Simulation of Visbreaker Fractionator Column_Vasilev

SIMULATION OF VISBREAKER FRACTIONATOR COLUMN – STEP BY STEP PROCEDURES

Svetlin Vasilev, Dicho Stratiev1, Ivelina Shishkova

1 Lukoil Neftochim Bourgas - R&D Department, 8104 Bourgas, Bulgaria,

e-mail: [email protected] KEY WORDS: process simulation ,visbreaker ABSTRACT

Simulating the performance of distillation columns whose feeds contain heavy oil components is the most challenging job. Poor feed characterization as well as inadequate column model techniques are the main reasons for inaccurate performance simulation. Computer models of systems processing wide boiling range hydrocarbon streams typically employ pseudo component representation of distillation fractions. In this method, commonly known bulk properties such as boiling point and gravity distributions are used in correlations to derive physical properties for petroleum fractions (pseudocomponents). These derived characteristics represent the properties of a mixture that is not, or can not be characterized by its individual chemical species. The heavy oil feed characterization is typically based on standard refinery laboratory distillation tests – ASTM D-1160 or ASTM D-2887. These distillation tests end at a distillation temperature of 5400C and extrapolation of 5400C+ distillation data is applied. The proper extrapolation technique along with the proper correlations used for feed pseudocomponent characterization are critical for an adequate distillation column performance simulation. In this work an example of simulation of a visbreaker column performance is presented where all feedstock characterization and modeling techniques are addressed.

INTRODUCTION

There are basically two main tasks a process engineer is faced with while creating a steady-state simulation model of a refinery fractionation column:

1. Specification of the feed requirements and proper thermodynamic models;

2. Creation of a flowsheet of adequately selected unit operations in order to create a mathematical model to closely match the real-life operation.

The first task also involves the proper sample collection of the feed and products from the existing plant, and performing adequate laboratory analyses.

It is well known among process designers that simulation of the performance of fractionators, whose feeds contain heavy hydrocarbon components is quite a challenging job. Poor feed characterization as well as inadequate column modeling techniques are the main reasons for the discrepancies between real-life operation and computer simulation, and also responsible for poor design of the plant [1]. It is known fact that computer models of systems employing hydrocarbons of wide boiling range are typically

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represented with pseudocomponents, one pseudocomponent for a narrow boiling range fraction. Each pseudocomponent’s properties are predicted by its average boiling point and specific gravity specified at least. The heavy hydrocarbon fractions represent the main obstacle to fully describe all the products. This is based on the fact that the laboratory distillation test available (ASTM D-1160 and ASTM D-2887) are limited to distillation temperature of no higher than 540 oC. This requires the distillation data beyond this point to be extrapolated.

In this article we will follow all the steps from the sample collection to the final simulation model that represents the real-life operation of the Visbreaker Fractionation Tower. We will also focus on how to deal with lack of laboratory data and how to overcome some of the short-comings, most commercial simulators have in the generation of pseudocomponents, extrapolating measured data and representing real-life phenomena that is not readily available in simulator’s unit operation models. SAMPLE COLLECTION AND LABORATORY ANALYSES

The main obstacle in feed characterization is that it is impossible to directly take a good sample from the fractionator’s feed transfer line. The main reasons for this are: high temperature of the stream; presence of water steam in the feed; the flow regime in the transfer line is far from what we call ideal mixing; the stream is in vapour-liquid state (moreover the vapour and liquid are not in equilibrium) and in last place – the cracking reactions which are still taking place in the transfer line.

Obviously the only adequate way to describe the feed is by blending (mixing) all the product streams leaving the fractionator. This method is successful only if product’s flowrates are properly measured and maintained in steady condition for at least 24 hours.

The following products, leaving the visbreaker fractionator can be identified: Hydrocarbon gas, visbreaker naphtha, process water, visbreaker gasoil (diesel) and visbreaker residue. Table I shows laboratory analyses, distillation method employed and measured product flow rates.

As mentioned above it is difficult and even impossible to perform analysis of products with normal boiling points above 540 oC. Since the recovery of the material boiling up to 5400C in the visbreaker residue was about 40% it was necessary to extrapolate the data to get some additional data points. According to Kaes the most accurate approach to extrapolate distillation data is the use of probability distillation paper [2]. It was indeed found this to be the better alternative to using the routines for extrapolation in the process simulator. The end boiling point has been taken from the recommendations made by Kaes [2]. A probability distillation paper plot for Visbreaker residue of our case is represented in Figure 1.


Table I Physical and Chemical Properties of the Visbreaker main fractionation column products

Properties

Visbreaker residue

Visbreaker Diesel

Visbreaker Naphtha Gas

Density @15 0C kg/m3 992.9 827.2 714.0 1.302

Viscosity @80 0C, 0E 33.6 Viscosity @ 100 0C, 0E 11.6

D-2887 D-86 vol.%

Distillation, wt.% TBP, 0C wt.% 0C vol.% 0C H2 3.0 8.3 360 IBP 101 IBP 37 CH4 33.4 12.2 400 5 153 5 55 CO2 0.4 15.0 420 10 164 10 65 C2H4 2.8 21.4 455 20 180 20 77 C2H6 16.4 29.1 490 30 196 30 87 C3H6 6.0 34.7 517 40 212 40 96 C3H8 10.8 50* 565 50 228 50 104 C4H10 8.0 70* 640 60 244 60 112 C5 2.7 90* 755 70 262 70 118 C6 0.1 98* 850 80 281 80 126 H2S 15.0 90 308 90 134 95 331 95 FBP 395 97 146

Density @15 0C of the residue boiling above 5170C

1.0609

Flow rates, kg/h 155 000 15 000 5 500 3 956

* Extrapolated from a probability distillation paper plot (see Figure 1)

PSEUDOCOMPONENT BREAKDOWN AND GENERATION Two main issues should be considered when generating the

pseudocomponents: 1) Blending of product streams to get the feed stream; 2) Proper prediction of pseudocomponent’s molecular weight. Some clarifications of the above-mentioned issues are given below: Pseudocomponent breakdown, generation and blending of dist. curves

Let us first follow how pseudocomponents are generated in commercial simulators. The first step is to convert all the specified distillation curves in True Boiling Point (TBP) distillation curves. This is done with the use of empirical formulae or nomograms. If a single distillation curve is specified the computer simulator first divides the whole distillation range into the number of pseudocomponents specified (For more information of all the procedures, please consult your simulator’s user manual or Kaes [2]). Each pseudocomponent is given a normal boiling point – an average of each interval and composition in volume or weight percent depending on the laboratory analysis type. Thus we defined one of the required properties of the pseudocomponent – its normal boiling point. The other required property to calculate all the rest physical properties is the specific gravity. There are two available routines the simulator uses to calculate this property - the first and the most exact is by specifying an additional curve for each distillation curve – specific gravity curve. However, this curve is not readily available from


laboratory analysis. So, we have chosen the second option, explained shortly below. In order to calculate each pseudocomponent’s specific gravity the computer simulator assumes equal Watson K-factor for each pseudocomponent and specific gravity is calculated from the Watson K-factor definition: Watson K-factor = (NBP)1/3/sp.gravity, (1) Where NBP is the normal boiing point of the pseudocomponent, in oR.

Watson K-factor is determined iteratively so that the calculated overall specific gravity of the product matches the specified.

Figure 1.The probability distillation paper plot for the Visbreaker residue

Blending of distillation curves is a procedure in which each pseudocomponent is given normal boiling point and sp.gravity specially fitted so that to correctly represent all the involved product distillation curves. In our case blending of distillation curves was avoided because it gave obsolete results. We adopted a method in which the Watson K-factor is calculated for each product distillation curve and assuming it is constant for all the pseudocomponents that belong to the same product, generated from this distillation curve. The pseudocomponents in our example are generated externally from the simulator and their properties are shown in Table II.


Table II Pseudocomponent breakdown and properties.

NBP SG MW K-factor NBP SG MW K-factor

0 0.6307 59.51 12.51412 397 0.9207 304.83 11.562

15 0.6420 64.88 12.51412 412 0.9275 321.18 11.562

30 0.6530 70.50 12.51412 428 0.9347 339.23 11.562

45 0.6636 76.36 12.51412 444 0.9417 352.86 11.562

61 0.6745 82.98 12.51412 461 0.9491 374.68 11.562

76 0.6845 89.39 12.51412 477 0.9559 396.40 11.562

91 0.6941 95.93 12.51412 493 0.9627 419.58 11.562

107 0.7042 102.95 12.51412 510 0.9698 446.18 11.562

122 0.7133 110.24 12.51412 526 0.9763 472.94 11.562

137 0.7697 117.69 11.74121 543 0.9832 503.87 11.562

152 0.7790 124.93 11.74121 559 0.9896 535.26 11.562

168 0.7887 130.18 11.74121 576 0.9963 571.89 11.562

183 0.7975 137.99 11.74121 592 1.0025 609.51 11.562

198 0.8062 146.60 11.74121 608 1.0086 651.00 11.562

213 0.8146 155.57 11.74121 625 1.0151 700.43 11.562

229 0.8235 165.67 11.74121 641 1.0211 752.57 11.562

244 0.8316 175.46 11.74121 661 1.0285 828.19 11.562

259 0.8395 185.67 11.74121 684 1.0368 934.18 11.562

274 0.8474 196.32 11.74121 707 1.0451 1070.80 11.562

290 0.8555 208.33 11.74121 730 1.0532 1196.00 11.562

305 0.8631 219.99 11.74121 753 1.0612 1330.38 11.562

320 0.8705 232.16 11.74121 776 1.0690 1478.85 11.562

336 0.8918 245.92 11.562 799 1.0768 1643.89 11.562

351 0.8991 259.33 11.562 822 1.0844 1827.35 11.562

366 0.9063 273.38 11.562 845 1.0920 2031.28 11.562

381 0.9133 288.13 11.562 868 1.0994 2257.97 11.562

Prediction of the pseudocomponents’ molecular weight

Numerous methods exist for predicting the molecular weight of oil fractions. They can be divided into two groups – graphical and analytical (empirical equations). The problem with most of these methods is that the derived correlations are generally made for predicting the molecular weight of straight-run oil fractions. When oil-fractions from conversion processes are specified discrepancies are observed from the actual molecular weight. The well know rule-of-thumb is: the higher is the average normal boiling point the greater is the deviation from the truth. In his work [3] Adriaan G. Goosens publishes a model applicable for straight-run fractions as well as products from conversion processes, where the standard deviation is only 2%. We adopted the correlation of Mr. Goosens in the calculation of the molecular weight of our pseudocomponents. The correlation stated in [3] is:

MW = 0.01077(TBP) [1.52869+0.06486ln(TBP/(1078-TBP))]/d, (2)

Where d – is the specific gravity @20 oC; TBP – is the pseudocomponent’s or fraction’s average normal true boiling point in K.


Correct molecular weight is crucial for the calculation of the mass-

transfer and phase equilibrium in the fractionator since distillation curves are specified in volumetric or weight percent, but the phase equilibrium equations use mole percent. We have to point out that no single solution is available to a complex problem – it can be seen that the heaviest last few components go beyond the correlation limit (above 804 oC the function is undeterminable as can be seen from Table 1). We extrapolated the function to get the molecular weight of these few pseudocomponents. The generated in this way pseudocomponents with their basic properties – normal boiling point, specific gravity and molecular weight are presented in Table 2. For our simulation we used ChemCAD for Windows of Chemstations Inc, a very robust and convenient simulator. It has an option for adding user defined components, which we used to enter the pseudocomponents generated by the way mentioned above. SPECIFYING THERMODYNAMIC METHODS FOR THE SIMULATION

A lot of models exist for the calculation of the vapor-liquid equilibrium constant K. Most of these equations represent a specially developed equation-of-state or an equation of corresponding states, some are purely empirical. In our case we used the Grayson-Streed equation of state because the visbreaker fractionator operates at low pressure. When selecting thermodynamic method the advice of the applied process simulator’s manual can be used. BUILDING THE FLOWSHEET AND PERFORMING THE SIMULATION

Figure 2 shows the Visbreaker Fractionator configuration as it is operated at site. The computer flowsheet used for the simulation is represented in Figure 3. There are several phenomena that should be considered when building the flowsheet. S. Golden, et all describe in their work [1] the main issues with deep cut vacuum columns simulation. Basically the same issue applies here to greater or lesser extent. We will follow in the same order as presented in [1]. Transfer line flowsheet representation.

The transfer line in the Visbreaker unit connects the Soaker Vessels with the fractionator feed nozzle. The flow regime in the line is of a mixed vapour-liquid phase. The pressure drop in the transfer line is a function of the velocity, physical properties of the oil and its physical layout. Things are more complicated by the cracking reactions still taking place in the transfer line. As a result of the transfer line pressure drop we know that the phase change is changing throughout the transfer line length. In most of the possible flow regimes the vapour and liquid phases in the transfer line are not uniformly mixed and liquid and vapour are not in equilibrium. The vapour entering the fractionator’s flash zone is highly superheated and additional volatilized by the steam available in the line. In our simulation model the transfer line is represented by a single theoretical stage.


Legend: C- Column; F – Furnace; D – Drum; S –Soaker; AC – Air Cooler: HE – Heat exchanger

Figure 2: Visbreaker Fractionator Column simplified P&ID


1

2

3

4

5

HC gas

Naphtha

RESIDUUM

6

WATER

3040 Nm3/h

5500 kg/h

LHT CGO 15000 kg/h

155000 kg/h

T=231.8 C

10 11

14

15

16

19

20

PRODUCT

177 C15000 kg/h

18 m3/h

13 m3/h

155 000 kg/h

37.2 m3/h

NAPHTHA5500 kg/h

gas 3040 Nm3/h

T=37.9 C

P=2.7 kg/cm2

379 C T=358 C

P=3.72 kg/cm2

T=132 C

VISBREAKER FRACTIONATOR SIMULATION

MEASURED DATA SHOWN

Measured tray temperatures:

#17 - 200 C

#23 - 284 C

#27 - 332 C

#28 - 339 C

WASH OIL

25

26

RESIDUE

24FEED

FLASH ZONE

ENTRAINMENT

SH VAPOURS

TRANSFER LINE

NON-IDEAL MIXUP

27

31

8

29

residue

23

30

33

12

34

35

water drain

7

22

36

38

WASH ZONE

13

reflux

PUMPAROUND

9

28

1737

21

Figure 3: Computer flowsheet - Simulation representation of Visbreaker Fractionator Configuration Flash zone

The vapour-liquid feed enters the column and experiences pressure drop at the column feed nozzle. After that vapour and liquid are separated and vapour rises up the column. Normally some sort of vapour-liquid separating device (vapour horn, multivane distributor or more complex devices provided by column internal vendors). In our case no special device is available but a simple splash baffle at the nozzle outlet. This results in high heavy oil entrainment with the rising vapour. This increases the requirement for wash oil to the wash zone of the column. The liquid entrainment actually exceeds the overflash. Wash zone

At best the wash zone function is to fractionate the volatilized contaminants and de-entrain residue. It should also de-superheat the rising flash zone vapour. The main obstacle in simulating the wash zone is that one cannot specify liquid, leaving upper tray to go to a lower tray. This conflicts the column material balance. There is no problem to specify a pumparound where liquid from a lower tray is cooled and introduced to upper tray. To overcome this wash zone is represented externally from the column unit operation.


Remaining trays of the fractionator. The remaining part of the column does not constitute significant

problem. Distillation unit operation is used with Inside-out rigorous distillation method used. The column is fed with the overflash vapour from the wash zone, has a top product, one side-drawoff and liquid bottom product, which enters the wash zone. DISCUSSION OF THE SIMULATION RESULTS In Table III a comparison between measured plant data and simulation results is made. A close match can be seen between the computer simulation and the real plant data. Now as we match the computer model to reality we can highlight more important design task:

1) Reduce the consumption of the wash-oil in wash zone by choosing a column internals vendor to supply a vapour-liquid distributing device.

2) Increase the diesel drawoff flowrate. The visbreaker diesel is valuable feedstock to the hydrodesulphurization plant. Now it is mixed back with the residue to reduce its viscosity so it can be used as fuel oil. A possible alternative can be the FCC unit heavy cycle oil – some preliminary calculation had been made.

Table III Comparison between simulated and real performance of the visbreaker main fractionator

Simulated Real measured

Column temperature profile,

0C

Top 144 132

17 tray 206 200

23 tray 253 284

28 tray 341 339

Bottom 358 358

Product quantity, t/h

Gas 4.3 4.0

Naphtha 5.0 5.5

Diesel 14.3 15.0

Residue 156.2 155.0

Product quality

Specific gravity

Naphtha 0.704 0.714

Diesel 0.847 0.8272

Residue 0.989 0.993

Distillation

ASTM D-86, vol.%/ 0C

Naphtha

IBP -18 37

5 32 55

10 52 65

20 75 77

30 91 87

40 104 96

50 113 104


Simulated Real measured

60 120 112

70 126 118

80 132 126

90 141 134

95 151

97 146

100 163

Diesel

IBP 120 101

5 191 153

10 198 164

20 209 180

30 220 196

40 235 212

50 253 228

60 282 244

70 319 262

80 332 281

90 349 308

95 371 331

97 395

100 442

Residue

TBP at 1 atm

IBP 61

5 327 323

10 356 379

20 440 448

30 490 497

40 533 538

50 557 565

60 587 612

70 622 650

80 734 694

90 769 751

95 808 796

97

100 881

REFERENCE

1. Golden S. W., Villalanti D. C., Martin G. R., “Feed Characterization and deep cut vacuum columns: simulation and design. Impact of High Temperature Simulated Distillation”, AIChE 1994 Spring National Meeting, 1994, Atlanta, Georgia, USA. 2. Kaes G. L., “Modeling of Oil Refining Processes and Some Practical Aspects of Modeling Crude Oil Distillation”, VMGSim User’s Manual, www.virtualmaterials.com. 3.Goossens A. G., “Prediction of Molecular Weight of Petroleum Fractions”, Ind.Eng. Chem. Res., 35 (3), 985-988, 1996.


4. Bridjanian H., Ghaedian M., Hashemi R., Mohammadbeigy Kh., “Effective parameters of PNA reduction in visbreaker naphtha”, Petroleum and Coa,l 47 (3), 1-5, 2005. 5. Goossens A. G. “Prediction of the Hydrogen Content of Petroleum Fractions”, Ind. Eng. Chem. Res., 36, 2500-2504, 1997.


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