NotesNov-09NOTES:The papers listed here have been obtained by search SPE and IPTC papers post 2005 on the SPE's OnePetroThe papers relating to reservoir engineering have been catergorised for inclusion on the reservoirengineering.org.uk websiteThe affiiations searched were;Total No PapersReservoir Engineering RelatedBP551175Shell575279Chevron482238ConocoPhillips19168Marathon5537Total255129Schlumberger1130563Imperial College, London9553Heriot Watt University, Edinburgh235175(Anywhere in Article)Total35691717Total number of papers published post 2005 =10,00035% of papers published categorised

Material BalanceOrganisationSourcePaper No.ChapterSectionSubjectTitleAuthorAbstractMARATHONSPE105982Reservoir ModellingDynamic Material BalanceMaterial Balance RevisitedK.P. Ojo, Marathon Oil Company, and S.O. Osisanya, U. of OklahomaAbstract The material balance is a very important part of the reservoir engineers toolbox that is being relegated to the background in todays reservoir evaluation workflow. This paper examines some issues that normally preclude its regular use especially as a pre-step before moving into full reservoir simulation and the use of a new method of analyzing the material balance equation called the dynamic material balance method for solving some of these issues. The dynamic material balance method allows the simultaneous determination of the initial oil-in-place (N) or initial gas-in-place (G) ratio of initial gas to oil (m) reservoir permeability (K) or skin factor (S) and average pressure history of a reservoir from the combination of solution to the material balance equation and pressure transient analysis theory. Cumulative production history and PVT data of the reservoir are used with limited or no pressure data. By introducing a time variable into the classical material balance equation (MBE) and combining the solutions of the resulting equations with the theory of pressure transient analysis the cumulative production history of the reservoir and readily available PVT data of the reservoir fluids we can estimate not only the original reserves in place but also determine the average reservoir pressure decline history as indicated by the net fluid withdrawal from the reservoir. The reservoir permeability and skin factor as seen within the drainage area of each producing well can then be estimated from the already determined average pressure decline history. This method is expected to improve the use of material balance by expanding the list of problems that can be tackled using material balance especially to reservoirs in marginal fields and reservoirs in which limited pressure data is available. Introduction The material balance equation (MBE) is a very import tool used by reservoir engineers in the oil and gas industry. MBE can provide an estimate of initial hydrocarbon in place independent of geological interpretation and can also serve the purpose of verifying volumetric estimates. It can also help determines the degree of aquifer influence understanding the applicable drive mechanism and in some cases estimate recovery factor and recoverable reserves. Conventionally MBE is applied by considering different time intervals in the production history of the reservoir and maintaining that there exists a volumetric balance in the reservoir at these different time intervals. Several methods have been developed and published on applying the MBE to various types of reservoirs and solving the equation to obtain the initial oil-in-place (N) or initial gas-in-place (G) and the ratio of the initial free gas to oil (m) in the reservoir. One of such methods is the straight-line method popularized by Havlena and Odeh2 3 which instead of considering each time interval and corresponding production data as being separate from other time interval combines all time intervals and obtain a solution that satisfies all the intervals together. In applying the straight-line method however it is usually required that an independent source of determining the value of m exist. Most application uses an m that is derived from geological data on relative ratio of gas cap to oil column volumes. Another important requirement is the need to accurately estimate the average reservoir pressure at the various time intervals. The standard practice is to estimate the average reservoir pressure from well test conducted on individual wells producing from the reservoir. In thick formations with high permeability and low viscosity hydrocarbons average pressures obtained from the individual well tests are good estimates of the average reservoir pressures in the drainage area of the well. But for thinner formations of lower permeability and higher viscosity hydrocarbons there are often large variations in reservoir pressure throughout the reservoir and obtaining an average drainage area reservoir pressure usually require longer testing times and obtained values are often inaccurate. Accurately determining this average reservoir pressure is critical to the accuracy of the reserves estimate obtained from the MBE.CHEVRONIPTC11489Reservoir ModellingMaterial BalanceComplex Dynamic BehaviourCapturing Complex Dynamic Behaviour in a Material Balance ModelJalal Mazloom and Mike Tosdevin, SPE, Sasol Petroleum International, and Dominique Frizzell, Bill Foley, and Mike Sibley, SPE, ChevronAbstract Sometimes a simple and quick material balance method is preferred to using a numerical simulation model. This preference can be justified when preparing the development plan and production optimization for a collection of hydrocarbon reservoirs (lean and rich gas condensate oil rim and gas cap) some connected to an aquifer and the reservoirs cannot be modelled separately. This situation can occur when multiple gas reservoirs are needed to be developed in order to provide enough gas for a particular project. A significant drawback of this modelling approach is the simplification introduced when a single tank model (Material balance method) is being used instead of a fine grid simulation model. The material balance method assumes every well contacts all hydrocarbons and that geological heterogeneity is not a factor in recovery. It is necessary to know how reliable are final gas and condensate recovery factors and gas condensate and water production profiles predicted by a material balance model. In this study we address all these uncertainties. A sensitivity analysis has been carried out on different aquifer strengths gas condensate richness and reservoir heterogeneity which are related to the real and field data set. Introduction of a generic method for selecting the important input data to the material balance model (relative permeabilities and well productivities) in order to have reliable results is the target of this study. The material balance results are compared to a fine grid simulation. It is observed that using the introduced method the effect of reservoir heterogeneity and aquifer influx on final gas recovery factor can be captured in a material balance model. Introduction Predictions of oil and gas reservoirs behavior and hydrocarbon production profiles from them are crucial steps for planning fields development. Although it is believed numerical simulation (3 dimensional models) gives more reliable results than a material balance (zero dimensions) evaluation a material balance method can be utilized in an acceptable range of uncertainties. Material balance has been used as a reliable tool for calculating hydrocarbon volume initial in place and reservoir drive mechanism and prediction production profile1 2. Sometimes material balance can be used for narrowing down uncertainties around in place volume and compartmentalization and presence of faults before simulation3. Recent years have witnessed efforts for improving the material balance method4 5. Also some studies have shown that material balance can be utilized for performance prediction of gas condensate reservoirs6. However it is still important to understand whether field performance as predicted by a tank model is reliable enough for making a financial investment decision. In this paper reservoir performance and production profiles predicted by material balance and 3D simulation model are compared with each other. It is explained how the tank model can capture the effect of aquifer and condensate drop-out on reservoir performance if the model is tuned properly. Model construction and sensitivity analysis 1. Simulation model construction A heterogeneous 3D geological model that had been constructed in GOCAD was selected as the reservoir model. General characteristics of the model can be found in table 1.SCHLUMBERGERSPE101138Reservoir ModellingMaterial BalanceComplex Mature ReservoirsMaterial Balance Analysis in Complex Mature Reservoirs - Experience in Samarang Field, MalaysiaT. Bui, SPE, Schlumberger; M. Bandal, SPE, and N. Hutamin, SPE, Petronas; and A. Gajraj, SPE, Golden Eagle Intl.Abstract In this paper we present the results of a material balance study for a mature field in East Malaysia. The field consists of several stacked sands and is highly faulted resulting in a complex system of several compartmentalized reservoirs. The drive mechanisms of these reservoirs range from strong gas cap drive to strong water influx or combinations of these. Fourteen material balance models were built and the results analyzed. This study shows that proper integration of all pressure production and geological data is critical in defining reservoir compartmentalization and in analyzing the results of material balance (MB) analysis. In particular analysis of the reservoir production behavior and the fluid contact movement over time is essential in narrowing the uncertainty in the parameters used in the model. In building the MB model two new techniques were proposed and successfully used: moving linear regression for generating the input pressure for the MB model production-derived relative permeability data for MB prediction. Applying these techniques resulted in a well-behaved model and a realistic production profile. Introduction The Samarang field is located offshore in Sabah East Malaysia. The field was discovered in 1972 and began production in mid1975. By the end of 2004 nearly 400 MMSTB of oil had been produced from 18 sand sequences with the main reservoirs being the J K and M sands (Fig. 1). The major sand bodies were deposited in a shallow nearshore marine environment during the late Miocene to early Oligocene eras. The field is situated at the crest of a rollover anticline and is characterized by a series of northeast-southwest trending faults. This fault system divides the main producing area into sub-parallel fault blocks. The fluid properties in the field vary vertically with oil density gradually increasing from 35-37 API in the deeper reservoirs to 19 API in the shallow reservoirs. Most reservoirs have an initial gas cap with the ratio of gas cap volume to oil volume ranging from 0.1 to 3.0. The production history shows that most reservoirs experienced strong water influx. In 2004 a field review project was initiated to investigate the potential of the field and to look for opportunities to increase oil and gas recovery. Material balance analysis is a part of that integrated study. The objective of the material balance analysis is to investigate the drive mechanism and parameters of each reservoir unit and their effect on the fluid recovery. Some results of the MB analysis will beCHEVRONSPE103258Reservoir ModellingMaterial BalanceP/ZA Straight Line p/z Plot is Possible in Waterdrive Gas ReservoirsM. Elahmady, Chevron, and R.A. Wattenbarger, Texas A&M U.Abstract Field data and simulated models have revealed that in some cases waterdrive gas reservoirs can be mistakenly misidentified using material balance methods as depletion drive gas reservoirs causing a significant overestimation in gas reserves. The famous straight-line plot of p/z vs. Gp has been traditionally used to estimate original gas in place (and gas reserves) for depletion-drive gas reservoirs. A gas reservoir in contact with an aquifer in transient phase (unsteady-state) and producing under a certain production schedule can plot as a straight-line on a p/z plot masking the existence of an active aquifer and causing a significant overestimation in gas reserves. The authors in this paper simulate synthetic cases of gas reservoir/aquifer models using a forward model and an inverse model that were programmed in visual basic to show that the combination of certain rate schedules and the unsteady state nature of aquifers can cause a straight-line p/z plot in waterdrive gas reservoirs. The authors also demonstrate that the Havlena-Odeh1 2 Plot (also known by some authors in the literature as the Cole3 Plot) for those same cases will also mask the existence of an active transient aquifer giving the same value of overestimated original gas in place (OGIP) as that obtained from the p/z plot. Introduction The material balance equation for a depletion-drive gas reservoir when observed on plots will have what historically is thought to be unique features that help easily to estimate OGIP (and reserves). In this paper we show that these features are not unique for a depletion-drive reservoir but can happen to exist also in a waterdrive gas reservoir. This causes a clear non-uniqueness problem which can cause to overestimate OGIP (and Reserves). The material balance equation for a reservoir with no water influx and no water encroachment and if we neglect formation and water compressibilities is shown in Eq. 1 Equation (1) The above equation can be written also as Equation (2) Eq. 2 states that there is a linear relationship between p/z and the cumulative volume of produced gas Gp as shown in Fig. 1. If the trend of this straight-line is extrapolated to p/z = 0 then we can obtain an estimate of the original gas in place (OGIP) which we will call from here on as G.SCHLUMBERGERSPE107907Reservoir ModellingMaterial BalanceUncertainty ManagementPressure and PVT Uncertainty in Material-Balance CalculationsCarlos A. Garcia and Jose R. Villa, U. Central de VenezuelaAbstract Original Oil In Place (OOIP) calculations based on material balance methods are strongly influenced by data uncertainty. Although some research is available in literature usually the effects of data uncertainty on material balance calculations are rarely considered and quantified in most studies. This work presents an approach to properly quantify and account for the impact of reservoir pressure and PVT data uncertainty on material balance calculations under different drive mechanisms and using different material balance methods. This study allows reservoir engineers properly select the most suitable material balance method when uncertainty on reservoir pressure and PVT data is significant. In this work two different methodologies are proposed. First a sensitivity analysis was conducted using generated realizations of reservoir pressure and PVT data to evaluate their effect on material balance calculations. Second a more robust approach was proposed using experimental design and analysis of variance to systematically evaluate the influence of reservoir pressure and PVT data on material balance calculations in an optimal and integrated fashion. In both methodologies different material balance methods were used and computed OOIP were compared to reference values from a conceptual reservoir model with known PVT data and simulated reservoir pressure. A MATLAB-based program with graphical user interface was coded for this purpose1. Application of the proposed methodologies allowed to determine and quantify the most significant parameters that influence material balance calculations. Interestingly the most important parameter was the selected material balance method used to compute the OOIP. More accurate results were obtained using the traditional graphical method (F-We vs. Et) for volumetric oil reservoirs with minimal pressure and PVT data uncertainty. In those cases with moderate to significant water influx and gas cap and some uncertainty on pressure and PVT data less accurate original oil in place was obtained when graphical methods were used. Reservoir pressure uncertainty was the most significant parameter on the material balance calculations. Gas-oil ratio uncertainty was also significant. Oil and gas gravity and reservoir temperature were less significant. Introduction Material balance is a simple and one of the most important reservoir engineering tools. Calculations require production/pressure data PVT data and aquifer parameters so that original oil in place and drive mechanisms can be quantified. Data quality is an important issue in material balance calculations. Uncertainty due to data errors can be found in field production data measured PVT properties and average reservoir pressure. Usually it is expected that oil and gas production are measured with confidence since industry revenues are based on oil and gas sales and consequently error in production data can be considered minimal. However reservoir pressure is uncertain since limited well measurements are usually available and averaging procedures might introduce some uncertainty in the computed reservoir pressure history. PVT data can be also uncertain since some reservoirs have no representative fluid samples for a complete PVT analysis and correlations are used instead for material balance calculations.