification, µg/Nm3 < 0.01

Parallel fixed-bed reactors using advanced absorbents at the PTT GSP-5 gas plant, Map Ta Phut, Rayong, Thailand.

FIG. 4

Rawnatural gas

CO2 removalDryers

Feed-gasseparator

Molecularsieves

Advancedadsorbent

Non-regenerableabsorbent

A flow scheme for the combined removal of mercury utilizing both regenerable molecular sieves and non-regenerable absorbents.

FIG. 3



includes eight gas processing trains with the capacity to process 3.5 Bscfd of non-associated and associated gas. In addition to network gas, the Habshan facility produces NGLs, condensate and liquid sulfur.

The OGD-1 expansion raised output at Habshan from 450 MMscfd to 1,865 MMscfd. Three new trains were developed: two 350-MMscfd trains for the treatment of non-associated and associated gas (T1 and T2) and one 625-MMscfd train for the treatment of non-associated gas (T3). In addition, condensate recovery was raised from 5,000 bpd to 131,000 bpd. Raw gas entering OGD-1 is currently conditioned to remove CO2, hydro-gen sulfide (H2S), H2O and Hg.

From plant startup in 1996, the OGD-1 gas processing trains have used molecular sieve adsorbents. In 1998 following a study effort together with Gasco, a layer of silver-promoted molecular sieve adsorbent was incorporated into each drying vessel as a retro-fit solution to ensure that the gas passing to downstream cryogenic equipment was mercury free. The combination of dehydration-grade molecular sieves and advanced silver-promoted molecular sieve adsorbent products has demonstrated excellent operating performance in each of the three OGD-1 trains. Each train has successfully used silver-promoted molecular sieve adsorbent in up to six-year lifetime cycles, to reduce a design inlet mercury level of 200 ng/Nm3–250 ng/Nm3 down to a cold box specification of < 10 ng/Nm3.

Case 3: Enterprise US. The Enterprise Meeker I gas plant, located in Colorado’s Piceance Basin, started up in 2007 with an initial gas processing capacity of 750 MMscfd, incorporating 35,000 bpd of NGLs. A Phase II expansion in the form of sister plant, Meeker II, started up in 2008 and doubled processing to 1.5 Bscfd of gas and 70,000 bpd of produced NGLs.

Both Meeker I and Meeker II condition raw gas to remove CO2 using amines and remove water and mercury using molecu-lar sieve technology. Dehydration-grade molecular sieves and silver-promoted molecular sieves are uitilized in the drying vessels to remove water and mercury from the raw gas prior to the treated gas passing to the cryogenic system. In addition, an advanced absorbent is used to remove mercury from the molecular-sieve regeneration stream. The molecular sieve dryers are configured such that two vessels are in adsorption mode and one vessel is in

regeneration mode at any given time. Each molecular sieve vessel processes 375 MMscfd of feed gas. Table 4 provides a summary of the mercury removal process conditions for the combination system at Enterprise Meeker I and II.

Summary. If mercury is allowed to reside in an NG plant un-checked, it can cause severe damage to process equipment and potentially compromise the health and safety of plant operators. Two distinctive technologies have been developed to remove mer-cury from various locations within a gas plant. Each technology affords maximum mercury removal and protection and includes within it a number of non-regenerable and regenerable fixed-bed solutions. The well-established silver-impregnated molecular-sieve technology ensures that the cryogenic component of a gas plant is protected against potential mercury ingress. Applying such systems can provide cost-effective (lower capital cost) options with longer service life. The latest non-regenerable products offer the option to remove mercury from raw gas as it enters the plant. Alterna-tively, desorbed mercury can be removed from the molecular sieve regeneration gas using a small cost-effective fixed bed. HP

ACKNOWLEDGMENTThe author acknowledges the cooperation of PTT, Gasco and Enterprise in

the writing of this article.

LITERATURE CITED 1 Willhelm, M. S., “Risk analysis for Operation of Aluminium Heat Exchangers

Contaminated by Mercury,” Annual AICHE Conference, April 2008, New Orleans.

2 Lund, D.L., “Causes and remedies for mercury exposure to aluminum cold-boxes,” 75th Annual GPA Convention, March 11–13, 1996, Denver.

3 AIChE Paper Jointly authored by UOP and Equistar, “Mercury removal from cracked gas a liquid streams,” Ethylene producers conference, April 2004.

4 Biscan, D. A., R. S. Gebhard, T. M., Matviya, “Impact of process condi-tions on mercury removal from natural gas using activated carbon,” 8th International Conference on Liquefied Natural Gas, 1986.

5 Edmonds, B., R. A. S. Moorwood and R. Szcepanski, “Mercury partioning In natural gases and condensates,”GPA European Chapter Meeting, London, March 1996.

6 2009 TLVs and BEIs – ACGIH. 7 Private correspondence with Begemann Milieutechniek B.V. Mercury waste

reclaimers. 8 Corvini, Stiltner, Clark, “Mercury removal from natural gas and liquid

streams.”

TABLE 4. Enterprise Meeker I and II

Gas treated Natural gas

Gas flowrate to mol sieve vessels, MMscfd 750

Absorbent operating temperature, °C 30–40

Absorbent operating pressure, kg/cm2 70

Raw gas Hg concentration to HgSIV 1, ng/Nm3 Up to 800

Regeneration gas Hg concentration to absorbent, ng/Nm3 Up to 2,000

Effluent Hg concentration from absorbent, ng/Nm3 < 10

0102030405060708090

100110120130140150

0 1 2 3 4 5 6 7 8 9 1 01 11 2Months online

Mer

cury

con

cent

ratio

n, μ

g/Nm

3

MRU inletMRU outlet

Mercury influent and effluent levels at the PTT GSP-5 gas plant with the new advanced absorbent system.

FIG. 5

Neil Eckersley is the UOP business manager for Aluminas and Specialties respon-sible for its complete portfolio of alumina-based solutions including mercury and sulfur removal products. He graduated from Sheffield Hallam University in the United Kingdom with a BS degree in chemistry and has worked in the areas of Research, Technical Service, Sales and Product Management.

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A unique natural gas processingsuccess storyCost-effective expansion created high reliability operations

C. BAKER, Anadarko Pinnacle Gas Treating, Inc., East Central Texas;T. BARNETTE, Merichem Chemicals and Refinery Services LLC, Schaumburg, Illinois

F or the past decade Anadarko Petroleum has been operating two liquid redox processing H2S removal systems. They managed to maintain extremely high removal efficiencies along with

keeping the highest online time record in the area. For this reason, Pinnacle Gas Treating is bringing on more natural gas wells in the area and needs to expand the H2S removal capacity of their facility. The ultimate goal of their expansion will require the removal of up to 40 long tons per day (LTPD) of sulfur from the amine acid gas, while maintaining their high turndown capacity that has consistently given them their reputation for reliability. A modular approach of adding multiple expansion gas processing systems in stages, as needed, met their requirements in the most cost-effective way.

Background. In 1996, Western Gas Resources selected a liquid redox process to treat the amine acid gas generated in their new Pinnacle Gas processing plant located in Tennessee Colony, Texas. Initially, Western Gas purchased a 2-LTPD liquid redox-based sul-fur recovery unit (SRU), that started up in June 1997. However, shortly into designing the first unit, it became apparent that the unit’s sulfur capacity would be exceeded. Consequently, Western Gas purchased a 7-LTPD unit and it started up in November 1997. In 2001, the facility was purchased by Anadarko Petroleum, which currently operates the facility.

The 7-LTPD SRU was originally designed to treat amine acid gas at the processing conditions itemized in Table 1. As indicated, the SRU was designed to remove 99.99+% of the H2S under severe turndown conditions of 155:1 for the gas flow and 45:1 for the H2S concentration.

Additionally, while the unit was designed to handle a wide range of flow and H2S concentrations totaling the design to 7 LTPD of sulfur, it would also be required to maintain operation with a sulfur load turndown that could go from nearly nothing (100 lb/day) up to the design capacity within a short time.

Because the increase in the sulfur removal requirement at the gas plant was expected to continue to rise, and plans were begun to add a 40-LTPD Claus plant to the SRU capacity at the facil-ity. The goal was to use the liquid redox process up to 7 LTPD removal and then use the Claus system above that, with the liquid redox process acting as the tail-gas treater to achieve the high removal efficiency required. Since flexibility was key, the operating plan for the facility is illustrated in Table 2.

Let the expansion begin. From 1997 until 2000, the gas processing systems were operated exclusively for H2S removal. In 2000, the Claus system was completed, consisting of:

• Acid gas enrichment (AGE) to concentrate the 2–3% H2S amine acid gas to 25% for minimum Claus feed concentration

• 40-LTPD Claus SRU• Tail-gas hydrotreatment to convert all sulfur species to

H2S• Cooling• Tail-gas feed to the existing 7-LTPD liquid redox process

unit as a tail-gas treater.As this system was operated, several operational difficulties

were experienced, specifically with the hydrotreater system and the Claus plant. The Claus plant operational difficulties were related to the previously mentioned load swings, which the Claus could not tolerate. After a year of difficult operation, Anadarko decided to stop operation of the AGE/Claus/hydrotreater train and to begin using the liquid redox processing systems exclusively for the SRU. This was a problem, as it severely limited the com-pany’s ability to further expand processing natural gas, as it was now limited to a 7-LTPD sulfur throughput.

And stop. From 2001 to 2005, operation focused on optimiz-ing the existing liquid redox processing operations and mainte-nance to maximize online time and capacity. In 2005, however, Anadarko began discussions with area gas producers, which would potentially push the SRU requirements at Pinnacle beyond the

TABLE 1. Processing conditions for treating amine gas

Case 1 Case 2

Type of gas Amine acid gas Amine acid gas

Flowrate, MMscfd dry 9.3 0.06

% H2S in acid gas 2.0 90.0

Removal efficiency 99.99+% 99.99+%

Outlet H2S, lb/hr < 2 < 2

LTPD sulfur 7 7

TABLE 2. Operating plan for the facility

Sulfur load Operation

< 2 LTPD 2 LTPD liquid redox processing unit

2-LTPD – 7-LTPD 7 LTPD liquid redox processing unit

> 7 LTPD Claus plant, with AGE/ hydrolysis/gas processing TGU



capacity of the existing liquid redox processing units. Over the next year, expansion requirements expanded from 10 LTPD, to 15 LTPD, finally settling on 40-LTPD of total SRU capacity. Several options were considered and dropped as the total sulfur load increased, including, shortly, revamping and restarting the Claus system (which was made unfeasible as the AGE unit had been dismantled and moved). In 2007, two options remained:

• Adding additional liquid redox gas processing system(s)• Direct oxidation with existing liquid redox process modified

and run as TGCU tail-gas clean-up unit (TGCU)A lean feed acid gas process was initially considered for the DO

portion, as the sour acid gas would still normally have low H2S concentrations (2–4 vol%). Further investigation of potential oper-ating conditions showed that H2S levels could attain 8% for long periods and periodically see levels as high as 16%. The lean acid gas process could not tolerate these excursions and was pulled from consideration. Pinnacle’s excellent operating experience and online time with the liquid redox processing system and ease at which the unit was operated with the highly variable sulfur load made them very receptive to adding modular trains of larger liquid redox processing systems. These systems are operating parallel to their existing 7-LTPD unit, which is how the system is proceeding.

With a total sulfur capacity of 40-LTPD still planned, of which the 7-LTPD would be considered part, 3 x 11 LTPD expan-sion trains were planned, with the first 11-LTPD system ordered in September 2007. This expansion will meet the plant’s needs

through new producers being brought online in June 2008, with the liquid redox processing expansion planned to be operational by that time. Future addition of gas producers tied to the Pinnacle plant will require additional acid gas treatment capacity, with a second 11-LTPD liquid redox processing expansion plant planned for the future.

The liquid redox process. A single train flow, diagramming the liquid redox process, is illustrated in Fig. 1.

The acid gas from the amine unit is passed through a knock-out pot to remove any condensable liquids and/or amine car-ryover. The acid gas then enters the proprietary autocirculation liquid redox processing unit. In the autocirculation liquid redox unit, the sour gas is sparged through a proprietary solution of diluted chelated iron within the vessel’s absorber sections. Within the absorbers, H2S is absorbed (reaction A) and converted to elemental sulfur (reaction B) as follows:

H2S (gas)+ H2O H++ HS + H2O (A)

HS + 2Fe+++ H++ SO + 2Fe++ (B)

The reduced iron solution then flows into the vessel’s oxidizer sections where air is sparged through the solution to reoxidize the chelated iron back to the ferric state (Fe+++) in accordance to reaction C.

1

2 O2 + H2O + 2Fe++ 2OH + 2Fe+++ (C)

Through a unique arrangement of weirs and baffles within the proprietary autocirculation vessel, liquid circulation between the absorber and oxidizer sections is maintained through a series of airlifts, thus circulation pumps are not required. The air and the sweetened acid gas streams are combined in the headspace of the autocirculation vessel and directed to either an incinerator or directly to the atmosphere.

The solid elemental sulfur, which is formed in the process, is removed by directing a slipstream of solution to a settler vessel where the slurry concentration is increased to approximately 10 wt%. The slurry is then pumped to a vacuum belt filter where the sulfur is dewatered into a 60% dry cake.

Conclusion. Anadarko’s decision to continue to employ the liquid redox process as its primary sulfur recovery unit proved to be not only an economical approach, but also a technical success, even at sulfur loads that normally would be associated with a Claus system. The liquid redox processing unit allowed them to achieve removal efficiencies of greater than 99.9% while achieving nearly 100% turndown. This wasn’t only on their sulfur recovery, but also on their gas flow, achieving > 99% online availability, making their facility the most reliable in the area (Fig. 2). HP

Tony Barnette is the technology manager for Merichem Chemicals and Refinery Services LLC Gas Technology Products in Schaumburg, Illinois. Mr. Barnette has been employed at MCRS Gas Technology Products for over 20 years, during which he has held roles as sales engineer, pilot plant engineer, project manager,

applications engineer, senior applications engineer and applications manager before his current position. His primary focus is desulfurization systems. Mr. Barnette received a BS degree in chemical engineering from the South Dakota School of Mines and Technology.

Sour gas

Filter andsilencer

Sulfursettler

Settler feed pump

Vent gasAir blower

To sulfurseparation

optionAutocirculation(absorber/oxidizer)

Knock-outpot

A single train flow diagram.FIG. 1

7 LTPD liquid redox plant, Pinnacle Gas plant.FIG. 2



Equilibrium considerationsin choosing a gas treating aminePursue these guidelines to understand solubility

S. A. BEDELL, The Dow Chemical Company, Freeport, Texas

S olvents have been used for decades to remove acid gases from a variety of gas streams.1,2 The simplest type of solvent is referred to as a physical solvent, usually a pure organic

compound that dissolves acid gases through nonreactive interac-tions. The more commonly used solvent systems are aqueous amine solutions that are called chemical solvents. In addition to processing a certain degree of physical solubility, chemical solvents (amines, in particular) can also react to form thermally regenerable salts with acid gases.

Alkylamines are the simplest type of amine. An alkanolamine is a particular type of amine that contains hydroxyethyl or hydroxy-propyl groups in place of some or all alkyl groups. The introduc-tion of hydroxyalkyl groups is considered to be an improvement relative to an alkyl group since they increase the water solubility, reduce the amine volatility and reduce hydrocarbon solubility. However, hydroxyalkyl groups also reduce the amine’s basicity (relative to an alkyl groups) which may not be an advantage from an equilibrium viewpoint.

Equilibrium limitations. At the heart of any understand-ing of amine treatments are equilibrium limitations of the reac-tion between dissolved acid gas and the amine. The acid-base interactions of the amine (Am) and the conjugate base of the aqueous acid gas species, X–, are represented by the following protonation equilibria:

X + H+ HX K1 = [HX]/[H+ ][X ] (1)

Am + H+ AmH+ K2 = [AmH+ ] / [H+ ][Am] (2)

The equilibrium constant for the solution reaction of the amine and the dissolved acid gas can be represented by:

Keq = K2 / K1 (3)

The following discussion is based only on the amine’s solution properties and those of the dissolved acid gas. Gas phase concen-tration differences (both inlet and desired outlet specification) coupled with physical solubility differences of solvent/solute com-binations will also play a role in solvent performance to determine the actual equilibrium position. Such an analysis can be used to calculate equilibrium partial pressures of acid gases over amine solutions of various acid gas loadings.

Fig. 1 shows the protonation constants for two typical gas treating amines, mono-ethanol amine (MEA) and methyl dietha-nolamine (MDEA), along with several acid gases. Protonation

constants shown are for the species formed by acid gas dissolu-tion in water. A larger protonation constant value represents a molecule’s higher affinity for the proton. Thus, the acid molecules shown at the bottom of the figure are more likely to give up their protons to the amines above them. The temperature range represents absorber conditions on the left and common stripper conditions on the right. Fig. 1 can be used to illustrate several aspects of amine acid gas interactions. Acid and base protonation constants are from a National Institute of Standards and Technol-ogy (NIST) database.3 Values of protonation heats were used to calculate constants by using the van’t Hoff equation:

ln(KT 2/KT1) = H/R(1/T1 1/T2 ) (4)

Example 1. The reaction of MDEA with CO2 shows a difference in log K values of two at 40°C. Thus, the equilibrium constant for the reaction of MDEA and CO2 under absorber conditions is about 102 or 100. Under stripper conditions, the same equilibrium constant drops to 10. This equilibrium constant reduction, com-bined with a reduction of CO2 partial pressure by the steam strip-ping gas, facilitates the release of CO2 from solution. The line for H2S is similar to CO2 which explains the use of MDEA for both acid gases. This analysis takes into account only the equilibrium

0

2

4

6

8

10

12

14

40 60 80 100 120Temperature, °C

Log

K pr

oton

atio

n

OH-

CH3 SH

SO2

MDEAH2S

CO2

MEA

Comparative protonation equilibria used to assist gas treating amine selection.

FIG. 1



limitations of the reactions: kinetic limitations for the reaction of CO2 with water can be used to selectively remove H2S.

Example 2. The protonation equilibrium line for methyl mer-captan (CH3SH) is above MDEA. This means that the equi-librium constant for their reaction at 40°C is only 10–2, which explains why most alkanolamine systems are severely limited with respect to mercaptan removal. Notice, that the use of caustic solutions (OH–) provides a large enough equilibrium constant (>103) for efficient removal, but is not regenerable due to the large constant (>102) at regenerator conditions. Though MEA is a stronger base than MDEA, its protonation equilibrium line is substantially below CH3SH.

Example 3. Fig. 1 predicts that the reaction equilibrium con-stant for MDEA with SO2 under absorber conditions is about 106, certainly much larger than that for H2S or CO2. Unfortu-nately, the equilibrium constant under stripper conditions is also very large—more than 104—too large to effectively strip the SO2. This is typical for acids that are much stronger than H2S or CO2 and the salts that they form with amines such as MDEA, MEA and DEA are not regenerable under standard stripper configura-tions. These salts are referred to as heat stable amine salts and will reduce the capacity of the amine solution unless other methods (vacuum distillation, electrodialysis or ion-exchange) are used to regenerate the amine.

Example 4. Example 3 showed how the reaction of SO2 with MDEA is essentially irreversible in a typical gas-treating plant. Fig. 1 can be used to “design” an amine that could be used for reversible SO2 scrubbing. Taking the reaction of MDEA with H2S or CO2 as a basis, one needs to find an amine of reduced basicity such that its line in Fig. 1 would lie the same distance above the SO2 line. This is essentially what has been done in the develop-ment of SO2 removal processes.1

The previous examples show only a consideration of equi-librium constants. Actual amounts of neutralized acid gas will depend on inlet or outlet gas concentrations.

Nonprotonation Equilibria. Total acid gas solubility can be partitioned into physical and chemical with chemical solubility

depending on acid-base equilibrium properties as well as the physical solubility. Thus, physical solubility in aqueous amine solutions acts as a bottleneck in the overall acid gas capacity for a given solvent. Fig. 2 illustrates the relative solubility of nitrous oxide (N2O) in three amine solutions with the same water con-centration. N2O is often used as a nonreactive gas to determine relative physical solubilities of CO2 in aqueous amine solutions. Fig. 2 shows that:

1. N2O solubility drops by 10%–20% (at zero CO2 loading) by replacing 30% of the water with amine. This should be expected with CO2 and perhaps H2S, but it has been noted that physical sol-ubility of methyl mercaptan increases as water content is decreased in alkanolamine solutions.4 This is likely due to a higher affinity between the more hydrophobic mercaptan and amine.

2. Physical solubility drops substantially as the acid gas load-ing increases due to a salting-out effect. Though it appears that the salting-out effect is less substantial for 30% DEA, data from that same source at 20% amine concentration show a different relative performance of these amines.

Thus far, the equilibria involved between CO2 and a primary or secondary amine to form carbamates have not been mentioned. While Fig. 1 may be a good representation of MDEA reactions with acid gases and MEA reactions with H2S and SO2, the ability of MEA to form carbamates with CO2 adds a degree of complexity that is discussed in other literature.6 An increase in amine basicity(Kprotonation) results in both a higher degree of carbamate forma-tion and faster reaction kinetics with CO2.

Although Example 2 demonstrates why mercaptan removal with amines is severely limited, other more favorable equilibria may be used to increase mercaptan removal by amine solutions. The most common method is to find a co-solvent with high physical solubility—such mixtures of water, amine and a physi-cal solvent are called hybrid solvents. Other solution reaction equilibria have been shown to provide favorable absorption/desorption characteristics, including first-generation mercaptan removal additives (MRAs) such as cyclodextrins.7 Figs. 3 and 4 show the effect of �-cyclodextrin on mercaptan vapor liquid equilibrium in water. Not only is there an increase in the solubil-

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5Moles CO2/mole amine

Rela

tive

N 2O

solu

bilit

y

30% MEA30% DEA30% MDEA

Solubility of N2O in aqueous amines solution compared to water.5

FIG. 2

0

50

100

150

200

250

300

350

400

450

500

0.00 0.040.02 0.06 0.08 0.10mmoles RSH/L

ppm

RSH

in v

apor

MeSHEtSHnPrSHnBuSH

VLE plot for mercaptans in water at 40°C.FIG. 3

GAS PROCESSING DEVELOPMENTS

ity of all mercaptans but the cyclodextrin cavity size is best suited for a larger mercaptan such as butyl (butanethiol). Normally, a combination of low aqueous solubility and reduced acidity makes it more difficult to remove higher mercaptans with aqueous scrub-bing. Further refinements in MRA chemistry have led to a second generation that shows a much higher affinity for mercaptans in alkanolamine solutions.8

These discussions of acid gas solubility and amine equilibria are intended only as a guide to better understand the under-lying principles of acid gas treating with amines. Many other considerations—including reaction kinetics, energy requirements, corrosion and degradation—enter into the selection of a proper amine system for acid gas removal. Also, in practice blends of amines are often chosen to optimize operability for particular applications. HP

LITERATURE CITED1 Kohl, A. and R. Nielsen, Gas Purification, Fifth Edition, Gulf Publishing

Company, Houston, 1997.2 Astarita, G., D. W. Savage and A. Bisio, Gas Treating with Chemical Solvents,

John Wiley, New York, 1983.3 Martell, A. E., R. M. Smith and R. J. Motekaitis, NIST Critically Selected

Stability Constants of Metal Complexes Database, NIST Standard Reference Database 46, Version 7, US Department of Commerce, 2003.

4 Bedell, S. A. and M. Miller, Industrial and Engineering Chemistry Research, p. 46, 2007.

5 Browning, G. J. and R. H. Weiland, Journal of Chemical and Engineering Data, p. 39, 1994.

6 da Silva, E. F. and H. F. Svendsen, International Journal of Greenhouse Gas Control, p. 151, 2007.

7 Bedell, S. A., “Improved control of organic sulfur,” 12th Annual Green Chemical Engineering Conference., Washington, DC, 2008.

8 Bedell, S. A., L. L. Pirtle and J. M. Griffin, “Improve mercaptan solubility in amine units,” Hydrocarbon Processing, January 2007.

MeSHEtSHnPrSHnBuSH

0

50

100

150

200

250

300

350

400

450

500

mmoles RSH/L

ppm

RSH

in v

apor

0.00 0.02 0.04 0.06 0.08 0.10

With 10% CD

VLE plot for mercaptans in 10% aqueous �-cyclodextrin at 40°C.

FIG. 4

Steve Bedell is a research scientist and senior technical person for Dow Oil & Gas, working across multiple technologies in the refining and processing market segment. Dr. Bedell received a BS degree in chemistry from West Virginia University and a PhD in chemistry from Texas A&M University. He holds 19 US patents and

is the author of over 50 external publications and presentations, most of which deal with acid gas removal processes.

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Designing a selectiveMDEA tail-gas treating unitFollowing these protocols will enhance sulfur recovery efficiency

S. NAGPAL, Fluor, Gurgaon, India

S elective amine-based Claus sulfur recovery units (SRUs)–tail-gas treating units (TGTUs) have become the preferred option for enhancing sulfur recovery efficiency to above

99.8% while minimizing sulfur emissions. The most commonly used selective amine is a generic methyl diethanol amine (MDEA). The most commonly known process is the SCOT process. Over 400 such plants have been built and many others are under con-struction that are using the SCOT process.

The TGTU process represents an extreme operating scenario for an amine gas-sweetening unit. While the TGTU process con-figuration is similar to a typical amine absorption-regeneration system, both the absorber and regenerator operate at extreme conditions. H2S and CO2 absorption occurs at low pressure just above atmospheric (typically 1 bara to 1.2 bara). Amine regen-eration to very low lean amine H2S-loadings is required, leading to operation with a high steam requirement.* TGTUs preferably employ a selective amine solvent to minimize CO2 co-absorption and recycle it to the SRU.

The SRU converts acid-gas feed into elemental sulfur and produces a tail-gas containing unconverted sulfur species. This gas is hydrogenated to reduce all unconverted sulfur species to H2S in a fixed-bed catalytic reactor, quench cooled with water and fed to the TGTU absorber. The product from the TGTU is off-gas that is sent to the incinerator while an acid-gas from the TGTU regenerator is recycled to the Claus SRU furnace. Fig. 1 shows a schematic of the SRU-TGTU process.

This article discusses some key issues that engineers need to address when designing these units. There are several pub-lished articles that present quali-tative effects of TGTU operating parameters. This article gives a more quantitative description that can be used as a preliminary design guideline, using several commercial process simulators. Variation among different simu-lators will be highlighted.

Selective H2S removal. MDEA is a tertiary amine that

does not react directly with CO2 to form carbamate. The tri-molecular reaction of MDEA with CO2 (Eq. 1), is slow, while the MDEA-H2S reaction (Eq. 2) is a fast proton transfer reaction that can be considered to be almost instantaneous.

R'R2N + CO2 + H2O R'R 2NH++ HCO3 (1)

R'R2N + H2S R'R2N++ HS (2)

This results in the kinetic selectivity shown by MDEA toward H2S absorption over CO2 absorption. However, maximum equi-librium loadings achievable for both H2S and CO2 are ~1 mole per mole of MDEA, provided that an adequate pressure-driving force is available in the gas phase and adequate contacting time is provided. Thus, selective H2S removal results are entirely due to the choice of gas-liquid contacting time being long enough for H2S removal but too short for equivalent CO2 capture.

Optimum design for an amine contactor is required to allow necessary H2S removal but minimal CO2 co-absorption. Equip-ment over-sizing is not advisable as it leads to excessive CO2 absorption and recycle to the Claus SRU.

Accurate computer models that consider inter-phase mass-trans-fer with simultaneous chemical reactions are required to simulate the adsorption/stripping process for optimal design and retrofitting of selective gas sweetening units. Use of equilibrium stage models with user-experience-based H2S and CO2 stage efficiencies, is a common approach for designing gas-sweetening units. However, this approach is not suitable for selective removal applications

where tray performance is highly variable and can be sensitive to factors such as tray type/design, solvent loading, column tempera-ture profile, etc. Also, tray effi-ciency estimation is difficult.

Process simulation. The performance of selective amine sweetening process simulators depends on two key model com-ponents: Vapor-liquid equilib-rium (VLE) and rate models.

Both H2S and CO2 absorp-tion in the amine solution are reversible reactions. As men-tioned above, the H2S-amine

ClausfurnaceAir

Acidgas Converters,

reheaters andcondensers

Tail gas Hydrogenation

and quenchTGTU

absorber

TGTUregenerator

Richamine

Off-gas(to incineration)

Leanamine

Acid gas (recycle to SRU furnace)

Sulfur

Sulfur recovery unit Tail-gas treating unit

Schematic of a sulfur recovery unit with a tail-gas treating unit.

FIG. 1* Loading is defi ned as mole H2S or CO2 per mole amine in aqueous phase.



reaction is extremely fast, and the process operates close to vapor-liquid equilibrium with respect to H2S absorption/regeneration. On the other hand, the CO2-amine reactions for tertiary amines, such as MDEA, are slow in the absence of the much faster car-bamate formation reaction that occurs for primary and secondary amines.** Thus, accurate rate models are required to determine the extent of CO2 removal while meeting H2S specification in the off-gas for incineration.

VLE model. VLE models, comprising a gas phase equation-of-state (EOS) model and a liquid phase activity coefficient model are used to correlate experimental VLE data for the H2O-amine-H2S-CO2 system over a range of amine concentrations, H2S and CO2 loadings, and temperatures.

Fig. 2 compares VLE calculated with several simulators, with the VLE data for 50 wt% MDEA at 40°C and 120°C.1 Simulators 1, 2 and 3 are seen to fit the data quite well.1 Recent VLE data for this system reports significantly higher H2S partial pressures as a function of amine loading.2,3 Fig. 2 illustrates that Simulator 4 based VLE calculations for 50 wt% MDEA at 40°C matches the later data.

At 120°C (regenerator condition), Simulators 1, 2 and 3 fit the data fairly well.1 At 120°C, the lowest loading data reported was at 0.0095m/m.1 Extrapolation of the VLE data to lower H2S load-ings down to 0.001–0.005m/m is required, as TGTU regenerators are required to produce lean amine of this quality. Extrapolation of VLE models into this low loading region with scanty data adds to model prediction uncertainty.

The above VLE model comparison indicates that the process simulator choice will have a significant impact on the design cal-culations as the simulators use different VLE models and even use different VLE databases for the VLE model parameter tuning.

Rate model. The rate model (also called the non-equilibrium stage model) is used to calculate the approach to equilibrium on

each tray/packing section. With rate models, stage equations are the traditional equations of mass and energy balances for each stage, the vapor and liquid phases are now characterized by a bulk composition and an interfacial composition. These models typically assume that the bulk vapor and liquid phases are well-mixed and the resistances to mass-transfer are located in the two films at the vapor-liquid interface. Linear concentration profiles are assumed in the two films. Mass-transfer correlations are used to incorporate effects of system hydrodynamics. The vapor and liquid mass-transfer coefficients are estimated using appropriate correlations for the type of tray being simulated. Diffusivities in the multi-component vapor and liquid mixtures—along with other transport properties, such as density, viscosity, thermal conductivity—are required to calculate the mass-transfer coef-ficients. Heat-transfer coefficients are commonly estimated using the Chilton-Colburn analogy.

Rate model use requires the user to provide details of tray type, column diameter, weir height, down-comer width, number of passes, etc. These models report calculated tray efficiency for H2S and CO2. The rate model accuracy determines how well H2S selectivity or CO2 slip is estimated.***

Selective absorption at low pressure. There are several challenges in the design of low-pressure tail-gas treating (TGT) absorbers. A typical case is used to illustrate these issues. The feed gas and lean amine to the absorber for this case are specified in Table 1.

1. Attainment of H2S specification in treated gas. The overall sulfur recovery of the SRU-TGTU process is depen-dent on the TGT absorber off-gas H2S concentration. Attainment of sulfur recoveries in excess of 99.9% requires the off-gas H2S spec to be 150 ppmv or less. (Note that a generic amine will be able to achieve a 250 ppmv H2S spec, a selective amine ~150 ppmv and a formulated amine ~10 ppmv.) Attaining this H2S spec in absorbers operating close to ambient pressure (1 to 1.2 bara) requires lean amine with very low H2S loading.

Fig. 3 shows the off-gas H2S concentration variation with H2S lean amine loading at a column top temperature of 40°C, esti-mated with various process simulators. Fig. 3 also illustrates the equilibrium H2S concentrations based on VLE data for 50 wt% MDEA at 40°C.1,2 Note that the VLE data-based equilibrium H2S concentrations represent the lower limit of off-gas H2S con-centration achievable.

Off-gas H2S concentrations in the range 60–150 ppmv are obtained for a lean amine with 0.005 H2S loading. Simulators 1,

TABLE 1. Case study—50 wt% MDEA absorber

Feed gas Lean amine

Flow, kmol/h 1,062 Flow, kmol/h 2,819 (88 TPH)

Temperature, °C 43.3 Temperature, °C 40

Pressure, bara 1.09 H2S loading, m/m 0.005

CO2, mol% 5.2 CO2 loading, m/m 0.0001

H2S, mol% 1.7

Column Treated-gas spec

Diameter, m 2.1 H2S, ppmv 100

No. of Trays (Valve) 14

0.001

0.01

0.1

1

10

100

1,000

10,000

0.001 0.01 0.1 1H2S loading, m/m

H 2S

pres

sure

, kPa

Jou data 120°CSimulator 1Simulator 2Simulator 3Jou data 40°C

Simulator 3

Simulator 1Simulator 2

Rogers data 40°CSimulator 4

Simulator estimation of H2S VLE in 50 wt% MDEA.FIG. 2

** Carbamate formation for secondary amine: R2NH + CO2 = R2NCOO– + H+

*** CO2 slip (%) = 100 x moles of CO2 in off-gas/moles of CO2 in absorber feed.

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2 and 3, although all based on VLE data,1 reported significantly different results, essentially from different rate models. Simulator 4, which is based on the VLE data2 reported, gives higher off-gas H2S concentrations than all the other simulators at H2S lean loadings above 0.004–0.005. Comparing Simulator 4 results with the equilibrium limit of H2S concentrations suggests that it is essentially an equilibrium based model with super imposed CO2kinetic effects (to estimate CO2 selectivity). Operating experience has shown that absorber off-gas will typically approach 3–4 times the equilibrium H2S partial pressure on the absorber top tray.6

These simulator results indicate that attaining an off-gas spec of 100 ppmv will require a lean amine H2S loading of 0.005 m/m or lower. Use of a typical refinery gas-sweetening unit lean amine H2S loading of 0.01–0.015 m/m would allow the reduc-tion of H2S to 250–500 ppmv, which may not suffice to meet the required overall sulfur recovery target.

2. Maximizing CO2 slip. The low pres-sure TGT absorber is usually designed with just enough trays/packing height to ensure that the gas leaving the column top is close to equilibrium with the lean amine entering the column with respect to H2S. Avoid over design to minimize CO2 absorption.

Table 2 illustrates the impact of number of trays on column performance. Increasing the number of trays allows some reduction in off-gas H2S concentration, but this comes

at the cost of increased CO2 co-absorption and it will eventual recycle to the Claus SRU. Typical CO2 slip observed in trayed MDEA TGTU absorbers ranges from 60–85%, but this can vary considerably based on column design. Yet, Simulators 3 and 4 simulate an unrealistically high CO2 slip, and show no impact on the number of trays for treated gas H2S concentration. This suggests that 10 trays are adequate to reach H2S equilibrium composition w.r.t feed lean amine.

It should be noted that commercial-grade MDEA commonly has some DEA impurity, which can reduce CO2 slip, and result in increased off-gas H2S concentrations. Use of high-purity MDEA can enhance TGTU performance.

3. Optimal amine concentration. The maximum H2S loading achievable in the rich amine leaving the absorber bottom is controlled by the feed gas H2S partial pressure and amine con-centration used. MDEA use became popular for refinery amine systems as it could be used at higher concentrations and with higher acid-gas loadings than the earlier generation primary and secondary amines, viz. MEA and DEA. MDEA also allows reduced CO2 pick-up in the absorbers. These factors resulted in operation with significantly reduced amine circulation rates. However, for the low-pressure TGTU absorber, operation with high amine concen-tration at high H2S loading is not feasible due to column bottom pinch. This leads to the question, “Is there any benefit to operating TGTU absorbers at high amine concentrations?”

This is examined in Fig. 4, which illustrates the variation in off-gas H2S and CO2 concentrations with amine circulation

TABLE 2. Impact of number of trays

H2S out, ppmv CO2 slip, %

Simulator Simulator Simulator Simulator Simulator Simulator Simulator SimulatorNo. of trays 1 2 3 4 1 2 3 4

10 307 244 61 141 84.4 84.8 96.3 98.5

14 135 100 61 141 79.1 79.5 96 98.0

20 93 70 61 141 71.3 72.1 92.8 97.2

25 85 66 61 141 65.1 66.7 91.1 96.8

Simulator 1Simulator 2Simulator 3Simulator 4Equilibrium limit @ 40°C1

Equilibrium limit @ 40°C2

0

50

100

150

200

250

300

350

400

450

500

0.000 0.0150.005 0.010Lean amine H2S loading, m/m

Off-

gas

H 2S,

ppm

v

Off-gas H2S concentration dependence on H2S lean amine loading for the TGT absorber defined in Table 1. Absorber top pressure considered is 105 kPa.

FIG. 3

0

100

40 60 80 100 120

200

300

400

500

600

700

800

900

1,000

Amine circulation rate, TPH

H 2S

in tr

eate

d ga

s, p

pmv

4.0

4.1

4.2

4.3

4.4

4.5CO

2 in

trea

ted

gas,

%m

olH2S (50 wt% MDEA)H2S (20 wt% MDEA)CO2 (50 wt% MDEA)CO2 (20 wt% MDEA)

Effect of amine concentration and amine circulation rate on off-gas H2S and CO2 concentration estimated with Simulator 2. Lean amine H2S and CO2 loadings considered were 0.005 m/m and 0.0001 m/m, respectively.

FIG. 4

TABLE 3. Case study- regenerator column

Rich amine feed Column

Temperature, °C 104 Condensor pressure 2.35 bara

Flow, kmol/h 7544 Reboiler pressure 2.6 bara

MDEA concentration 50wt% Condensor temperature 40C

H2S loading, m/m 0.077 Diameter, m 3.3

CO2 loading, m/m 0.027 Trays (total) 27

Trays (below feed location) 24

Weir Height, cm 5



rate for two amine concentrations, 20 wt% MDEA and 50 wt% MDEA. For the 50 wt% MDEA case, a sharp increase in off-gas H2S concentration is calculated at amine circulation rates below 50 TPH, which is indicative of a column bottom pinch. However, for the 20 wt% MDEA case, onset of pinch conditions occurs at a higher amine circulation rate of ~90 TPH. Thus, higher MDEA concentration use is estimated to allow operation with a lower amine circulation rate and a higher CO2 slip. (Typical MDEA application range is between 35 wt% and 50 wt%).

Amine regeneration. A typical rich amine feed to a TGTU regeneration column is considered to illustrate some design issues; this data is listed in Table 3.

1. Steam requirement. As previously discussed, a very low lean amine H2S loading of 0.005 m/m or lower is estimated to achieve off-gas H2S concentration below 100 ppmv. Attaining such low

lean amine loading requires high steam input to the amine regen-erator column (ARC) reboilers. For the ARC case in Table 3, Fig. 5 shows a specific steam consumption (SSC) variation with H2S lean amine loading estimated with various simulators. All the simulators estimate a sharp increase in steam consumption as H2S lean loading decreases below 0.01 m/m. However, there is considerable variability in the calculated magnitude of specific steam consumption.

Medium- and high-pressure refinery/gas plant absorbers required to reduce treated gas H2S to 4–40 ppmv can operate with H2S lean loading of 0.01-0.015m/m with a corresponding SSC of ~1 lb-steam/gal-amine. However, for the low-pressure TGTU that requires an H2S lean loading of ~0.005, ARC operates at sig-nificantly higher SSC of 1.5 lb-steam/gal-amine and is estimated with Simulators 2 and 3. However, Simulator 4 allows very low lean amine H2S loadings down to 0.003 m/m to be achieved with an SSC of 1 lb-steam/gal-rich amine.

From an overall unit design perspective, it is useful to look at ARC steam requirements for attaining a target absorber off-gas H2S concentration. This is illustrated in Fig. 6. For off-gas H2S concentration >400 ppmv, the discrepancy between the simulators is fairly small, with SSC of 0.6–0.8 lb-steam/gal-rich amine for all simulators. However, for off-gas H2S concentrations below 200 ppmv, the simulator results deviate significantly. For instance, for 100ppmv H2S in off-gas, Simulator 2 estimates SSC two times that obtained from Simulator 4. This suggests that different simu-lator use can lead to significantly different design when targeting off-gas H2S that is below 200 ppmv.

Reliability of these estimations is subject to the VLE data accuracy, especially at low H2S loading. Published VLE data

Simulator 3

Simulator 1Simulator 2

Simulator 4

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0.000 0.002 0.004 0.006 0.008 0.010 0.012 0.014Lean H2S loading, m/m

Rebo

iler s

team

con

sum

ptio

n (S

SC),

lb s

team

/gal

rich

am

ine

Reboiler specific steam consumption for producing lean amine of varying quality estimated with various simulators for the regenerator defined in Table 3.

FIG. 5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

0 200 400 600 800 1,000Off-gas H2S, ppmv

SSC,

lb s

team

/gal

rich

am

ine

Simulator 2Simulator 3Simulator 4

Simulator 1

Reboiler specific steam consumption required for associated tail-gas absorber off-gas H2S concentration estimated with various simulators.

FIG. 6

(a)

1.00

1.25

1.50

1.75

2.00

20 25 30 35 40 45 50Number of trays

SSC,

lb s

team

/gal

rich

am

ine

(b)

1.70

1.80

1.90

2.00

195 215 235 255Reboiler pressure, kPa

SSC,

lb s

team

/gal

rich

am

ine

120

125

130

135

Rebo

iler t

empe

ratu

re, °

CTemperature

SSC

Impact of number of trays and column pressure on reboiler specific steam consumption (SSC) for the case described in Table 3. Lean amine H2S loading considered was 0.005 m/m. Estimations were done with Simulator 2.

FIG. 7



at the ARC bottom conditions (H2S loading below 0.01 m/m, and temperature above 120°C) are scanty and of relatively lower accuracy. Thus, the estimations from the simulators should be validated using reliable operating data.

ARC lean amine CO2 loading is calculated to be significantly lower than the H2S loading. This is due to the higher volatility/K value of CO2 compared to H2S. The bulk of the CO2 in the rich amine strips out rapidly in the trays below the rich amine feed, while H2S stripping continues all the way down to the bottom of the column. At high specific steam consumptions, increase in CO2 loading in the rich amine feed does not result in an increase in the spe-cific steam consumption (SSC can even decrease at increased feed rich-amine CO2 loading). To a certain extent, the presence of CO2 acts as a strippping gas for H2S. This is in contrast to conven-tional regenerators designed to produce lean amine with acid-gas loadings of 0.015 m/m (or higher) in which the specific steam consumption increases in proportion to the feed rich amine acid-gas loading.

2. Number of trays. Using a higher number of trays in the stripping section of the ARC can be employed to reduce steam requirement for attaining a low lean amine H2S loading. Fig. 7a shows the effect of increasing the total tray number in the ARC on steam required (SSC) to obtain a lean amine H2S loading of 0.005. The rate of reduction in SSC decreases as the number of trays increases. Typically, 20–25 trays are used in the TGTU ARC.

3. Column pressure. ARC operation at higher pressure leads to higher column temperatures and better regeneration. ARC operating pressures are limited on the lower side by back-pressure requirement from the downstream SRU and on the higher side by temperature limit for keeping amine degradation rates down at acceptable levels. Fig. 7b shows the effect of column pressure variation on steam consumption (SSC) and reboiler temperature, using Simulator 2. Simulators 1 and 3 give a lower sensitivity of SSC to column pressure. A low sensitivity due to counter balanc-ing effects of higher acid-gas vapor pressure at higher tempera-ture and higher column pressure has been previously reported.6 Reduction in SSC at higher pressures/temperatures comes at a cost of increased amine degradation rates. For generic MDEA solutions, recommended reboiler process-side temperatures are 125°C or less (with steam temperature below 150°C) to keep degradation rates in check.4

Conclusions. Accurate rate-based process simulators are required for optimal design of SRUs–TGTUs. The TGTU absorber and regenerator columns operate at extreme conditions with respect to H2S lean amine loadings and steam consumption. Lean amine with H2S loading below 0.01 m/m is estimated to achieve TGT off-gas H2S spec below 200 ppmv. This, in turn, entails ARC operation with high steam consumption, with steam consumption increasing exponentially with decreasing lean amine H2S loading. Unlike conventional ARC where SSC is controlled by the feed rich amine acid gas loading, the TGT ARC SSC is controlled by the required off-gas H2S concentration and lean amine H2S loading.

Considerable variability was found among commercial simula-tors with respect to SSC required for attaining off-gas H2S level below 200ppmv. Scanty VLE data at low H2S loadings results in uncertainty in the simulator estimation of steam requirements, and off-gas H2S concentrations at low loadings. Reliable operating data from existing units are thus required to validate the simula-tor results, and to optimize the steam consumption required to

attain low off-gas H2S concentration and high overall sulfur recovery for the SRU-TGT plant. A literature scan found just a few relevant reports on operating data with TGT amine units. The gas industry would benefit from a common database of reliable plant operating data that can be used in all commercial simulators.

Options that have been explored to reduce steam consumption for TGT units include acid-addition and split-flow processes.5 Acid addition can

allow production of lean amines with very low H2S loading (~0.001 m/m) with lower steam consumption. Split-flow ARC are sometimes used for refinery units that have critical users, e.g. TGTU and fuel gas absorbers where any H2S slip ultimately results in more SO2 emissions and less-critical users (e.g., absorb-ers for recycle gas in hydro-processing units) where bulk removal is sufficient. HP

LITERATURE CITED 1 Jou, F., A. E. Mather and F. D. Otto,”Solubility of H2S and CO2 in Aqueous

Methyldiethanolamine Solutions,” Industrial & Engineering Chemistry Process Design Development, Vol. 21, pp. 539–544, 1982.

2 Rogers, W., J. A. Bullin and R. R. Davison, “FTIR measurements of acid-gas-methyldiethanolamine systems,” AIChE Journal, Vol. 44 Issue 11, pp. 2423–2430, November 1998.

3 Huttenhuis, P. J. G., N. J. Agrawal, J. A. Hogendoorn, and G. F. Versteeg, “Gas Solubility of H2S and CO2 in aqueous solutions of n-methyldieth-anolamine,” Journal of Petroleum Science and Engineering, Volume 55, pp. 122–134, 2007.

4 Dupart, M. S., T. S. Bacon and D. J. Edwards, “Understanding corrosion in alkanolamine gas treating plants,” Hydrocarbon Processing, April 1993.

5 Wong, V. W., J. Y. Mak and T. K. Chow, “The DAP and STREP Processes for Acid Gas Removal, Acid Gas Enrichment, and Claus Tail-Gas Treating,” Brimstone Sulfur Recovery Symposium, 2007.

6 Huffmaster, M. A., “Stripping requirements for selective treating with sulfinol and amine systems,” Laurance Reid Gas Conditioning Conference, p. 262, 1997.

ACKNOWLEDGMENTThe author thanks Ashwin Nagarajan and Michiel Baerends of Fluor for their

assistance in preparing and reviewing the article.

■ The gas industry would

benefit from a common database

of reliable plant operating

data that can be used in all

commercial simulators.

Soumitro Nagpal is a process specialist with Fluor India. He has over 20 years experience in process design and development. Dr. Nagpal’s primary areas of work have been gas processing, gas-treating, sulfur recovery, CO2 and SO2 capture, petcoke gasification and alumina refining. He developed rate-based models for selective

gas-treating applications and used these models for process design and the revamp of gas-treating units in India. In the past, Dr. Nagpal has worked at Engineers India Limited and Imperial College, London. He received a BE in chemical engineering from Birla Institute of Technology & Science, Pilani and a PhD in chemical engineering from the University of Utah.

ENVIRONMENT


C apture and storage of carbon dioxide (CO2) is a techni-cally feasible method for making deep-reductions in CO2 emissions. As more governments mandate tighter emission

rules for carbon emissions, HPI companies must make thoroughly reasoned decisions when considering carbon captured and storage (CCS) projects. This case history investigates the economics of a CCS project with CO2 recovery.

Climate change. “The capture and storage of carbon dioxide is a technically feasible method of making deep reductions in CO2 emissions.”1 This statement, made by the Intergovernmental Panel on Climate Change, is widely accepted, as is the need for timely development of carbon capture and storage (CCS) demonstra-tion projects. However, without a clear projection of the future CO2 market value, the business case to make these demonstra-tion projects economically viable may be questionable. However, using CCS for enhanced oil recovery (EOR) via captured CO2 can provide economic drivers in some situations.

Economic solutions. Using captured CO2 for EOR may raise an interesting question for project stakeholders: “if the captured CO2 from a CCS project is used for EOR, does the project still result in a net reduction in CO2 emissions to the atmosphere?” This question could be answered by suggesting that the oil would be extracted anyway and that injecting CO2 for EOR does not affect the total global crude production rate. However, using CO2 for EOR implies significant reservoir depletion and that the incremental oil recovered as a direct result of CO2 injection would have remained unrecovered otherwise. We will discuss whether or not a CCS project with EOR would result in a net reduction in CO2 emissions to the atmosphere and to identify key factors that determine the total overall carbon emissions avoidance resulting from such projects. Simplified calculations may be done by bal-ancing the carbon extracted in the form of oil against the carbon permanently stored as CO2, as well as considering the emissions resulting from the likely use of extracted oil.

CO2 STORAGE OPTIONSA number of storage options have been postulated, including

storage in geological formations or deep-sea storage, where pressure of the overlying water column maintains the CO2 in supercritical form. There are significant technical and environmental risks asso-ciated with deep-sea storage that are at present unresolved.

The geological storage options include saline aquifers, depleted oil wells and depleted natural gas wells. Enhanced hydrocar-bon recovery is an option that can be considered for the two-well scenarios. Depleted wells have a significant advantage over saline aquifers, not only for the economic potential of EOR and enhanced gas recovery (EGR) but also because the containment integrity has been proven, although additional surveys may still be required to confirm this parameter.

For saline aquifers, more extensive geological surveys are required to characterize the storage location and caprock and to determine that the location is free from faults and discontinuities within the caprock, thus preventing injected CO2 from leaking back to the surface. In all permanent geological storage cases, continuous monitoring is required during, and for a significant period after CO2 injection.

The characteristics of each geological site will have a significant effect on the possible injection rate and, for oil and gas wells, the enhanced hydrocarbon recovery potential. Well permeability, depth and pressure are key factors to be considered, and these result in a wide range of experienced and anticipated recovery rates per unit of CO2 injected from one site to the next. Issues such as public acceptance and legal aspects of permanent CO2 storage, such as long-term operator liability will not be considered within the scope of this article.

Methodology. Three CCS with EOR project cases will be considered:

• Case A—Fossil-fuel power station with CCS, EOR, down-stream refinery or conventional power plant.

• Case B—Fossil-fuel power station with CCS, EOR, power plant with CCS sequestered in a saline aquifer.

• Case C—Fossil-fuel power station with CCS, EOR, power plant with CCS, EOR in a closed loop.

The CCS project cases will then be compared against control cases:

• Case D—Conventional power plant without CCS• Case E—Fossil-fuel power station with CCS, CO2 seques-

tered in a saline aquifer.The analyses will be conducted over three main steps for each

case. Step 1 considers only the emissions avoidance of the carbon-capture power plant. Step 2 calculates the expected net storage of carbon when CO2 is applied for EOR. Step 3 considers the emis-sions resultant from the likely use of incremental oil extracted.

When does carbon capturemake sense?Here are several options in which carbon capture can providecost-effective solutions

S. FERGUSON, Foster Wheeler Energy, Reading, Berkshire, UK

ENVIRONMENT


The analysis will consider the following example fossil-fuel fired plant for all cases; natural-gas fired combined cycle with net power output of approximately 350 MW, annually emitting 1.3 metric million tons of CO2 before carbon capture (Fig. 1).

Step 1—Fossil-fuel power plant with CCS. The global demand for power is ever increasing, and it can be assumed that a significant number of new, conventional power plants will be required to prevent a significant supply shortfall. We can begin our analysis by drawing a system boundary around a generic, 90% carbon-capture power station, which is proposed in place of a conventional power station (Fig. 2). Since a power station was required anyway, building one which emits only 10% of the CO2 that would otherwise have been emitted clearly results in a 90% net carbon emission reduction.

Step 2—Fossil-fuel power plant with CCS and EOR. If the CO2 is intended for EOR, then the total carbon storage of the project is impacted. Although a significant quantity of carbon will be stored in the reservoir as CO2, a significant quantity of carbon will be released from the reservoir in the form of oil. The balance between the mass of carbon stored vs. the mass of carbon recovered is key to the total carbon storage level of this project (Fig. 3).

The expected quantity of oil that can be recovered per unit of CO2 stored depends on the characteristics of the individual reservoir, such as permeability and pressure. This projected figure for the reservoir enables calculation of the net carbon storage.

Step 3—CO2 resulting from using extracted oil. The majority of crude oil used globally is processed in refineries into

a wide range of products, mostly fuels—although some crude is also fired or co-fired directly to generate power. This study will consider three cases for the end-use of oil:

• Refinery or conventional power plant feedstock• Carbon-capture power plant feedstock—storage in saline

aquifer• Carbon-capture power plant feedstock—EOR.

TOTAL CARBON AVOIDANCEFor CCS projects with EOR, the total carbon avoidance should

be calculated to include all three steps of the project chain: carbon emitted and stored across the power plant, in the reservoir and resultant from the recovered-oil end use.

Power plant net output and carbon avoidance. Power requirements for the CO2 capture and compression units of the power plant with CCS result in a reduced overall efficiency, requir-ing more consumption of fuel per MW of electricity net produced. To account for this efficiency reduction, a “90% carbon capture avoided” power plant with CCS would actually need to capture approximately 92% of its CO2 emissions, if it fired natural gas (or 93%–94% for coal-fired plants) to meet the “90% avoided” target, as compared to a conventional fossil-fuel fired power plant. For this analysis, the carbon-capture power plant is defined as “90% carbon avoided” overall, with a net power output of 350 MW.

Construction phase and other emissions. CO2 emis-sions resulting from the construction phase of the facility were assumed to be small as compared to the operational phase. Simi-larly, a full life-cycle analysis was not done as other contributing factors, such as land use change, are anticipated to be of lower impact as compared to the variables considered in this study.

CO2 recycle at the wellhead. It was also assumed that 100% of the CO2 that returns to the surface with the extracted oil is separated and re-injected as per normal practice.9 Without the CO2 injection, it would not be possible to extract further oil from the reservoir in question. Any additional process equipment and operational CO2 emissions at the injection site have not been considered. No consideration has been made for additional power required to recycle or compress CO2 at the wellhead.

ANALYSESThis example will consider a natural-gas fired power plant as

the base case.

Fossil-fuelpower plant

Natural gas

100% of CO2to atmosphere

Electricalpower

Systemboundary

Step 1—Block flow diagram of a natural-gas fired power plant with no CCS.

FIG. 1


Naturalgas


Electricalpower

Systemboundary

CO2 capture andcompression

90% of CO2to sequestration

Step 1— Block flow diagram of a natural-gas fired power plant with CCS.

FIG. 2


Naturalgas


Electricalpower

Systemboundary

CO2 captureand

compression

Incrementalcrude oilPartially

depletedreservoir

Step 2— Block flow diagram of a natural-gas fired power plant with EOR.

FIG. 3

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ENVIRONMENT


Step 1—Carbon-capture power plant. In the study, a conventional 350 MW (net) natural-gas fired power plant would have annually emitted 1.1 million metric ton (mMMtpy) of CO2. Instead, a 350 MW (net) natural-gas fired power plant with carbon capture is built, producing 1.3 mMMtpy of CO2 of which 0.1 mMMtons is emitted to the atmosphere and 1.2 mMMtons are transported to storage. The total CO2 emissions avoided are 1 mMMtpy, or 90%:

CCS power plant CO2 = 1.1 0.1= 0.1 mMMtpy (1)CCS power plant CO2 = 1.3 0.1= 1.2 mMMtpy (2)

Where “F” denotes carbon or CO2 emitted and “f” denotes car-bon or CO2 permanently stored.

Note: that had a saline aquifer or other permanent storage location been selected for the CO2 storage, then the analysis would end here, with the total carbon avoidance being equal to the carbon avoidance of the CCS power plant.

Step 2—Carbon capture power plant with EOR. The 350 MW natural-gas fired carbon capture power station captures 1.2 mMMtpy of CO2, as shown in Eq. 2:

Molar rate of:

CO2 =1.2 109

365 24 44.01= 3,112.6 kmol/h (3)

Mass rate of carbon injected:

C =3112.6 12.01 8760

1,000= 327,500 metric tpy (4)

In our example case, the maximum expected additional output from the reservoir is 40 MMbbl of oil over 15 to 20 years.2 Making an assumption based on the 20-year case, the oil resultant from stor-ing 1.22 mMMtons of CO2 is 2 MMbbl per year, on average.

The composition of a typical crude can be used to calculate the carbon recovered in the form of oil. For example, a Middle Eastern heavy crude is composed of approximately 85 wt% car-bon, 12 wt% hydrogen and 3 wt% sulfur. For a lighter crude, the hydrogen content will be higher and the sulfur content lower; yet, the carbon content will remain essentially the same. The typical specific gravity for this Middle Eastern crude is 0.89 and thus:

Carbon in extracted oil:

C =2 106 0.89 0.85

6.29= 240,800 metric tpy (5)

(Converting barrels of oil to cubic meters using 6.29 bbl/m3)

The net carbon stored:C = 327,500 240,800 = 86, 700 metric tpy (6)

Therefore, 26% more carbon is stored than is recovered using CO2 for EOR and 74% of the carbon returns to the surface. The CO2 emissions resulting from the return of this carbon to the surface depend entirely on the end use of the extracted oil.

Step 3—CO2 resulting from the use of extracted oil. In Case A, we will consider a refinery or conventional power plant feedstock. For the refinery case, most of the final products will be combusted as fuels. Although some carbon will be consumed as feedstock for petrochemical/chemical processes, and are therefore not combusted, a significant amount of carbon will be used to provide heat and power to the refinery itself, therefore the CO2 emissions resulting from the refinery are equivalent to having

combusted 100% of that oil. A conventional power plant will also result in combustion of 100% of the extracted oil. For this analysis, the two end uses can be assumed to result in the same emissions level:

100% combustion of oil

CO2 =240,800 44.01

12.01= 880,000 metric tpy (7)

Case B. Carbon capture power plant feedstock—storage in saline aquifer. If the extracted oil is fired in a power plant designed for 90% carbon capture, then the total resulting emissions will depend on the use of that captured CO2. If the CO2 is stored in a saline aquifer, then only the emissions from the plant must be considered:

Emissions from 90% CCS plant:CO2 = 880,000 tpy 0.1= 88,000 metric tpy (8)

Case C. Carbon capture power plant feedstock—with EOR. If a CCS power station is operated in a closed loop with storage and an EOR reservoir then the total CO2 emissions avoided, including the EOR component, remains 90%, as shown in Fig. 4. (Note: This assumes that the power plant is oil-fired rather than gas-fired and that oil recovered through EOR is less than the total fuel requirement of the power plant, with the deficit being made up with imported fuel from elsewhere.)

The only streams crossing the system boundary are imported makeup fuel (if required to maintain power output at 350 MW net) and 10% of combustion generated CO2, which is released to the atmosphere from the original capture plant. Therefore, the addi-tional CO2 emissions due to the end use of the recovered oil are:

Additional emissions from CCS plant: CO2 = 0 metric tpy (9)

OVERALL CARBON AVOIDANCE RESULTSWe have calculated the carbon balance across each step in the

process from the original power plant, the EOR reservoir and end use of the recovered oil. The total carbon avoidance results can be calculated for each end-use case presented here:

Case A consists of a carbon-capture power plant with CCS for EOR. The resultant oil is subsequently combusted, either as power-plant feedstock, or as refinery products such as transport fuels:


Makeupfuel


Electricalpower

Systemboundary

CO2 captureand

compressionIncremental

crude oil

Partiallydepletedreservoir

Step 3—Block flow diagram of a natural-gas fired power plant in a closed loop with an EOR reservoir.

FIG. 4

ENVIRONMENT


Case A total emissions:CO2 = 110,000 + 880,000 = 990,000 metric tpy (10)Case A carbon avoidance:

CO2 =1,100,000 990,000

1,110,000100 = 10% (11)

Case B consists of a power plant with CCS for EOR. The resultant oil is subsequently combusted in a second 90% carbon-capture power plant from which the CO2 is stored in a saline aquifer:

Case B total emissions:CO2 = 110,000 + 88,000 = 198,000 metric tpy (12)Case B carbon avoidance:

CO2 =1,100,000 198,000

1,110,000100 = 82% (13)

Case C consists of a power plant with CCS for EOR. The plant is operated in closed loop with the reservoir; combusting the recovered oil as fuel with a makeup stream imported, operating at 90% carbon capture:

Case C total emissions:CO2 = 110,000 + 0 = 110,000 metric tpy (14)Case C carbon avoidance:

CO2 =1,100,000 110,000

1,100,000100 = 90% (15)

Conventional-power station case, Case D. For compar-ison, the same calculation can easily be done for the conventional power plant case, Case D:

Case D total emissions: CO2 = 1,100,000 metric tpy (16)Case D carbon avoidance:

CO2 =1,100,000 0

1,100,000100 = 0% (17)

Permanent storage case, Case E. The same can be applied to a carbon-capture power station for which the CO2 is stored directly in a saline aquifer, or similar permanent storage location, instead of being used for enhanced hydrocarbon recovery, Case E:

Case E total emissions: CO2 = 110,000 metric tpy (18)Case E carbon avoidance:

CO2 =1,100,000 110,000

1,100,000100 = 90% (19)

The total carbon emissions and avoidance for each case are summarized in Table 1.

Sensitivity analysis. The analysis conducted is highly sensi-tive to the quantity of oil recovered per unit of CO2 injected into the reservoir. The calculations above are based on assuming that 40 million barrels are recovered over 20 years. Any change in the assumed recovery rate could have a significant impact on the bal-ance of carbon stored vs. carbon recovered from the reservoir.

Considering the high impact of this variation, a sensitivity to the expected rate of oil recovered per metric ton of CO2 injected

was done. Table 2 shows a range of figures for the quantity of oil recovered as a function of the CO2 injection rate from different data sources for different example locations:

Calculating the resultant proportion of carbon that remains stored in the reservoir over this range of figures is shown in Fig. 5, where the proportion of carbon stored is calculated as:

CO2 =

(carbon in injected CO2 ) (carbon in extracted oil)

(carbon in injected CO2 )100

Fig. 5 shows that carbon storage in the reservoir can range from 0% to 37% depending on the mass of CO2 stored per bar-rel of incremental oil recovered. This clearly has a very significant impact on the total carbon avoidance of the project and must be assessed for each project rather than relying upon any generic assumption of recovery or storage.

For our example project, the site-specific data gave a 26% carbon storage averaged over the life of the project. This shows that the very lowest figures would result in zero or negative carbon storage in the reservoir. Therefore, the end use of the recovered oil

TABLE 1. Overall emissions and carbon avoidanceof the example CCS project

Case Total CO2, mMMtpy CO2 avoided, %

A CCS plant, EOR, refinery .99 10

B CCS plant, EOR, CCS plant, aquifer .198 82

C CCS plant, EOR, CCS plant, EOR, loop .11 90

D Conventional power plant 1.1 0

E CCS plant, saline aquifer storage .11 90

TABLE 2. EOR incremental oil recovery per metric ton of CO2 injected

te CO2 / bbl incremental oil Data source

0.45 to 0.6 Projected for Miller Field, North Sea2

0.44 Weyburn-Midale “typical,” Canada3

0.5 to 0.68 BERR projection for North Sea, 20076

0.68 USA averaged “typical”6

0.6 Paper example project

Reservoir net storage of carbon

-10

0

10

20

30

40

0.3 0.5 0.70.4 0.6 0.8Metric tons of CO2 stored per bbl incremental oil recovered

Prop

ortio

n of

car

bon

perm

enan

tly s

tore

d, %

Example project

Sensitivity graph of carbon stored in different locations.FIG. 5

ENVIRONMENT


would be key to the project total emissions avoidance. Conversely, in cases with high CO2 storage per bbl recovered, the end use has significantly less impact on the total balance of emissions avoided by the project.

Outlook. It can be seen in Table 1 that, in our example case, a 90% carbon-capture power station with EOR stores approxi-mately 26% more carbon as CO2 than is extracted as oil. A total project carbon emissions avoidance level of 10% is achieved, assuming that the extracted oil is eventually combusted. How-ever, if the recovered oil was subsequently combusted in a similar 90% carbon-capture power plant, then the total project carbon emissions avoidance level would be increased to between 82% and 90%.

It can be concluded that, despite the large quantity of carbon that is brought back to the surface as a result of using captured CO2 for EOR, the total project still provides a significant net environmental benefit in terms of CO2 emissions avoided, even if, as in the worst case, 100% of the recovered oil is combusted. The extent of total CO2 emissions avoided for a specific project is highly dependent on:

• End use of the extracted oil• Reservoir characteristics, particularly the projected oil recov-

ery per metric ton of CO2 injected.Thus, before the total carbon emissions avoided can be calcu-

lated for a proposed CCS project with EOR, both of these factors must be quantified. HP

LITERATURE CITED 1 IPPC, Intergovernmental Panel on Climate Change Special Report on

Carbon Dioxide Capture and Storage, 2005. Prepared by Working Group III of the Intergovernmental Panel on Climate Change; Metz, B., O. Davidson, H. C. de Coninck, M. Loos and A. Meyer (Eds.).; Cambridge University Press, Cambridge, UK, and New York, NY, p. 442.

2 http://www.bpalternativenergy.com/liveassets/bp_internet/alternativenergy/next_generation_hydrogen_peterhead.html.

3 http://www.ptrc.ca/weyburn_overview.php. 4 http://www.netl.doe.gov/publications/proceedings/01/carbon_seq/2a1.pdf. 5 http://www.ptrc.ca/siteimages/Summary_Report_2000_2004.pdf. 6 Becky, A., D. Hughes and M. Raistrick, “Introduction to the Geological

Storage of Carbon Dioxide,” Senergy Training Course, Guildford, UK, October 2008.

7 Wehner, S., “Operators apply CRP to a giant,” Hart Publications, Houston, Texas.

8 “CO2 EOR Technology, Technologies for Tomorrow’s E&P Paradigms,” US Department of Energy, Office for Fossil Fuel Energy, National Energy Technology Laboratory, March 2006.

9 “Storing CO2 with Enhanced Oil Recovery,” US Department of Energy, National Energy Technologies Laboratory, February 2008.

Suzanne Ferguson graduated with an MEng (Hons) in chemi-cal engineering from the University of Surrey in 2004 and joined the Foster Wheeler Energy Ltd. (FWEL) graduate training program. In her first three years at Foster Wheeler, she worked on refinery and hydrogen unit front-end engineering design (FEED) projects

and performed basis of design, FEED and EPC-phase dynamic simulation for LNG projects, obtaining her chartership as a chemical engineer in 2007. Ms. Ferguson is now a member of the CCS and gasification team in FWEL’s Business Solutions Group where she has worked on a range of CCS studies, FEED and pre-FEED projects. In 2008, she completed a training assignment at Foster Wheeler’s Italian operation in Milan during which she worked on power island design.

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Managing costs and incidentsin industrial plant equipmentUse this method to allogate limited maintenance resourcesto the most critical equipment

M. GARDELLA, E. EGUSQUIZA, X. ESCALER, Technical University of Catalonia, Barcelona, Spain; and A. GOTI, University of Mondragón, Guipúzcoa, Spain

T he purpose of this research is implementing a continuous improvement initiative in terms of reliability, availability, maintainability and safety. This article presents a method

with the goal of showing in which equipment, how and with which cost incidents related to maintenance appear in industrial plant equipment. The approach will be developed through performance ratios. The goal of the initiative is to extract the information required to know where the maintenance resources are spent and which criti-cal points reduce the availability of industrial plant equipment.

The study centers on three ratios: the number of incidents, their cost and the fraction between the cost and the number of incidents, all of them grouping incidents by equipment type or considering each piece of equipment. Each of these groups is presented in a structured way to back up plant managers in the decisions they make.

With the methodology designed, it is possible to know the number of events of a specific type of incident per machine type and its associated cost.

Thus, a procedure is defined for establishing reference values for indicating the importance of the frequent repetition and the cost of plant incidents.

The developed approach is applied to a chemical plant for several types of equipment: several incidents and costs related to pumps are systematically detailed.

The study aims at showing the importance of organizing the information in a structured way, which can be applied in the maintenance management of an industrial plant to improve the assigned resources, reducing costs and rocketing productivity.

Introduction. This work presents a method to extract informa-tion about incidents related to maintenance performed on indus-trial plant equipment, based on the studies developed by Bradley and Dhillon.1,2 In each of their works a compilation of incidents is performed, studying the periodicities that happen over the time.

A main difference between maintenance management as a business unit and maintenance benchmarking relies on the fact that the first aims at maximizing the maintenance department performance whereas the second is oriented to maximizing the plant profitability, as is indicated by Kelly and Levitt.3,4 Both maintenance as a business unit and benchmarking related to maintenance are taken as a basis for the presented research, as both goals are pursued jointly.

The objective herein is to establish a path that allows visual-izing the types of incidents that happen in a plant, categorized by different types. Thus, it is possible to focus the limited plant resources on improving the effectiveness of its resources, as Souris, Wireman and Goti recommend.5,6,7

To structure the maintenance activity information three main management ratios are presented: the amount of incidents, their cost and the ratio between these costs and number of incidents. Next, the ranges of the necessary values to size the importance of the ratio are presented. Machines with high values in their ratios are critical points for maintenance so that resources may be pri-oritized toward this machinery.

The diminution in the values of these ratios represents that the plant is managed more efficiently, increasing its productivity, as is affirmed by Juric,8 thanks to reductions in stoppages and unavail-ability, as Amendola and García Garrido indicate.9,10

Literature review. Failures producing anomalies in equip-ment operation are presented according to their relevance and gravity, as proposed by Narayan.11 These failures should be quan-tified, as proposed by Wireman.12

Industrial companies try to maximize the productivity of their equipment through management models that organize the human and technical resources they have, as Campbell and Tomlingson indicate.13,14 Performance indexes utilized herein are frequently related to productivity and quality, always trying to respect envi-ronmental regulations, as stated by Narayan and Wireman.11,12

The aim of any management model or philosophy, such as RCM, TPM, etc., is to try to maximize resource effectiveness, to avoid unscheduled stoppages and obtain the desired performance ratio values, as proposed by Amendola.9

MTBF is a reliability ratio consisting of the averaged value of working time between stoppages. It is scientifically related to reliability laws throught the failure rate.15,1,16 MTBF is comple-mented with the maintainability parameter MTTR. These ratios are useful to measure the amount of incidents in a system during a period of time.

Once events are technically analyzed, it is very important to perform a profitability study of the actions to be made, as Ber-man indicates.17

Thanks to the literature review, it is shown that the models and methods related to optimizing maintenance productivity and reli-



ability propose an overall framework. In this framework ways to detect significant productive inefficiencies through performance ratios must be developed, considering both economic impacts of incidents and how many times these events are repeated. Addition-ally, the proposed structure has to be helpful to propose actions that are profitable for the company.

The mentioned references also help in understanding how pro-duction and maintenance departments work, their needs and their objectives. But as a conclusion of the literature review a gap is detected in defining a method for the practical identification and prioritization of productive inefficiencies caused by equipment or system failures. This gap is also extended to the way the method results are presented, which should permit production and maintenance work together.

Industrial plant maintenance departments that act in a mainly corrective way have to somehow justify their usually high costs related to maintenance. The MTBF and MTTR values of their equipment are a function of their own effectiveness, being rela-tively difficult to be compared with other plants. This may hap-pen because of their deficiency in management, more specifically due to the lack of organization for identifying and being short of preventive maintenance interventions.

Thus, the next section proposes a methodology to detect sig-nificant productive inefficiencies through performance ratios, con-sidering both economic impacts of incidents and how many times these events are repeated. The work is then tested and applied to different cases to analyze its validity.

This way of working makes it easy to analyze the plant effi-ciency level. By sizing the parameters in the methodology pro-posed in the next section properly which combinations of failure modes and systems are more important can be determined.

In these critical points is where more human and technical resources can be used to diminish the value of the index, and thus obtain a higher efficiency. This procedure leads to the implanta-tion under the concepts of economic reliability and feasibility.

Methodology. The methodology proposed herein follows the steps presented in the scheme detailed in Fig. 1.

The information reported in the daily operative by all the departments is varied and complex, with several input and out-put values in the computerized management systems they use. In this study it is necessary to extract the information related to the maintenance actions in the different plant areas. It is also really important to have access to data about time and cost associated with these interventions.

Thus, it is important to integrate into a worksheet the follow-ing variables:

• Incident number• Industrial plant area• System affected by the incident• Incident description• Incident date• Number of hours to solve the incident• Cost associated with the incident repair.Once the information is properly arranged, it is necessary to

obtain the performance indexes to control the information and, therefore, manage the plant maintenance.

The indexes proposed in this article are the cost of the inci-dents, their numbers and the fraction obtained by dividing the cost with the number. Prior to the estimation, it is essential to define the incident and equipment types, and this work is a func-tion of the equipment type we have within our industrial plant.

Reckoning process. Eqs. 1 to 12 indicate the way to count maintenance incidents and costs in a structured way. Eqs. 1, 2, 3 and 4 count the total, per equipment, equipment and incident type and number of incidents, respectively.

Itot = Iij (k.l ),

ji k and l (1)

I je

= Iije(k.l ),

i

k and l (2)

Ile= Iij (k.l ),

ji

with Iij (k.l ) = 1 l = le and

with Iij (k.l ) = 0 1 le , and k (3)

Ike= Iij (k.l ),

ji

with Iij (k.l ) = 1 k = ke and

with Iij (k.l ) = 0 k ke , and 1 (4)

Eqs. 5, 6, 7 and 8 count the total, per equipment, equipment and incident types and cost incidents, respectively.

Ctot = Cij (k.l ),

j k and l

i(5)

C je

= Cije(k.l ),

i

k and l (6)

Definition of incidentsand equipment types

Information summaryof maintenance

Incident assignment types

To add incidents and costs forincident and cost types

To establish indicatorrange values of incidents,

costs and ratios

Contribution of technical andeconomic improvements

Obtaining and analysisof new results

Good results?No

Optimized system

Yes

Representation and resultsanalysis

Scheme for managing incidents.FIG. 1

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Cle= Cij (k.l ),

ji

with Cij (k.l ) = 1 l = le and

with Cij (k.l ) = 0 l le , and k (7)

Cke= Cij (k.l ),

ji

with Cij (k.l ) = 1 k = ke and

with Cij (k.l ) = 0 k ke , and l (8)

Eqs. 9, 10, 11 and 12 count the total, per equipment, equip-ment type and incident cost/incidents fraction, respectively.

CItot

=Ctot

Itot

, k and l (9)

CI je=

C je

I je

, k and l (10)

CIle=

Cle

Ile

, with Cij (k.l ) = 1 and Iij (k.l ) = 1 l = le .

with Cij (k.l ) = 0 and Iij (k.l ) = 0 1 le , and k (11)

CIke=

Cke

Ike

, with Cij (k.l ) = 1 and Iij (k.l ) = 1 k = ke and

with Cij (k.l ) = 0 and Iij (k.l ) = 0 k ke , and l (12)

Once the values from theses management ratios have been calculated then they have to be discussed. To do that, where the

highest and lowest values are obtained must be analyzed. These values must represent a unique group of importance or gravity defined for each group for a range of values for each ratio.

The lowest and highest points of each range of values are as well a function of the frequency we perform the analysis, being possible to apply a weekly, monthly, quarterly, annual, etc., periodicity.

Fig. 2 indicates the relationship existent between the ratio val-

Frequency

Variables

Seriousness

10 years

4,0001,000

2,000

1 105 2 105

2 105 5 105

10,000

25,000

7,500

500

20010

20

400

1,500

1AI

BI

AC

AC

AC/I

BC/I

2

20

Very

low

Low

Norm

al

High Ve

ry h

igh

100

2040 40 40 40

5050 50 50 50

5 years1 year

1 month1 week

Value ranges for performance indexes per equipment types.

FIG. 2

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DEFINING THE ART OF ENGINEERING EXCELLENCE



59

ues and the number of incidents, along with their costs and costs–incidents relationships. Some example values are given as well.

Eqs. 13, 14 and 15 indicate the value ranges for the number of incidents, incident costs, and ratio values per incident management indexes. These equations are adapted to the equipment type.

AI and BI in Eq. 13 indicate the lower and upper values for the number of incidents per equipment type. In addition, AC and BC in Eq. 14 represent the lower and upper values for the incident cost per equipment type. Lastly, AC/I and BC/I in Eq. 15 present the lower and upper values for the cost/number of incidents ratio per equipment type.

IleAI and I le

BI , with Iij (k.l ) = 1 l = le and

with Iij (k.l ) = 0 l le, and k (13)

CleAC and Cle

BC , with Cij (k.l ) = 1 l = le and

with Cij (k.l ) = 0 l le , and k (14)

CIleAC / I and CIle

BC /I , with Cij (k.l ) = 1 and

Iij (k.l ) = 1 l = le . with Cij (k.l ) = 0 and

Iij (k.l ) = 0 l le , and k (15)

Eqs. 16, 17 and 18 present the management ratio values related to the number of incidents and costs. These equations are related to a specific piece of equipment.

DI and EI in Eq. 16 represent the lower and upper values of the range of the number of incidents per piece of equipment. DC

and EC in Eq. 17 indicate the very same index but considering costs, while DC/I and EC/I in Eq. 18 are the same but for the costs/number of incidents ratio.

I je

DI and I jeEI , k and l (16)

C je

DC and C jeEC , k and l (17)

CI je

DC /I and CI jeEC / I , k and l (18)

The ratio range values are established by production and main-tenance managers. They are established through an extrapolation of the values obtained in the daily management ratios to the values to be obtained by these new indexes; thus, these complementary ratios help improve plant performance by complementing, with little effort, the operative ones identifying critical points that may not be identified with classical procedures.

Chemical plant application. This application is based on the information compiled in a Spanish chemical plant during a year.18 Specifically, all data necessary to calculate the variables pre-sented in the methodology section are exported to a spreadsheet.

This information is sorted taking into account the classifica-tion for equipment types and incidents shown in Table 1 based on the works of Gardella, August, Mobley and Moubray.19,18,20,21

Reckoning process. Using Eqs. 1 to 12, Tables 2, 3 and 4 show the number of incidents, their related costs and the costs/number of incidents ratio, for the types of incidents detailed in Table 1. Tables 5 and 6 present the information related to the

TABLE 2. Number of incidents per incident and equipment type

Agitator 0 29 9 1 26 3 1 69

Pump 104 728 165 146 256 580 7 1986

Boiler 44 5 0 5 1 16 0 71

Distillation 38 1 1 54 5 32 0 131 column

Heat exchanger 30 0 0 110 0 48 0 188

Reactor 347 23 15 210 178 61 0 834

Tank 127 70 3 79 0 160 1 440

Total 690 858 193 605 466 906 9 3,727

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TABLE 1. Equipment types and incidents

Equipment types Incident types

Agitator Instrumentation

Pump Magnetothermic off

Boiler Fastener leak

Column distillation Joint leak

Heat exchanger Lubrication

Reactor Planned revision

Tank Nailed pump




number of incidents with their costs. It is worth noting that for this case the studied elements are pumps.

Three groups or value ranges are defined for gravity, indicated with green, yellow and red colors depending on the lower or higher importance, respectively. White-colored cells represent noncritical equipment (Table 7).

In a cell in Table 2 there appears a 580 value (high gravity (red)) for the type of incident planned revision of the pump equipment. In Table 3 it is possible to observe that its cost is 60.548 € (average grav-ity (yellow)) and a fraction of 104,39 €/incident (low gravity (green)), in Table 4. This third ratio is an example since it shows the relative importance of a specific incident in the studied chemical plant.

Table 7 shows the lower and upper limits for the ranges of values for the management ratios presented in the previous tables, using Eqs. 13–18. It is worth remembering that these values are specific for this example, being necessary to adapt these limits to this situation.

Once the management ratios are detailed, it is necessary to establish priorities in assigning resources with the objective of diminishing the value of the indexes presented herein.

The reduction in the number of incidents and their costs in a machine is based on finding the best combination of economic and technological solutions, to guarantee that the interaction

among the productive process, maintenance, technical and mana-gerial concepts improves the plant performance.

Discussion of results. It can be observed in Tables 2, 3 and 4 that the type of incident magnetothermic off shows 728 incidents (red), being a very high value, costing 27,779 € (green) and a frac-tion of 38 €/incident, being a noncritical incident. Once analyzed from the study results it is clear that each incident of this type is not important, but it is significant on the whole.

After having studied and analyzed the causes of the incident type, magnetothermic off, it is concluded that it may happen because of an overcharge in the equipment, a lack of lubrication or refrig-eration, etc. In these cases the problem cannot be assumed by the maintenance department, because the equipment is not working in the conditions it should and the total annual cost is very high.

Concerning the reactor equipment, only 61 incidents have happened (green (low gravity)) with the reason planned revision, with a total cost of 163,320 € (red (high gravity)), with a costs/number of incidents ratio that is also critical.

TABLE 4. Cost/number of incidents ratio per incident and equipment types

Agitator 0 175 133 25 183 541 8 152

Pump 73 38 428 223 73 104 600 220

Boiler 275 4 0 75 10 1.498 0 266

Distillation 106 1 45 153 1.031 937 0 325 column

Heat exchanger 50 0 0 336 0 2.123 0 358

Reactor 122 49 30 284 22 2.676 0 455

Tank 109 18 179 174 0 41 60 83

Cost/incidents in 105 41 116 181 188 1.132 96 incidents types

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TABLE 3. Costs per incident and equipment types in €1

Agitator 0 5.089 1.193 25 4.762 1.624 8 12.702

Pump 7.614 27.779 70.590 32.560 18.693 60.548 4.201 221.985

Boiler 12.086 19 0 377 10 23.974 0 36.465

Distillation 4.038 1 45 8.251 5.155 29.979 0 47.469 column

Heat 1.494 0 0 36.941 0 101.920 0 140.355 exchanger

Reactor 42.199 1.126 457 59.555 3.974 163.220 0 270.531

Tank 13.839 1.258 538 13.771 0 6.570 60 6.037

Total 81.269 35.273 72.823 151.480 32.593 387.835 4.270 765.544

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TABLE 5. Number of incidents per incident type and specific pump

P-060 1 1 0 4 0 0 0 6

P-061 8 42 0 0 0 9 0 59

P-062 4 1 8 1 0 0 0 14

P-063 0 0 1 0 0 0 0 1

P-064 0 0 0 0 0 0 0 0

P-065 2 2 22 3 1 6 0 36

P-066 1 2 7 0 0 0 0 10

P-067 12 0 5 1 31 0 0 49

P-068 2 0 0 0 0 5 0 7

P-069 0 0 5 0 0 0 0 5

P-070 1 1 5 3 2 5 0 17

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icat

ion

Plan

ned

revi

sion

Nai

led

pum

p

Tota

lTABLE 6. Cost per incident type and specific pump

P-060 109 119 0 533 0 0 0 762

P-061 195 441 0 0 0 2.011 0 2.647

P-062 269 0 2.775 25 0 0 0 3.068

P-063 0 0 364 0 0 0 0 364

P-064 0 0 0 0 0 0 0 0

P-065 41 256 18.274 4.202 479 139 0 23.392

P-066 62 28 2.779 0 0 0 0 2.868

P-067 677 0 2.153 31 1.464 0 0 4.324

P-068 251 0 0 0 0 26 0 278

P-069 0 0 1.604 0 0 0 0 1.604

P-070 201 0 5.791 186 173 21 0 6.372

Equi

pmen

t

Inst

rum

enta

tion

Mag

neto

ther

mic

of

f

Fast

ener

leak

Join

t lea

k

Lubr

icat

ion

Plan

ned

revi

sion

Nai

led

pum

p

Tota

l



Going deep into detail in the management of such reactors, it was concluded that these planned interventions are due to com-pulsory actions related to strict regulations must be performed, so there was little to do in this case.

Cells in Tables 5 and 6 present respectively 22 incidents (yel-low) for pump P-065, for the incident type fastener leak, with the associated cost of 18,274 € (red); with a 831 €/incident ratio, a nonindicated value. When a pump locker is loose, the locker has to be repaired, and this operation is usually very expensive. Thanks to this analysis it was concluded that it is not possible to afford more than 10 incidents per year for this incident type, as otherwise the maintenance profitability is seriously damaged, being reflected in the maintenance department budget.

Thus, the 22 incidents that in this case have to be faced are an excessive value although it is shown in yellow; this situation happens because several pumps with a high failure rate exist and there is little that can be done about it unless a substitution of the whole pump is performed.

As a summary, it has been proved that the results obtained permit finding the root causes that must be reduced to increase the chemical plant efficiency. HP

NOMENCLATURE Itot Total number of incidents I Number of incidents Ctot Total incident cost, € C Incident cost, € CItot Total incident cost ratio, € € Euro CI Incident ratio cost, € i Incident number i j, je Equipment k, ke Incident type l, le Equipment type AI, BI Lower and upper values of the number of incidents per

equipment type AC, BC Lower and upper values of the cost per equipment type AC/I, BC/I Lower and upper values of the cost/incident ratio per

equipment type DI, EI Lower and upper values of the number of incidents per

equipment DC, EC Lower and upper values of the cost per equipment DC/I, EC/I Lower and upper values of the cost/incident ratio per

equipment MTBF Mean-time-between failures MTTR Mean-time-to-repair RCM Reliability-centered-maintenance TPM Total productive maintenance

LITERATURE CITED 1 Bradley, Jones, R., Risk-Based Management: A Reliability Centered Approach,

Gulf Professional Publishing, 1995. 2 Dhillon, B., Engineering Maintenance: A Modern Approach, CRC Press, 2002. 3 Kelly, A., Benchmarking for School Improvement: Practical Guide for Comparing

and Achieving Effectiveness, Routledge, 2001. 4 Levitt, J., The Handbook of Maintenance Management, Industrial Press Inc.

New York, 1997. 5 Souris, J., Maintenace, source of profits, Ed. L’es éditions d’organisation, 1990. 6 Wireman, T., Benchmarking Best Practices in Maintenance Management,

Industrial Press, New York, 2004. 7 Goti, A., Sound-based predictive maintenance: a cost-effective approach, Special

Report on Maintenance and Reliability, Hydrocarbon Processing, vol. 87, no. 5, pp. 37–40, 2008.

8 Juric, Z., “Ingeniería de Planta S.L.,” Seminary on Maintenance and Profitability Ratios (in Spanish), 2004.

9 Amendola, L., “The Theory of Constraints,” Turnaround–Shutdowns Maintenance, Espuela de Plata. Sevilla, 1999.

10 García Garrido, S., Integral Organization and Management of Maintenance (in Spanish), Ed. Díaz de Santos, 2003.

11 Narayan, V., Effective Maintenance Management: Risk and Reliability Strategies for Optimizing Performance, Industrial Press Inc., 2004.

12 Wireman, T., Developing Performance Indicators For Managing Maintenance, Industrial Press Inc., 2005.

13 Campbell, J., and Reyes-Picknell, J., Uptime: Strategies for Excellence in Maintenance Management, Productivity Press, 2006.

14 Tomlingson, P., Effective Maintenance: The Key to Profitability: A Manager’s Guide to Effective Industrial, John Wiley and Sons, 1993.

15 Birolini, A., Reliability Engineering: Theory and Practice, Springer, 2004. 16 Lyonnet, P., Tools of Total Quality, Ed. Chapman & Hall, 2007. 17 Berman, J., “Maximizing Project Value: Defining, Managing, and Measuring

for Optimal Return,” AMACOM, 2007. 18 Gardella, M., Incidents in Chemical Plant Equipment (in Spanish), IGM, nº

49–50, Ed. Alcion, Madrid 2006–2007. 19 August, J., Applied Reliability Centered Maintenance, PennWell Books, 1999. 20 Mobley, R., Root Cause Failure Analysis, Elseiver, 1999. 21 Moubray, J., Reliability-Centered Maintenance, Industrial Press Inc., 2001. 22 Campbell, J., Maintenance Excellence: Optimizing Equipment Life Cycle

Decisions, CRC Press, 2001. 23 Wireman, T., Maintenance Management and Regulatory Compliance Strategies,

Industrial Press Inc., 2003.

Marc Gardella is an industrial engineer doing his PhD in the Polytechnic University of Catalonia (UPC) since 2004. His PhD work is aimed at improving the Reliability Centred Maintenance meth-odology in the petrochemical industry. In addition, Mr. Gardella has worked as maintenance manager in a chemical plant and as a

trainer in a petroleum company.

Xavier Escaler holds a PhD in industrial engineering and is a member of the Department of Fluid Mechanics of the UPC. He teaches courses on fluid mechanics and hydraulic machines. Dr. Escaler simultaneously heads CDIF projects and provides services for companies, including vibration analysis, damage detection

and applying predictive maintenance techniques for turbomachines both online and offline. His main research line is predicting erosive cavitation and the dynamic behaviour of large hydraulic machines.

Aitor Goti holds a PhD in Engineering. He teaches subjects related to project management and operations research in the Engineering School of the University of Mondragon (MU). Dr. Goti has taken part in over 20 research projects supported by private and public funding and written over 40 national and international publications.

Eduard Egusquiza holds a PhD in industrial engineering and is Professor of Fluid Mechanics at the School of Industrial Engineer-ing of Barcelona (ETSEIB) (UPC). Dr. Egusquiza has been secretary of the ‘Hydraulic Machinery and Systems’ section of the International Association of Hydraulic Engineering and Research (IAHR) since

2002. He is a member of the TC-10 Technical Diagnostics Committee (IMEKO) and of the ISO/IEC JWG1 Committee.

TABLE 7. Value ranges for the proposed management ratios

Low Medium High

AI 50 151 > 500

BI 150 500 > 500

AC 10,000 50,000,001 > 100,000

BC 50,000 100,000 > 100,000

AC/I 200 500,001 > 1,000

BC/I 500 1,000 > 1,000

DI 10 16 > 25

EI 15 25 > 25

DC 900 3,000,001 > 6,000

EC 3,000 6,000 > 6,000

AL DENTE



PLANTY SAFETY AND ENVIRONMENT

Designing for pressure safety valves in supercritical serviceUse this rigorous method to prevent over-sizing

R. C. DOANE, S&B Engineers and Constructors Inc., Houston, Texas

P ressure safety valves (PSVs) on vessels containing liquid hydrocarbon that may be blocked in during a fire can relieve a supercritical fluid, if the relieving pressure is higher than

the critical point. The conventional method for calculating an orifice size is presented in API RP-521.1 This method, however, treats all “un-wetted” vessels the same, whether the fluid contained is supercritical, a vapor or a gas. Caution is given in the API text and states that the given equations are based on the physical properties of air and the perfect gas laws with no change in fluid temperature. The reader is cautioned to review these assumptions to “ensure they are appropriate for any particular situation.”

Supercritical fluids are not obedient to the perfect gas laws. Compressibility factors can range from 0.5 to 0.7 and are not con-stant while the vessel is relieving. Also, the fluid temperature is not constant. Fortunately, it can be shown that the API method is con-servative, producing larger orifice areas than required. On the other hand, an over-sized valve has two problems: there is a potential for destructive valve “chatter” and larger PSVs are more expensive.

The method presented adheres to basic thermodynamic prin-ciples, not the perfect gas laws. The resulting orifice areas are significantly smaller than those derived from the API method. Sonic flow through the PSV orifice is taken into account.

Fire case scenario. Fig. 1 illustrates a typical fire case situation for a pressure vessel containing a hydrocarbon liquid. Both the

inlet and outlet lines have a valve capable of being closed, inadver-tently or not. If all the valves are shut, this is considered a “blocked in” condition. The vessel is only 10 ft from grade level. According to the API RP-521 standard, the entire vessel can be exposed to an external fire. The pressure in the drum will rise until the PSV set pressure is reached. At this point, the PSV will start to open. The valve will be fully open at the relieving pressure, normally 21% above the set pressure for a fire case design.

The relieved fluid condition depends on the critical pressure’s relation to the relieving pressure. If the relieving pressure is less than the fluid’s critical pressure, the liquid will boil when the PSV opens. Relieving pressure will continue until the liquid is all vaporized. The temperature will only vary during the relieving process if the fluid is multi-component having a boiling range.

If the relieving pressure is above the critical pressure, the liquid will not boil. The fluid becomes supercritical, having the proper-ties of one phase, somewhere between a liquid and a vapor. The fire will continue to heat the drum and its contents, even if the fluid is composed of only one compound. Eventually the pres-sure will reach the PSV relieving pressure. The PSV will open and relieve a vapor below the critical pressure. Relieving pressure will continue until no more moles of fluid remain in the drum to maintain the pressure.

Vent to process

To flare

10 ft To pump

Typical vesssel subject to fire case study (and possibly supercritical relief).

FIG. 1

Enthalpy

Critical pressure

Criticaltemperature

Relieving pressure

Maximumback-pressure

Criticalpoint

Two-phaseregion

Liquid region

Vaporregion

Line of constant specific volume

Initialcondition

Chokeconditions

Lines ofconstantentropy

Pres

sure

Typical hydrocarbon P-H Diagram (showing path of fluid conditions into the supercritical).

FIG. 2


PLANT SAFETY AND ENVIRONMENT

The path to supercritical. Fig. 2 shows a pressure-enthalpy (P-H diagram) to illustrate the path taken by the fluid from the initial condition to the relieving condition—after the drum is blocked in and a fire starts. The vapor remains in equilibrium as the temperature increases.

The pressure follows the liquid’s vapor pressure up the boundary of the two-phase region to the critical point. If the relieving pressure is above the critical point, the pressure and temperature will con-tinue to increase along the path of constant specific volume, from the critical point to the horizontal relieving pressure line. The fluid must remain at constant volume because, with no fluid relief, both the mass of fluid and the vessel volume remain essentially constant. The distinction between vapor and liquid phases has been lost.

After reaching the relieving pressure, the fluid will continue to be heated by the fire. The pressure must remain the same to avoid over-pressuring the drum. The temperature and required relieving rate will vary as the relieving process continues.

Fig. 2 also shows five points, corresponding to different PSV inlet conditions along the relieving pressure line. These points will be needed to verify location of the condition requiring the largest PSV orifice area. It has been shown that the mass relieving rate, volume relieving rate and maximum orifice area are not necessarily found at the same temperature.3

Also illustrated are four points corresponding to a choked condition at the outlet of the orifice. The velocity through the orifice is sonic for these conditions and the relieving rate must be calculated accordingly. Sonic flow is typical for supercritical relief. The remaining four points, along the back-pressure line, are only needed when the orifice flow is not sonic.

Procedure and calculations. The procedure consists of transcribing property data obtained from a process simulator onto a spreadsheet that calculates relieving rates and required orifice

areas (Table 1). The calculations follow the logic diagram in Fig. 3. The fluid in this example is normal butane. The vessel is assumed to be essentially full, with a small vapor space. Table 2 shows the fluid and vessel data that should be gathered and entered into the spreadsheet.

To calculate the heat transfer rate from a fire, use Eq. 1:1

Q = 21,000 fAe0.18 (1)

It is assumed that Eq. 1, derived for wetted surface areas, is also applicable for supercritical fluids, where the concept of “wetted” becomes nebulous. Any error is on the safe side, since the heat trans-fer rate to a wetted surface is higher than for an unwetted surface.

TABLE 2. Fluid and vessel information gathered and inputted into the spreadsheet

Data required Comment

Vessel exposed area Include both heads

Insulation factor Usually 1.0; see Table 5 in API RP-521 § 3.15

PSV relieving pressure For a fire case, the relieving pressure is 1.21 times the set pressure.

Maximum PSV back pressure The flare system is usually designed to provide a maximum value at each PSV

Fluid mole weight and The process simulator may be needed to calculatecritical properties the critical properties.

TABLE 3. API RP-521 method vs. the rigorous method

Max. orifice Relief OrificeMethod area (in.2) mass rate (lb/hr) velocity (ft/sec)

API RP-521 0.186 14,351 287

Rigorous 0.0651 13,405 950

TABLE 1. Supercritical relief valve sizing example problem—normal butane

Choked Choked Orifice Mass Volume Mass Orifice Enthalpy Entropy Cp/Cv pres flow velocity flux flow flow areaSegment Point T P rho V h s k Pc ? v G Q W Apoints number (F) (psia) (lb/ft3) (ft3/lb) (Btu/lb) (Btu/lb-F) (psia) (ft/sec) (lb/ft2sec) (ft3/hr) (lb/hr) (sq in.)

critical 306 550 10.74 0.0931

1 to 2 1in 424.0 983 10.74 0.0931 –815.8 0.5797 1.522 499.9 yes 953 4,658 1,304 6,374 0.0644

1sonic 359.0 499.9 4.889 0.2045 0.5797 1.295

1subout 200.8 40.0 0.3430 2.9155 –881.7 0.5797

2 to 3 2in 434.0 983 10.19 0.0981 –807.0 0.5896 1.464 508.9 yes 950 9,685 1,315 1,3405 0.0651

2sonic 372.3 508.9 4.775 0.2094 0.5896 1.268

2subout 214.3 40.0 0.3352 2.9833 –875.1 0.5896

3 to 4 3in 444.0 983 9.711 0.1030 –798.6 0.5990 1.415 516.8 yes 949 9,219 1,274 12,371 0.0631

3sonic 385.0 516.8 4.671 0.2141 0.5990 1.246

3subout 227.3 40.0 0.3281 3.0479 –868.6 0.5990

4 to 5 4in 454.0 983 9.293 0.1076 –790.3 0.6081 1.375 523.5 yes 949 8,819 1,250 11,620 0.0620

4sonic 397.4 523.5 4.57 0.2188 0.6081 1.227

4subout 239.8 40.0 0.3216 3.1095 –862.3 0.6081

5in 464 983 8.925 0.1120 –782.2

Vessel diameter (ft): 6 Tnormal 90 FVessel tan-tan (ft): 12 Molecular weight: 58.12 Pnormal 44 psiaAe (exposed area) (sq ft) 304 Relieving pressure (psia) 983 Kd 0.85 (2)f (insulation factor) 1.0 = found by trial Kb 1q (mBTU/hr) 2.283 (5) Back-pressure, Pa (psia) 40 Kc 1



Using a simulator program, define the first point 1in, on the relieving pressure line. The specific volume must equal the fluid’s critical volume. Knowing P and V, find T by trial. This is equiva-lent to drawing a line of constant specific volume from the critical point to the horizontal relieving pressure line. Record h, s and k for point 1in.

Move to the next point by incrementing T by 10°F. A higher accuracy can be achieved with smaller temperature increments, but 10o is sufficient for this example. Knowing P and T, use the simulator to find V, h, s and k for point 2in. Repeat the temperature increments until all five PSV inlet pressures have been defined.

For each point it must be known whether or not the flow through the orifice is sonic. The choke pressure at the orifice is calculated from Eq. 2.4

Pch = Pin[2 / (1+ kin )](kin /(kin 1) (2)

Compare Pch with Pback . If the choke pressure is higher than the back-pressure, sonic flow exists at the orifice.

Sonic flow. Since the change in condition from upstream of the orifice to the orifice itself is adiabatic and almost reversible, the change is virtually isentropic. We can determine the other properties for isonic by keeping s the same as for the inlet point, iin and setting P = Pch . The temperature is found by trial. This is equivalent to drawing an isentropic line from point iin to Pch on the P-H diagram. Record ksonic and V.

The sonic velocity is found using Eq. 3:4

vson = kson gc (R /M )T (3)

The orifice area equation will need a value for the mass flux, G, found from the velocity and specific volume:

G = vson /Vson (4)

Subsonic flow. For subsonic flow, the procedure and equa-tions are similar to the sonic case. At constant s and with P = Pback , define point isubout . The temperature is found by trial. This is equivalent to drawing an isentropic line from iin to the back-

Calculate the heat transfer rate fromthe fire to the vessel:

q = 21,000 f Ae-0.18

Using a process simulator, find point 1in ,at the relieving pressure and the criticalvolume.

Determine: Vessel exposed areaVessel insulation factorPSV relieving pressureMaximum PSV back-pressure

Assume: Adequate drainage existsunder the vessel

Fluid critical properties (pressure,temperature and specific volume)Fluid molecular weight

Record h, s and k for point 1

Increment T by 10°F

Let i = point number 1

Using the simulator, find V, h, s and k forpoint i. Maintain P at the relieving pressure.The temperature is found by trial.

NoYesi = 5 ?

Next pointi = i + 1

Back to first pointi = 1

Calculate the choke pressure for point iin :Pch = Pin [2/(1 + kin ](kin / (kin – 1)

Flow throughthe PSV orificeis sonic.

Flow throughthe PSV orificeis subsonic.

At constant s and with P = Pch ,find point isonic . The temperatureis found by trial. Record V and k.

At constant s and with P = Pback ,find point isubout . The temperatureis found by trial. Record V and h.

Calculate the fluid velocitythrough the orifice:

vson = kson gc (R/M) T

Calculate the fluid velocitythrough the orifice:vsub = 2(hin– hsubout)gc (778)

Calculate the fluid mass fluxthrough the orifice:

G = vson /vson

Calculate the fluid volumetric flow:Q = q(Vin,i+1 – Vin,i ) /(hin,i+1 – hin,i )

Calculate the mass flow:W = G/V

Calculate the required orifice area:

Select the largest requiredorifice area.

A = 0.04 W/ (Kd Kb Kc G)

Next pointi = i + 1

G = vsub /Vsub

Calculate the fluid mass fluxthrough the orifice:

NoYesIs Pch ≥ Pback ?

NoYesi = ?

Logic diagram for supercritical relief valve sizing.FIG. 3




pressure line on the P-H diagram. Record h and V.The subsonic velocity can be found using Eq. 5, derived from

the first law of thermodynamics, neglecting the relatively low velocity upstream of the orifice.4

vsub = 2(hin hsubout )gc (778) (5)

The mass flux equation for the subsonic case is very similar to that of the sonic case. Note that the subscripts in Eq. 6 are not the same as in Eq. 4.

G = vsub /Vsub (6)

Perform the velocity and mass flux calculations, including the sonic/subsonic flow analysis, for each point 1 through 4.

Orifice sizing. After calculating G for each of points 1 through 4, the fluid volumetric flow is found using Eq. 7.

Q = q(Vin,i+1 Vin,i ) / (hin,i+1 hin,i ) (7)

This is an approximation to the differential equation resulting from a heat and mass balance around the vessel, with constant relieving pressure:3

Q = q(dV /dh)p (8)

Knowing Q and G, the mass relieving flow and required orifice area are found from Eqs. 9 and 10 as follows:2

W = G /V (9)

A = 0.04W /(K d KbK cG ) (10)

The PSV discharge coefficient is assumed to be 0.85, as rec-ommended in the API RP-521 standard for preliminary sizing when vendor data is unavailable. The back pressure correction is normally 1 for supercritical relief, since the relieving pressure is so high. The combination factor is also 1, since a rupture disk is not included in this example.

When the spreadsheet is complete, there are four values for the orifice area to choose from. Simply select the maximum value for the design. In the example spreadsheet, the area for point 2, 0.0651 in.2, is the largest of the four. It may be necessary to define more points and expand the spreadsheet if the maximum area occurs at point 4 or beyond.

Comparison with the conventional method. Table 3 compares the results of the conventional method in the API RP-521 § 3.15 standard with the more rigorous method pre-sented. The results of both methods are based on the previous example problem. For the conventional method, the relieving

temperature is the same as for the rigorous method. Using the ideal gas law to find the relieving temperature, as suggested in the API RP-521 standard, may lead to unrealistic results.

It is readily seen that the conventional method in the API RP-521 standard produces conservative results for relief of supercritical fluids. The orifice design size is about three times the area calculated using the more rigorous method. The mass rate is higher, but the orifice velocity is far below sonic.

Conclusion. PSV orifice areas calculated using the method in the API RP-521 standard when relieving supercritical fluids are conservatively large. Orifices sized using a more rigorous approach, based on thermodynamic principles, can be signifi-cantly smaller, resulting in cost savings. HP

LITERATURE CITED1 Guide for pressure-relieving and depressuring systems, American Petroleum

Institute, API RP 521, Fourth Edition, March 1997.2 Sizing, selection and installation of pressure-relieving devices in refineries,

American Petroleum Institute, API RP 521, Seventh Edition, January, 2000.3 Ouderkirk, R., “Rigorously size relief valves for supercritical fluids,” CEP,

August 2002, pp. 34–43.4 Weber, H. C. and H. P. Meissner, Thermodynamics for Chemical Engineers,

Second Edition, New York, 1963.

NOMENCLATURE P Fluid pressure, psia T Fluid temperature, degrees Rankine rho Fluid density, lb/ft3

V Fluid specific volume, ft3/lb v Fluid velocity, ft/sec h Fluid specific enthalpy, Btu/lb s Fluid specific entropy, Btu/lb-°F k Specific heat ratio, Cp/Cv G Fluid mass flux, lb/ft2-sec W Fluid mass flow, lb/hr A PSV orifice area, in.2 Ae Surface area of vessel exposed to the fire, ft2

i Fluid point number on the relieving pressure line gc Newton’s law conversion factor, lbm-ft/lbf–sec2

M Fluid molecular weight Kd PSV discharge coefficient Kb PSV back pressure correction factor Kc PSV combination correction factor Q Fluid volumetric flow rate, ft3/hr q Heat transfer rate from external fire to the fluid,

millions of BTU/hr f Vessel insulation factor

R Gas constant, 1,546 lbs ftlbmol °R

SUBSCRIPTSin Fluid data at PSV inlet

sonic or son Fluid sonic velocity data at the PSV orifice outletsubout Subsonic fluid data at the outlet of the PSV orifice

norm Normal fluid condition ch Choke flow condition

Richard Doane recently retired following 37 years experience in engineering and construction, plant start-up, and operation supervision. When this article was written, Mr. Doane was a senior process engineer with S&B Engineers and Constructors in Houston, Texas. He holds BS and MS degrees in chemical engineering from

Northeastern University in Boston, Massachusetts and an MS degree in accounting from the University of Houston in Clear Lake, Texas.

■ The PSV discharge coefficient is

assumed to be 0.85, as recommended in

the API RP-521 standard for preliminary

sizing when vendor data is unavailable.

The back pressure is normally 1 for

supercritical relief, since the relieving

pressure is so high.

SEE YOU IN ROMESubmit your technical paper and be part of this exciting, market-leading conference.

21–23 June 2010 Sheraton Roma Hotel Rome, Italy

REFININGHosted by

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Topics for consideration include, but are not limited to: • “Deep” conversions and heavy-oil technologies• Aging equipment and maintenance• Advanced catalyst/licensed technology developments• Competing with refi ned-product imports• Energy effi ciency• Switch to diesel: impact on climate change• New carbon and CO2 management technologies• Renewables and biofuels issues• Energy supplies• Next-generation clean fuels• Environment• Safety

For additional information on the technical program, please contact Hadley McClellan at +1 (713) 520-4475 or [email protected].

For information on sponsorship and exhibiting opportunities, please contact Hadley McClellan or your Hydrocarbon Processing representative (see page 81 to fi nd your local representative).

PIPING


C alculating the “ƒ” factor is an essential step with piping sys-tems for laminar and turbulent flows in smooth or rough pipes. The “Moody diagram” is the most widely accepted

graphical method for determining ƒ factor but there are also many equations for this purpose. Eqs. 1, 2 and 3 are used for ƒ calcula-tion for “laminar flow in pipes,” “turbulent flow in rough pipes” and “turbulent flow in smooth pipes” respectively.

f =64Re

(1)Re

1f

= 2 log10/ D

3.7+

2.51Re f

(2)

1f

= 4 log10 Re f( ) 0.4 (3)

The last two equations are very accurate but have the disad-vantage of being implicit in ƒ that need an iterative estimation method hence, considerable effort has been expended to introduce an explicit equation to determine ƒ and simplify the calculation for turbulent flow in rough and smooth pipes but this work just focuses on Eq. 3 to introduce a new explicit friction factor equa-tion for turbulent flow in smooth pipes.

In 1913, Blasius proposed Eq. 4 that is valid for the range 3,000 < Re < 105. Drew, et al. also introduced Eq. 5 that is good for the range 3,000 < Re < 3×106 in 1932 but recently Goudar and Sonnad1 recommended a very accu-rate equation (Eq. 6) that is valid over the entire range of turbulent flow regime in pipes 4,000 < Re < 108 and com-pared the range of error in ƒ, % for nine explicit equations.

f = 0.0791Re 0.25 (4)

f = 0.0014 + 0.125Re 0.32 (5)

1

f= aW Re

ae b

a(6)

where:

a = 4/ln(10)b = 0.4W (x) = ln x

ln x(ln x)h

h = exp 1.1244919897778080.4225028202459761+ (ln(x))

Proposed explicit equation for ƒ. To represent the new equation, the first step is deriving the ƒ factor from Eq. 3 for 3,000 points by the iterative method over 4,000 < Re < 108 and then accurate and uniform relations are obtained between Re and ƒ for five regions by data fitting and the final form Eq. 7 is derived by selecting an average value for coefficients (Fig. 1).

f =

1.5114978x10 4+

0.59501296(ln(Re))

+

2.3501318(ln(Re))2

3.3218937(ln(Re ))3

2

(7)

New explicit friction factor equation for turbulent flow in smooth pipesA simple, explicit and high-accuracy equation is presented

A. SASAN-AMIRI, Bouali Sina Petrochemical Company, Khuzestan, Iran

0.000103

“f”

fact

or

Re104 105 106 107 108 1E+09

0.0010.0020.0030.0040.0050.0060.0070.0080.0090.0100.011

Friction factor from Eq. 3

ƒ factor derived from Eq. 3.FIG. 1

TABLE 1. Max., min. and average error in ƒ percent for 99,997 points

Equation name Eq. 7 Sonnad Nikuradse Blasius McAdams Bhatti Drew, et al.

Average -0.000243024 0.006791315 0.209029792 -39.84423026 -16.77314702 -9.155504298 11.58937747

Min. -0.000752998 0.006131462 -14.4272666 -46.75906704 -22.22733063 -18.85983705 -0.484544169

Max. -0.000208474 0.011714088 1.139429761 2.7564055 2.419757397 2.338352892 17.40457569


PIPING

Sonnad and Goudar have compared the range of error in ƒ per-cent for nine equations and Fig. 2 shows the mentioned compari-son for five equations that vary in a wide range and Fig. 3 compares the mentioned error for Sonnad and Goudar and Eq. 7. Table 1 also represents the average error in ƒ percent for 99,997 points in the range 4,000 < Re < 108 by the interval 1,000 and max. and min. values. Hence, the recommended equation seems to be proper to calculate the ƒ factor and estimate a more reliable and accurate value in smooth pipes and the turbulent flow regime. HP

NOMENCLATURE ƒ = Friction factor �/D = Pipe roughness Re = Reynolds number W = Lambert W function

LITERATURE CITED 1 Sonnad, J. R. and C. T. Goudar, “Explicit friction factor correlation for pipe

flow analysis,” Hydrocarbon Processing, June 2005, pp. 103–105. 2 Holland, F. A. and Dr. Dragg, R., “Fluid Flow for Chemical Engineers,”

Edward Arnold publishing, Great Britain, 1995, pp. 71–75.

103

Re104 105 106 107 108 1E+09

-0.0005

0.0015

0.0035

0.0055

0.0075

0.0095

0.0115

0.0135

“f”

fact

or

Sonnad, e%New eq., e%

Error in ƒ percent for Sonnad and Goudar and the new equations.

FIG. 3

Amir Sasan-Amiri works in the paraxylene unit in the pro-cess engineering department of Bouali Sina Petrochemical Co. as a process senior engineer. He holds a BSc degee in chemical engineering from Arak Azad University, Iran, and an MSc degree in construction management from Grenoble University in France. Mr.

Sasan-Amiri’s interests include fluid mechanics, heat transfer, separation processes and process simulation.

Blasius, e%McAdams, e%Bhatti, e%Drew, et al., e%Nikuradse, e%

-50

-40

-30

-20

-10

0

10

20

Erro

r in “f”

,%

103

Re104 105 106 107 108 1E+09

Error in ƒ percent for five former explicit equations.FIG. 2

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INSTRUMENTATION

Implement a constrained optimal control in a conventional level controller—Part 1Novel tuning method enables a conventional PI controller to explicitly handle the three important operational constraints of a liquid level loop in an optimal manner as well as copes with a broad range of level control from tight to averaging control

M. LEE, Yeungnam University, Kyongsan, Korea; and J. SHIN and J. LEE, LG Chem., Daejeon, Korea

D ue to the importance of liquid level loops for success-ful plant operation, extensive research has been done to enhance their control performance.1–9 A level controller

is often required to not only minimize level deviation but also to provide nonaggressive control action. Controlling outflow behavior is as crucial as controlling the liquid level itself, especially when the outflow is situated upstream of a critical unit such as a reactor or a separation column. Furthermore, a liquid level loop generally has three important operational constraints: the rate of change in the outflow should be kept below an allowable limit for smooth control action, the level deviation should be within an allowable inventory limit and the outflow overshoot should also be within an allowable limit to avoid severe overflow and downstream oscillations.

For these reasons, level control problems can be considered as typical constrained optimal control problems. In spite of its industrial importance, the constrained optimal control strategy has rarely been employed in level loops because of the lack of a proper design method to implement it in the conventional PI con-troller. Recently, a novel constrained optimization-based approach has been proposed to cope with the constrained optimal control of a level loop in a unified manner.10,11 In this article, we introduce a practical PI controller tuning method for optimal level control by extending this approach to explicitly handle the three typical constraints previously mentioned.

Optimal level control formulation. The liquid level loop in Fig. 1 can be simply described by the following equation:

H (s ) =

1As

Qi (s )1As

Qo (s) (1)

where:

Qo (s) = K L 1+

1

I sH (s) H set (s )( ) (2)

and

K L = K cQovmax

Hspan

(3)

The closed-loop transfer functions for the regulatory problem are then:

H (s ) =H I

As

H I s2+ I s +1

Qi (s ) (4)

Qo (s) =I s +1

H I s2+ I s +1

Qi (s ) (5)

where:

H =A

K L

=V

K c

(6)

and

V =

A Hspan

Qovmax

=VT

Qovmax

(7)

Qi

Qo

LT

LC

Typical level control loop.FIG. 1


INSTRUMENTATION

The damping factor of the above closed-loop characteristic equation is expressed as:

=

12

I

H

(8)

The control objective is to minimize both the rate of change in the outflow and the level deviation against the variation of the inflow, which is the main concern in a level loop. The level loop should also be operated under the following three operational constraints or specifications: a maximum allowable rate of outflow change, Q'o max ; maximum allowable level deviation, Hmax ; and a maximum allowable outflow, Qo max, to a given inflow variation.

Therefore, the optimal control problem of a level loop can be formulated as:

min =H (t )Hspan

2

0dt +(1 )

Q 'o (t )Q 'ov max

2

0dt (9a

subject to:

Q 'o (t ) Q 'o max (9b)

H (t ) Hmax (9c)

Qo (t ) Qo max (9d)

Consider a regulatory problem with regard to a step change of magnitude �Qi in the inflow (i.e., Qi(s)=�Qi /s). Through some mathematical manipulations, the optimal control problem defined by Eqs. 9a–d can be converted into the following con-strained optimization problem expressed in terms of �H and � (see the Appendix for the details of its derivation):

min = ( H , ) = H

3 2+

1

H

1+1

4 2(10a)

subject to:

H + hh( ) 0 (10b)

Hg

g ( )0 (10c)

f ( ) f 0 (10d)

where:

= 2Qi

A Hspan

2

; =1

2Qi

Q 'ovmax

2

;

h =Qi

Q 'o max

; g =AHmax

Qi

; f =Qo max

Qi

(11)

where h(�), g(�) and f (�) are given by Eqs. (A9), (A13) and (A6) in the appendix, respectively.

Optimal PI controller design. Applying the Lagrangian multiplier12 converts the constrained problem in Eqs. 10a–d into the equivalent unconstrained problem:

min L( H , , 1, 2 , 3, 1, 2 , 3 )

=3H

2+

1

H

1+1

4 2+ 1( H hh( ) 1

2)+

2g

H

g ( ) 22

+ 3( f f ( ) 32) (12)

If γh h(ζ†)≤ τ†H ≤

If τ*fH ≤ τvl

H

If ζmin ≤ ζ*h

≤ ζ vr

If ζmin ≤ ζ*g

≤ ζ vr

If ζ*g > ζ vr

If ζ*h > ζ vr

If τ†H ≤ γh h(ζ†)

If τ†H >

Kc = =; τ IVT

If τvuH

≥ τ*f

H ≥ τvlH

If τ*fH

> τvu

H

Global optimum

(ζ†, τ†H )

(ζmin, τvlH )

(ζmin, τ*fH )

(ζ*h , τ*hH )

(ζ*g , τ*gH )

(ζ vr , τvrH )

(ζ vr , τvrH )

(ζopt , τoptH )

= 4(ζopt)2 τopt

H

(ζmin , τvu

H )

(ζmin , τvl

H )

(ζmin , τvl

H )

(ζmin , τ*f

H )

Y

Y

Y

Y

Y

Y

Y

Y

Y

Y

N

N

N

N

N

N

N

N

N

N

Yg(ζ†)

γg

g(ζ†)

γg

If ζmin ≤ ζ†

Qomax τoptH

Flow chart for finding the global optimum and optimal PI parameters.

FIG. 3

Case A Case B

Case C

Case E Case F Case G

Case D

H = g/g( )

H

H = hh( )

H

HH H H

H

f = f( )

( +H

+)

( *h, H*h)

( vr, Hvr)( *g, H

*g)

( vl, Hvl)

( vu, Hvu)( *f, H

*f)

Typical contours and constraints for the seven possible cases with respect to the global optimum location. The shaded part denotes the feasible region.

FIG. 2

Proof only. Copyrighted material. May not be reproduced without permission.

Proof only. Copyrighted material.May not be reproduced without permission.

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INSTRUMENTATION

where � 1 is a Lagrange multiplier (� 1 ^0) and �i is a slack variable.

The necessary conditions for a stationary point are:

L

H

=3 2H

2 12H

1+1

4 2+ 1

2 g2H

=0 (13a)

L= 2 3

H 21

H3 2 g '( ) 3 f '( )=0 (13b)

L

1= H hh( ) 1

2= 0 (13c)

L

2=

g

H

g( ) 22

= 0 (13d)

L

3= f f ( ) 3

2= 0 (13e)

L

1

= 2 1 1 = 0; L

2

= 2 2 2 = 0;

L

3= 2 3 3 = 0 (13f )

The simultaneous solutions of Eqs. 13a–f for various combina-tions of � i=0, � i�0, �i=0 and �i�0 are associated with the cor-responding optimum cases. Fig. 2 shows the seven possible cases with respect to the global optimum location of the optimization problem in Eqs. 10a–d. As depicted in Fig. 2, the global optimum can be located in the interior of the three constraints (case A), on the boundary of one constraint (cases C, B and E) or on the vertex formed by two constraints (cases D, F and G). The conditions associated with these seven possible cases can be evaluated by investigating the geometrical characteristics of the contours and constraints shown in Fig. 2 and are summarized in Table 1.

For example, case A corresponds to the situation where �1= �2=�3=0 in Eq. 12.

This case is likely to occur when the three specifications, Q'o max , Hmax and Q'o max are mild (i.e., have large values). In particular, case A happens when �min ^ �† and

hh( † ) †H

g

g( † ) .In this case, the extreme point (�†, �†

H) in the interior of the three constraints is the global optimum. The global optimum (� †

, � †H) is calculated from Eqs. 13a–b as given in Table 1:

†=

1

2 and †

H =

14

Once the global optimum of (�, �H) is evaluated for a given specification set, the corresponding optimal PI parameters can be directly calculated from Eqs. 6, 7 and 8 as follows:

KC =VT

Qov max H

; I = 4 2H (14)

The shortcut procedure for finding the global optimum and PI parameters is illustrated in Fig. 3. Since Qo max is only a func-tion of � for a given �Qi, setting the value of Qo max is equivalent to setting that of the minimum allowable damping factor, � min. Furthermore, it is clear that � *f, � vu and � vl are equal to � min. As seen in Table 1, most of the equations employed for finding the optimal � are expressed in their implicit forms. However, cal-culating the optimal � can be easily achieved by using a simple root-finding method.

It should be noted that when �h<�g , no vertex point is formed by

H =g

g( )and �H =�h

h(�). This situation is likely to occur when the specification Q'o max and/or Hmax are mildly set with relatively large values. In this case, it should be noted that case D does not exist and the value of �vr can be simply considered as extremely large for evaluating the conditions in Table 1.

Effect of weighting factor. The weighting factor, w, is a crucial parameter to adjust the control performance and robust-ness. When a larger w is chosen, the optimal control performance measure is mainly determined by the level response. Therefore, the PI controller yields a tighter level response, which corresponds to “tight level control,” and the response is likely constrained by Q'o max . When a smaller w is used, the performance measure is mainly weighted by the rate of change in the outflow. The control-ler gives a smoother control action, i.e., “averaging level control” and the response is likely constrained by Hmax.

Constraint set feasibility. It is often desirable to control a level loop on the tightest possible constraint set. However, since all three specifications are interrelated, they cannot be selected arbitrarily or independently. Therefore, the constraint set should be determined not only by considering the process requirement but also by satisfying the feasibility.

Remark 1. For any given Q'o max (or Hmax), the tightest avail-able Hmax (or Q'o max ) always occurs at �t = 0.4040 and thus satis-fies11

HmaxQ 'o max = 0.5206( Qi2 / A) (15)

A g i v e n ( Q ' o m a x , H m a x ) s e t i s f e a s i b l e i f HmaxQ 'o max 0.5206( Qi

2 / A). Otherwise, the (Q'o max , Hmax) set is infeasible.

if ζmin ≤ ζ vr

if γh ≥ γg

Feasible (Q′omax , Hmax , Qomax)

Given (Q′omax , Hmax , Qomax)

Increase Qomax

Increase (Q′omax, Hmax)

If HmaxQ'omax ≥ 0.5206 (∆Q2i/A)

Infeasible

Infeasible

Y

Y

Y

N

N

N

Feasibility check and design of a constraint set.FIG. 4

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INSTRUMENTATION

Remark 2. Qo max can be specified only between �Qi and 2�Qi . Any (Q'o max , Qo max) and (Hmax , Qo max) set is feasible with this available Qo max . The tight (Q'omax , Qo max) (or (Hmax , Qo max)) specification set requires the mild Hmax (or Q'o max ) specification for it to be feasible.

Fig. 4 illustrates the overall procedure for checking the fea-

sibility of a given constraint set and designing a feasible con-straint set.

Part 2 of this article will be published in February and dis-cuss PI controller design for tight constraint control and provide some examples.

TABLE 1. Conditions associated with and calculation of global optimums for the constrained optimization problem in Eqs. 10

Lagrangian Typical Global optimum Global optimumCase parameter specification Condition and its location calculation

A� 1=� 2

=� 3=0Mild Q ’o max,Mild Hmax,Mild Qo max

min† and hh( † ) †

Hg

g ( †)

( † , †H )

In the interiorof the constraint set

† =

1

2; †

H =

14

B�1=� 2

=� 3=0Tight Q ’o max,

Mild Hmax,Mild Qo max

min*h vr and †

H hh( † )

( *h , *hH )

On H = hh( )*h

=12

†H

hh( *h )

*hH = hh( *h )

C�2=� 1

=� 3=0Mild Q ’o max,Tight Hmax,Mild Qo max

min* g vr and †

Hg

g( † )

( * g , * gH )

On H =g

g ( )

F ( * g ) = 0

* gH =

g*

D �1= �2

=0

Tight Q'o max,Tight Hmax,Mild Qo max

*h vr and †H hh( † )

or * g vr and †H

g

g ( † )

( vr , vrH )

On the vertex vr by

H =g

g( ) and H = hh( )

g( vr )h( vr ) =g

h

vrH = hh( vr )

E w1=w2

= � 3=0

Mild Q'o max,Mild Hmax,Tight Qo max

min >† and vl

H <* fH <

vuH

( min , * fH )

On f = f ( ), i.e., = min

f = f ( min )

* fH =

1+ 4 2min

12 4min

14

F �1=�3

=0

Mild Q ’o max,Tight Hmax,Tight Qo max

[ min >† and * f

HvuH ]

or †min

* g and †H

g

g ( † )

( min , vuH )

On the vertex vu by

f = f ( ) and H =g

g ( )

f = f ( min )

vuH =

g

g( min )

G�2=�3

=0Tight Q ’o max,

Mild Hmax,Tight Qo max

[ min >† and * f

HvlH ]

or [ †min

*h and †H hh( † )]

( min , vlH )

On the vertex vl by

f = f ( ) and H = hh( )

f = f ( min )vlH = hh( min )

• If �h<�g, the vertex vr or case D is not available and set �vr by an infinite or extremely large values.

• F ( * g ) is 2 3g

* g g ( * g )2 g

g 5( * g )( * g )3

3 3g ( * g )2

g

g 4( * g ) 1+1

4( * g )2g '( * g )

ENGINEERING CASE HISTORIES


Vertical pump vibrations are usually written up by the operator as a motor vibration problem. It has been the writer’s experience that 80% of the time it wasn’t the motor vibrating at all. There are many causes for vibration problems (Fig. 1), but the first observation is usually made on the motor.

Fig. 2 shows another reason why the motor can be reported as the vibration source. With only one measurement on the motor the value would be four mils. At 3,600 cpm, this would appear very rough. However, when data are taken on the verti-cal as shown, only one mil of vibration is on the motor, and none is on the foundation. All of the vibratory motion is taking place through the “I” beam structure. If this was a new installation, filling the structure with grout material could be required. However, if it is an old installation, loose anchor bolts may be the cause.

Shutting the motor down and noticing how the system responds can be productive. Even with no vibration-monitoring equip-ment available, if the vibration disappears immediately when the power is removed this can indicate an electrical problem.

A “shudder” or vibration level increase and then decrease on shut down can reveal

a resonance problem. Try to identify an external source of the vibration by repeat-ing the startup and shut down, if safety isn’t a concern.

A vibration level that drops as the sys-tem coasts down can signal several prob-lems. Bent shafts, bad couplings or fouled impellers all cause imbalance forces that are reduced as the speed is reduced and come down as the square of the speed.1

With horizontal motors locked out, the motor and driven device can be rotated by hand. A heavy spot while turning could indicate misalignment.

Sometimes corrections haven’t been made for thermal misalignment. The motor or driven equipment is supported in such a way that if the machines are not offset during cold alignment they will be out of alignment and vibrating when at operating temperature. When the hot alignment condition is not considered an indication of this is that the machine runs smoothly when first started but vibrates when hot. When a machine vibrates when

it is cold but smoothes out when at operat-ing temperature, the hot corrections were probably made.

Many times when there is motor vibra-tion, usually on smaller motors, a “soft foot” can be the problem. This occurs when one of the motor feet pulls down more than the rest. It is generally thought that this causes internal misalignment which can result in vibration. When the suspect bolt is loosened the vibration drops sig-nificantly. Shimming of the “soft foot” is usually the remedy. The motor shouldn’t be operated with the loose bolt, even if it runs smoother.

At one time the writer was on the plat-form with a 7,000 hp motor with vibration problems. As he contemplated the cause and leaned against the air intake filter screen, the vibration stopped. The cause was local resonance of a loose screen and shows the importance of a walk around.

There are many other causes of motor problems,2 however, a few rather unsophis-ticated checks may allow the plant special-ist to save the time and the expense of an extended outage. HP

LITERATURE CITED 1 Sofronas, A., Analytical Troubleshooting of Process

Machinery and Pressure Vessels: Including Real-World Case Studies, (p. 35), ISBN: 0-471-73211-7, John Wiley & Sons.

2 Bloch, H. P. , Geitner, F. K., Machinery Failure Analysis and Troubleshooting, (p.343), ISBN 0-88415-662-1, Gulf Publishing Co.

Case 54: Is it motor vibrationor some other cause?It’s not always the motor causing the vibration

T. SOFRONAS, Consulting Engineer, Houston, Texas

Unbalance rotor, bearings

Locked, unbalanced,misaligned coupling Loose boltsOil-soaked grout

Bent or misaligned shaft

Imbalanced, corroded orfouled impellers

Bushing wear

System resonance

NPSH problem plugged screen

Loose anchors

Electrical problem

Vertical pump vibration reported as a vibrating motor problem.

FIG. 1

0 1 2 3 4mils p-p

Motor

Foundation

Structure

Displacement

3,600 rpm

Motor vibration shown as problem with single measurement.

FIG. 2

Dr. Tony Sofronas, P.E., was worldwide lead mechanical engineer for ExxonMobil before his retirement. The case studies are from companies the writer has consulted for. Informa-

tion on his books, seminars and consulting are available at the Web site http://www.mechanicalengineeringhelp.com.


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IL, LA, MO, OK, TXJosh Mayer5930 Royal Lane, Suite 201, Dallas, TX 75230Phone: +1 (972) 816-6745, Fax: +1 (972) 767-4442E-mail: [email protected]

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Merrie Lynch20 Park Plaza, Suite 517, Boston, MA 02116Phone: +1 (617) 357-8190, Fax: +1 (617) 357-8194Mobile: +1 (617) 594-4943E-mail: [email protected]

SALES OFFICES—EUROPE

FRANCE, GREECE, NORTH AFRICA, MIDDLE EAST, SPAIN, PORTUGAL, SOUTHERN BELGIUM,LUXEMBOURG, SWITZERLAND, GERMANY,AUSTRIA, TURKEY

Catherine Watkins

30 rue Paul Vaillant Couturier78114 Magny-les-Hameaux, FranceTél.: +33 (0)1 30 47 92 51, Fax: +33 (0)1 30 47 92 40E-mail: [email protected]

ITALY, EASTERN EUROPEFabio Potestá

Mediapoint & Communications SRLCorte Lambruschini - Corso Buenos Aires, 8 5° Piano - Interno 7 16129 Genova - Italy Phone: +39 (010) 570-4948, Fax: +39 (010) 553-0088E-mail: [email protected]

RUSSIA/FSULilia FedotovaAnik International & Co. Ltd.10/2 Build. 1,B. Kharitonyevskii Lane103062 Moscow, RussiaPhone: +7 (495) 628-10-333E-mail: [email protected]

UNITED KINGDOM/SCANDINAVIA, NORTHERN BELGIUM, THE NETHERLANDS

Peter Gilmore

57 Keyes HouseDolphin SquareLondon SW1V 3NAUnited KingdomPhone: +44 (0) 20 7834 5559, Fax: +44 (0) 20 7834 0600E-mail: [email protected]

SALES OFFICES—OTHER AREAS

AUSTRALIA – PerthBrian Arnold

Phone: +61 (8) 9332-9839, Fax: +61 (8) 9313-6442E-mail: [email protected]

BRAZIL – São PauloAlfred BilykBrazmedia Rua General Jardim, 633 Cj 61 01223 011 São Paulo SP, Brazil Phone: +55 (11) 3237-3269Fax: +55 (11) 3237-3269 E-mail: [email protected]

JAPAN – TokyoYoshinori Ikeda

Pacific Business Inc.Phone: +81 (3) 3661-6138, Fax: +81 (3) 3661-6139E-mail: [email protected]

INDONESIA, MALAYSIA, SINGAPORE, THAILANDPeggy Thay

Publicitas Major Media (S) Pte LtdPhone: +65 6836-2272, Fax: +65 6297-7302E-mail: [email protected]

KOREA – SeoulJoong Hyon Kwon & JES MEDIA, INC.

Phone: +82 (2) 481-3411, FAX: +82 (2) 481-3414E-mail: [email protected]

PAKISTAN – KarachiS. E. Ahmed

Intermedia CommunicationsKarachi-74700, PakistanPhone: +92 (21) 663-4795, Fax: +92 (21) 663-4795

DATA PRODUCTS AND CLASSIFIED SALESLee NicholsPhone: +1 (713) 525-4626, Fax: +1 (713) 525-4631E-mail: [email protected]

REPRINTSPhone: +1 (713) 525-4633E-mail: [email protected]

W E B C A S TH y d r o c a r b o n P r o c e s s i n g . c o m

Live Event • Thursday, 21 January 2010 • 10 a.m. CST | 11 a.m. EST

For the fi rst time ever, the editors of Hydrocarbon Processing will present the fi ndings from their annual forecast during an interactive webcast.

Join the editors of Hydrocarbon Processing as they explore the outlook for the downstream industry for 2010. During the hour-long event, the editors will present projections for capital, maintenance and operating expenditures by the refi ning, petrochemical and gas processing industries in 2010 as discussed during the December Industry Forecast Forum. The editors will focus on the economic, environmental and industry trends for the year ahead.

Be a part of this exclusive event.

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HPI Outlook 2010


ABB Automation

Technologies Division . . . . . 42 (69)www.info.hotims.com/29415-69

Alstom Power, Inc. . . . . . . . . . 27 (156)www.info.hotims.com/29415-156

Axens . . . . . . . . . . . . . . . . . . 84 (53)www.info.hotims.com/29415-53

BASF Catalysts LLC . . . . . . . . 51 (75)www.info.hotims.com/29415-75

Cameron . . . . . . . . . . . . . . . . . 2 (55)www.info.hotims.com/29415-55

CB&I . . . . . . . . . . . . . . . . . . . . 8 (98)www.info.hotims.com/29415-98

CB&I . . . . . . . . . . . . . . . . . . . 66 (68)www.info.hotims.com/29415-68

Chas. S. Lewis & Co., Inc. . . . . 36 (67)www.info.hotims.com/29415-67

Emerson Process Mgmt

Delta V . . . . . . . . . . . . . . . . 28 (92)www.info.hotims.com/29415-92

Emirates . . . . . . . . . . . . . . . . 16 (85)www.info.hotims.com/29415-85

Fisher Controls . . . . . . . . . . . 12 (84)www.info.hotims.com/29415-84

Flexitallic LP . . . . . . . . . . . . . . 5 (93)www.info.hotims.com/29415-93

Gas Technology Products LLC . 26 (59)www.info.hotims.com/29415-59

Gulf Publishing Company

Construction Boxscore . . . . . 75

Events, IRC . . . . . . . . . . . . . 68

HPI Marketdata Book . . . . . 73

Products . . . . . . . . . . . . . . . 58 (159)

www.info.hotims.com/29415-159

Software . . . . . . . . . . . . . . . 70

Webcast . . . . . . . . . . . . . . . 80 (163)


Hoerbiger . . . . . . . . . . . . . 20-21 (152)


HPI Marketplace . . . . . . . . 78-79

Hytorc . . . . . . . . . . . . . . . . . . 14 (91)


Idrojet . . . . . . . . . . . . . . . . . . 27 (155)


Inpro / Seal Company . . . . . . . 6 (78)


Kobe Steel Ltd . . . . . . . . . . . . 22 (103)


LA Turbine . . . . . . . . . . . . . . . 41 (157)


Linde Process Plants . . . . . . . 45 (81)


Lurgi GmbH . . . . . . . . . . . . . 18 (95)


OHL . . . . . . . . . . . . . . . . . . . 27 (154)


ONS . . . . . . . . . . . . . . . . . . . 62 (104)


Prosernat . . . . . . . . . . . . . . . 24 (153)


Prosim . . . . . . . . . . . . . . . . . 59 (160)


Samson GmbH . . . . . . . . . . . . 4 (151)


SNC-Lavalin Engineers

& Construction Inc. . . . . . . . 24 (161)


Spencer Turbine . . . . . . . . . . . 54 (158)


Swagelok Co. . . . . . . . . . . . . 10 (63)


T.D. Williamson . . . . . . . . . . . 83 (66)


Team Industrial Services . . . . 57 (73)


Toyo Engineering Corporation 31 (57)


URS Corporation . . . . . . . . . . 33 (108)


Veolia Environment . . . . . . . . 31 (94)


FREE Product and Service Information — JANUARY 2010

ADVERTISERS in this issue of HYDROCARBON PROCESSING

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This information must be pro-vided to process your request:PRIMARY DIVISION OF INDUSTRY(check one only):A �-Refining CompanyB �- Petrochemical Co.C �-Gas Processing Co.F �-Equipment ManufacturerG �- Supply CompanyH �-Service CompanyJ �-Chemical Co.P �-Engrg./Construction Co.JOB FUNCTION (check one only):B �- Company Official, ManagerE �-Engineer or ConsultantF �- Supt. or Asst.G �-Foreman or Asst.I �-ChemistJ �-Purchasing Agt.

81

Company Page RS# Website



LORAINE A. HUCHLER, CONTRIBUTING EDITOR

HPIN WATER MANAGEMENT

[email protected]


Title IV, Permits and Licenses, of the Federal Water Protection Control Act, also known as the Clean Water Act (CWA) created the system for permitting wastewater discharges, known as the National Pollutant Discharge Elimination System (NPDES). Under NPDES, all facilities that discharge pollutants from any point source into waters of the US must obtain a wastewater dis-charge permit. Environmental personnel are directly responsible for reporting compliance to wastewater discharge permits. These environmental regulations impact the decisions and choices for chemical treatment in the water utilities.

Water permits. States regulate the volume and concentration of contaminants in treated wastewater and industrial storm water discharged to the local watershed. State regulators customize per-mits for each plant based on contaminants consistent with the manufacturing process and characteristics of the local watershed.

Each permit is unique and subject to renewal every several years. With each renewal cycle, the environmental regulations usually become stricter. The EPA limits the circumstances under which an existing permit can be modified or reissued with less stringent effluent limits, standards or conditions than those already imposed. Table 1 shows two examples of impacts by stricter permit limits on water utility operations.

The permit provides two levels of control: technology-based limits the ability of plants in the same industrial category to treat wastewater and water quality-based limits apply if the technology-based limits are insufficient to provide protection.

Pollutant categories. Regulators have grouped pollutants into three general categories under the NPDES program: con-ventional, toxic (priority) and nonconventional. CWA designated these five parameters as conventional pollutants:

• Five day biochemical oxygen demand (BOD5)• Total suspended solids (TSS)• pH• Fecal coliform• Oil and grease (O&G).Toxic (priority) pollutants include metals and man-made organic

compounds. The remaining pollutants are non-conventional pollut-ants including chlorine, ammonia, nitrogen, phosphorus-, chemical oxygen demand (COD) and whole effluent toxicity (WET).

Best control methods. Regulators initially defined treat-ment as Best Conventional Pollutant Control Technology (BCT) and Best Practical Control Technology (BPT). Later, regulators increased the requirements for treatment by imposing the eco-nomically Best Available Technology (BAT). New Source Perfor-mance Standards (NSPS) reflect effluent reductions that are achiev-able based on BAT. These standards are the most stringent controls; they require permit applicants to install high-efficiency wastewater treatment technologies. Environmental regulators must consider

the cost of achieving effluent reductions and any non-water quality environmental impacts and energy requirements.

Pretreatment Standards for New Sources (PSNS) and Pre-treatment Standards for Existing Sources (PSES) are national and uniform, technology-based standards that apply to dischargers to publicly owned treatment works (POTWs) from specific industrial categories (i.e., indirect dischargers). PSNS and PSES prevent the discharges of pollutants that pass through, interfere with, or are oth-erwise incompatible with the operation of POTWs. Environmental regulators consider the same factors and issue PSNS and NSPS at the same time. Tables 2 and 3 summarize these requirements.

The EPA annually reviews and revises its technology-based regulations, called “effluent limitations guidelines” or “effluent guidelines,” that limit the discharge of pollutants from various categories of industrial facilities.

Summary. Wastewater discharge permits will become stricter. Environmental personnel can provide valuable information about potential changes in specific contaminant limits that will impact decisions for chemical treatment in the water utilities. HP

The author is president of MarTech Systems, Inc., an engineering consult-ing firm that provides technical services to optimize energy and water-related systems including steam, cooling and wastewater in refineries and petro-chemical plants. She holds a BS degree in chemical engineering and is a licensed professional engineer in New Jersey and Maryland. She can be reached at:[email protected].

Wastewater discharge permits; What should you know?TABLE 1. Sample impacts on permit limits

State Regulation Impact

TX, IL Ultra-low [zinc] in discharge Use of zinc-corrosion inhibitors in cooling water may violate permit limits

KY No gluteraldehyde Must choose alternate non-oxidizing biocides

TABLE 2. Relevant standards

Types of sites regulated BPT BCT BAT NSPS PSES PSNS

Existing direct dischargers • • •

New direct dischargers •

Existing indirect dischargers •

New indirect dischargers •

TABLE 3. Pollutants regulated

Pollutants regulated BPT BCT BAT NSPS PSES PSNS

Priority pollutants • • • • •

Nonconventional pollutants • • • • •

Conventional pollutants • • •

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