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Relevant bibliographies by topics / Oil reservoir simulation

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Academic literature on the topic 'Oil reservoir simulation'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Oil reservoir simulation"

1

Anonymous. "Oil reservoir simulation package." Eos, Transactions American Geophysical Union 70, no. 26 (1989): 676. http://dx.doi.org/10.1029/eo070i026p00676-03.

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Ghassemzadeh, Shahdad, Maria Gonzalez Perdomo, Manouchehr Haghighi, and Ehsan Abbasnejad. "Deep net simulator (DNS): a new insight into reservoir simulation." APPEA Journal 60, no. 1 (2020): 124. http://dx.doi.org/10.1071/aj19093.

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Reservoir simulation plays a vital role as a diagnostics tool to better understand and predict a reservoir’s behaviour. The primary purpose of running a reservoir simulation is to replicate reservoir performance under different production conditions; therefore, the development of a reliable and fast dynamic reservoir model is a priority for the industry. In each simulation, the reservoir is divided into millions of cells, with fluid and rock attributes assigned to each cell. Based on these attributes, flow equations are solved through numerical methods, resulting in an excessively long processing time. Given the recent progress in machine learning methods, this study aimed to further investigate the possibility of using deep learning in reservoir simulations. Throughout this paper, we used deep learning to build a data-driven simulator for both 1D oil and 2D gas reservoirs. In this approach, instead of solving fluid flow equations directly, a data-driven model instantly predicts the reservoir pressure using the same input data of a numerical simulator. Datasets were generated using a physics-based simulator. It was found that for the training and validation sets, the mean absolute percentage error (MAPE) was less than 15.1% and the correlation coefficient, R2, was more than 0.84 for the 1D oil reservoirs, while for the 2D gas reservoir MAPE < 0.84% and R2 ≈1. Furthermore, the sensitivity analysis results confirmed that the proposed approach has promising potential (MAPE < 5%, R2 > 0.9). The results agreed that the deep learning based, data-driven model is reasonably accurate and trustworthy when compared with physics-derived models.

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Ayache, Simon V., Violaine Lamoureux-Var, Pauline Michel, and Christophe Preux. "Reservoir Simulation of Hydrogen Sulfide Production During a Steam-Assisted-Gravity-Drainage Process by Use of a New Sulfur-Based Compositional Kinetic Model." SPE Journal 22, no. 01 (August 3, 2016): 080–93. http://dx.doi.org/10.2118/174441-pa.

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Summary Steam injection is commonly used as a thermal enhanced-oil-recovery (EOR) method because of its efficiency for recovering hydrocarbons, especially from heavy-oil and bitumen reservoirs. Reservoir models simulating this process describe the thermal effect of the steam injection, but generally neglect the chemical reactions induced by the steam injection and occurring in the reservoir. In particular, these reactions can lead to the generation and production of the highly toxic and corrosive acid gas hydrogen sulfide (H2S). The overall objective of this paper is to quantitatively describe the chemical aquathermolysis reactions that occur in oil-sands reservoirs undergoing steam injections and to provide oil companies with a numerical model for reservoir simulators to forecast the H2S-production risks. For that purpose, a new sulfur-based compositional kinetic model has been developed to reproduce the aquathermolysis reactions in the context of reservoir modeling. It is derived from results gathered on an Athabasca oil sand from previous laboratory aquathermolysis experiments. In particular, the proposed reactions model accounts for the formation of H2S issued from sulfur-rich heavy oils or bitumen, and predicts the modification of the resulting oil saturate, aromatic, resin, and asphaltene (SARA) composition vs. time. One strength of this model is that it is easily calibrated against laboratory-scale experiments conducted on an oil-sand sample. Another strength is that its calibration is performed while respecting the constraints imposed by the experimental data and the theoretical principles. In addition, in this study no calibration was needed at reservoir scale against field-production data. In the paper, the model is first validated with laboratory-scale simulations. The thermokinetic modeling is then coupled with a 2D reservoir simulation of a generic steam-assisted gravity drainage (SAGD) process applied on a generic Athabasca oil-sand reservoir. This formulation allows investigating the H2S generation at reservoir scale and quantifying its production. The H2S- to bitumen-production ratio against time computed by the reservoir simulation is found to be consistent with production data from SAGD operations in Athabasca, endorsing the proposed methodology.

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Taggart, I. J., and H. A. Salisch. "FRACTAL GEOMETRY, RESERVOIR CHARACTERISATION AND OIL RECOVERY." APPEA Journal 31, no. 1 (1991): 377. http://dx.doi.org/10.1071/aj90030.

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Reservoir heterogeneity is a dominant factor in determining large-scale fluid flow behaviour in reservoirs. Engineering estimates of oil production rates need to acknowledge and incorporate the effect of such heterogeneities. This work examines the use of fractal-based scaling techniques aimed at characterising heterogeneous reservoirs for simulation purposes. Well log data provide suitable fine-scale information for estimating the fractal dimension of reservoirs as well as providing known end- point data for interwell property value interpolation. Fractal techniques allow this interpolation to be performed in a manner which reproduces the same correlation structure as that found in the original well logs. Conditional simulation in these property fields allows the interaction between reservoir heterogeneity and fluid flow to be studied on a range of scales up to the interwell spacing. Analysis of results allows the calculation of effective reservoir properties which characterise the reservoir in terms of large-scale performance.

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Lee, Ji Ho, and Kun Sang Lee. "Multiphase, Multicomponent Simulation for Flow and Transport during Polymer Flood under Various Wettability Conditions." Journal of Applied Mathematics 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/101670.

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Accurate assessment of polymer flood requires the understanding of flow and transport of fluids involved in the process under different wettability of reservoirs. Because variations in relative permeability and capillary pressure induced from different wettability control the distribution and flow of fluids in the reservoirs, the performance of polymer flood depends on reservoir wettability. A multiphase, multicomponent reservoir simulator, which covers three-dimensional fluid flow and mass transport, is used to investigate the effects of wettability on the flow process during polymer flood. Results of polymer flood are compared with those of waterflood to evaluate how much polymer flood improves the oil recovery and water-oil ratio. When polymer flood is applied to water-wet and oil-wet reservoirs, the appearance of influence is delayed for oil-wet reservoirs compared with water-wet reservoirs due to unfavorable mobility ratio. In spite of the delay, significant improvement in oil recovery is obtained for oil-wet reservoirs. With respect to water production, polymer flood leads to substantial reduction for oil-wet reservoirs compared with water-wet reservoirs. Moreover, application of polymer flood for oil-wet reservoirs extends productive period which is longer than water-wet reservoir case.

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Dogru, A. H., H. A. Sunaidi, L. S. Fung, W. A. Habiballah, N. Al-Zamel, and K. G. Li. "A Parallel Reservoir Simulator for Large-Scale Reservoir Simulation." SPE Reservoir Evaluation & Engineering 5, no. 01 (February 1, 2002): 11–23. http://dx.doi.org/10.2118/75805-pa.

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Summary A new parallel, black-oil-production reservoir simulator (Powers**) has been developed and fully integrated into the pre- and post-processing graphical environment. Its primary use is to simulate the giant oil and gas reservoirs of the Middle East using millions of cells. The new simulator has been created for parallelism and scalability, with the aim of making megacell simulation a day-to-day reservoir-management tool. Upon its completion, the parallel simulator was validated against published benchmark problems and other industrial simulators. Several giant oil-reservoir studies have been conducted with million-cell descriptions. This paper presents the model formulation, parallel linear solver, parallel locally refined grids, and parallel well management. The benefits of using megacell simulation models are illustrated by a real field example used to confirm bypassed oil zones and obtain a history match in a short time period. With the new technology, preprocessing, construction, running, and post-processing of megacell models is finally practical. A typical history- match run for a field with 30 to 50 years of production takes only a few hours. Introduction With the development of early parallel computers, the attractive speed of these computers got the attention of oil industry researchers. Initial questions were concentrated along these lines:Can one develop a truly parallel reservoir-simulator code?What type of hardware and programming languages should be chosen? Contrary to seismic, it is well known that reservoir simulator algorithms are not naturally parallel; they are more recursive, and variables display a strong dependency on each other (strong coupling and nonlinearity). This poses a big challenge for the parallelization. On the other hand, if one could develop a parallel code, the speed of computations would increase by at least an order of magnitude; as a result, many large problems could be handled. This capability would also aid our understanding of the fluid flow in a complex reservoir. Additionally, the proper handling of the reservoir heterogeneities should result in more realistic predictions. The other benefit of megacell description is the minimization of upscaling effects and numerical dispersion. The megacell simulation has a natural application in simulating the world's giant oil and gas reservoirs. For example, a grid size of 50 m or less is used widely for the small and medium-size reservoirs in the world. In contrast, many giant reservoirs in the Middle East use a gridblock size of 250 m or larger; this easily yields a model with more than 1 million cells. Therefore, it is of specific interest to have megacell description and still be able to run fast. Such capability is important for the day-to-day reservoir management of these fields. This paper is organized as follows: the relevant work in the petroleum-reservoir-simulation literature has been reviewed. This will be followed by the description of the new parallel simulator and the presentation of the numerical solution and parallelism strategies. (The details of the data structures, well handling, and parallel input/output operations are placed in the appendices). The main text also contains a brief description of the parallel linear solver, locally refined grids, and well management. A brief description of megacell pre- and post-processing is presented. Next, we address performance and parallel scalability; this is a key section that demonstrates the degree of parallelization of the simulator. The last section presents four real field simulation examples. These example cases cover all stages of the simulator and provide actual central processing unit (CPU) execution time for each case. As a byproduct, the benefits of megacell simulation are demonstrated by two examples: locating bypassed oil zones, and obtaining a quicker history match. Details of each section can be found in the appendices. Previous Work In the 1980s, research on parallel-reservoir simulation had been intensified by the further development of shared-memory and distributed- memory machines. In 1987, Scott et al.1 presented a Multiple Instruction Multiple Data (MIMD) approach to reservoir simulation. Chien2 investigated parallel processing on sharedmemory computers. In early 1990, Li3 presented a parallelized version of a commercial simulator on a shared-memory Cray computer. For the distributed-memory machines, Wheeler4 developed a black-oil simulator on a hypercube in 1989. In the early 1990s, Killough and Bhogeswara5 presented a compositional simulator on an Intel iPSC/860, and Rutledge et al.6 developed an Implicit Pressure Explicit Saturation (IMPES) black-oil reservoir simulator for the CM-2 machine. They showed that reservoir models over 2 million cells could be run on this type of machine with 65,536 processors. This paper stated that computational speeds in the order of 1 gigaflop in the matrix construction and solution were achievable. In mid-1995, more investigators published reservoir-simulation papers that focused on distributed-memory machines. Kaarstad7 presented a 2D oil/water research simulator running on a 16384 processor MasPar MP-2 machine. He showed that a model problem using 1 million gridpoints could be solved in a few minutes of computer time. Rame and Delshad8 parallelized a chemical flooding code (UTCHEM) and tested it on a variety of systems for scalability. This paper also included test results on Intel iPSC/960, CM-5, Kendall Square, and Cray T3D.

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Kaliszewski, A. B. "RESERVOIR SIMULATION FOR RESERVOIR MANAGEMENT." APPEA Journal 26, no. 1 (1986): 397. http://dx.doi.org/10.1071/aj85034.

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The Hutton reservoir in the Merrimelia Field (Cooper-Eromanga Basin) was the subject of a 3-D reservoir simulation study. The primary objective of the study was to develop a reservoir management tool for evaluating the performance of the field under various depletion options.The study confirmed that the ultimate oil recovery from this strong water drive reservoir was not adversely affected by increasing total fluid offtake rate. However, any decisions regarding changes to the depletion scheme such as increasing production rates, if based solely on computer simulation results, should be viewed with caution. Careful monitoring of any changes to the depletion philosophy and checking of actual data against simulation predictions are essential to ensure that oil production rate and ultimate recovery are optimised.The model assisted in evaluating the economics of development drilling. While the simulation results are dependent on the validity of geological mapping, the model was useful in confirming that, due to very high transmissibility in the Hutton reservoir, additional wells would only accelerate production rather than increase ultimate recovery. The issue of drilling wells thus became one of balancing the benefits of accelerating production against the geological risk associated with that well.Interaction between the reservoir engineer and various disciplines, particularly development geology, is critical in the development and application of a good working simulation model. This was found to be especially important during the history matching phase in the study. If engineers and development geologists can learn more of the others' discipline and appreciate the role that each has to play in simulation studies, the validity of such models can only be improved.The paper addresses a number of the pitfalls commonly encountered in application of reservoir simulation results.

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Towler, B. F. "RESERVOIR SIMULATION IN THE MEREENIE FIELD." APPEA Journal 26, no. 1 (1986): 428. http://dx.doi.org/10.1071/aj85037.

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The Mereenie Field in the Amadeus Basin was discovered in 1964 and contains an estimated 240 million barrels of oil and 480 billion (USA) cubic feet of gas in three formations. The field commenced production at 1500 barrels of oil per day from seven wells in September 1984. The structure is large and elongated and the oil in the permeable sands appears as a rim round the structure. This paper describes a reservoir simulation study initiated to evaluate the recovery of oil from wells sited on the north and south flanks of the anticline where the steep dips cause the oil rim to become very narrow.Ten studies were made on a 21 × 15 cell pattern model using a three phase semi-implicit black oil reservoir simulator. The ten runs compared oil recovery and gas/oil ratio as a function of formation dip, bottom hole flowing pressure, gas injection and water injection. These showed that the flank wells could be expected to recover 300 000 stock tank barrels of oil from primary and secondary operations which represents about 25 per cent of the oil in place for wells sited on half mile spacings. However the wells will experience high gas/oil ratios and a steep decline in oil rate.

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Xu, Zhongyi, Linsong Cheng, Renyi Cao, and Sidong Fang. "Simulation of Counter-Current Imbibition in SRVs of Tight Oil Reservoir." Journal of Clean Energy Technologies 6, no. 4 (July 2018): 339–43. http://dx.doi.org/10.18178/jocet.2018.6.4.485.

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Tong, Kai Jun, Yan Chun Su, Li Zhen Ge, Jian Bo Chen, and Ling Ling Nie. "Numerical Simulation of the Buried Hill Reservoir in Bohai Bay." Applied Mechanics and Materials 448-453 (October 2013): 4003–8. http://dx.doi.org/10.4028/www.scientific.net/amm.448-453.4003.

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Buried hill reservoir fracture description and reservoir simulation technology have been a hot research, but also is one of the key issues that restrict the efficient development of such reservoirs. Based on JZ buried hill reservoir which heterogeneity is strong, some wells water channeling fast and difficult to control the situation for fracture affect, a typical block of dual medium reservoir numerical models which was comprehensive variety of information, discrete fracture characterization and geological modeling is established. The fractured reservoir numerical model is simulated through Eclipse software to seek the law of remaining oil distribution. Through the reservoir geological reserves and production history matching, the remaining oil distribution of main production horizon is forecasted. On this basis, the results of different oilfield development adjustment programs are predicted by numerical simulation.

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Dissertations / Theses on the topic "Oil reservoir simulation"

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Whaballa, Ala. "Reservoir simulation and well testing of compartmentalized reservoirs." Thesis, Heriot-Watt University, 1991. http://hdl.handle.net/10399/1493.

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Wang, Linna. "Reservoir simulation study for the South Slattery Field." Laramie, Wyo. : University of Wyoming, 2007. http://proquest.umi.com/pqdweb?did=1400965521&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.

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Ahmed, Elfeel Mohamed. "Improved upscaling and reservoir simulation of enhanced oil recovery processes in naturally fractured reservoirs." Thesis, Heriot-Watt University, 2014. http://hdl.handle.net/10399/2755.

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Naturally fractured reservoirs (NFR) contain a significant amount of remaining petroleum reserves and are now considered for Enhanced Oil Recovery (EOR) schemes that involve three-phase flow such as water-alternating-gas (WAG) injection. Accurate numerical simulation of flow in NFR is essential for sound reservoir management decisions to maximise oil recovery and minimise the cost of field development. In this thesis, two important issues related to flow simulation in NFR are investigated. First, a step-wise upscaling approach is developed to evaluate the accuracy of dual porosity models in estimating matrix-fracture transfer duringWAG injection. It was found that the classical dual porosity models generally overestimate recovery from matrix blocks. Hence, a double block model was developed and extended to a multi-rate dual porosity (MRDP). The multi-rate double block model showed significant improvements in matching detailed fine grid simulations of three-phase matrix-fracture transfer. Second, the accuracy of upscaling discrete fracture networks (DFN) is assessed and its impact on history matching was investigated on a real fractured reservoir. A new method to upscale the shape factors needed for MRDP models from DFN is presented. This method is a notable step towards more accurate but still efficient reservoir simulation in NFR.

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Balland, Philippe. "The solenoidal finite element method and reservoir simulation." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260727.

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Gessel, Gregory M. "A New Method for Treating Wells in Reservoir Simulation." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1902.pdf.

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Pamukcu, Yusuf Ziya. "Simulating Oil Recovery During Co2 Sequestration Into A Mature Oil Reservoir." Master's thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/3/12607418/index.pdf.

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The continuous rising of anthropogenic emission into the atmosphere as a consequence of industrial growth is becoming uncontrollable, which causes heating up the atmosphere and changes in global climate. Therefore, CO2 emission becomes a big problem and key issue in environmental concerns. There are several options discussed for reducing the amount of CO2 emitted into the atmosphere. CO2 sequestration is one of these options, which involves the capture of CO2 from hydrocarbon emission sources, e.g. power plants, the injection and storage of CO2 into deep geological formations, e.g. depleted oil reservoirs. The complexity in the structure of geological formations and the processes involved in this method necessitates the use of numerical simulations in revealing the potential problems, determining feasibility, storage capacity, and life span credibility. Field K having 32o API gravity oil in a carbonate formation from southeast Turkey was studied. Field K was put on production in 1982 and produced until 2006, which was very close to its economic lifetime. Thus, it was considered as a candidate for enhanced oil recovery and CO2 sequestration. Reservoir rock and fluid data was first interpreted with available well logging, core and drill stem test data. Monte Carlo simulation was used to evaluate the probable reserve that was 7 million STB, original oil in place (OOIP). The data were then merged into CMG/STARS simulator. History matching study was done with production data to verify the results of the simulator with field data. After obtaining a good match, the different scenarios were realized by using the simulator. From the results of simulation runs, it was realized that CO2 injection can be applied to increase oil recovery, but sequestering of high amount of CO2 was found out to be inappropriate for field K. Therefore, it was decided to focus on oil recovery while CO2 was sequestered within the reservoir. Oil recovery was about 23% of OOIP in 2006 for field K, it reached to 43 % of OOIP by injecting CO2 after defining production and injection scenarios, properly.

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Susuz, Onur. "Assessment Of Reservoir Rock And Fluid Data For Black Oil Simulation." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/2/12611561/index.pdf.

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Reservoir simulation studies are one of the key tools in an integrated reservoir management study. A successful reservoir simulation application requires representative input data for reservoir rock and fluid properties. This study aims to develop a road map from laboratory measurements to the input data file of reservoir simulation and to make a probabilistic approach for the estimation of unknown parameters. Raw data of reservoir rock and fluid properties of a selected oil field of Turkey will be interpreted and prepared in a way that they will be used as input data of a simulator.

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Papadopoulos, Andreas-Theodoros. "Block smoothed aggregation algebraic multigrid preconditioners for oil reservoir simulation systems." Thesis, University of Oxford, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409174.

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Hird, Kirk B. "A conditional simulation method for reservoir description using geological and well performance constraints /." Access abstract and link to full text, 1993. http://0-wwwlib.umi.com.library.utulsa.edu/dissertations/fullcit/9330024.

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Guehria, Fawzie M. "A new efficient fully integrated approach to compositional reservoir simulation /." Access abstract and link to full text, 1991. http://0-wwwlib.umi.com.library.utulsa.edu/dissertations/fullcit/9203795.

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Books on the topic "Oil reservoir simulation"

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Fanchi, John R. Principles of applied reservoir simulation. Houston, Tex: Gulf Pub., 1997.

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Principles of applied reservoir simulation. 2nd ed. Boston: Gulf Pub., 2001.

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Islam, M. Rafiqul, and Rafiqul Islam. Advanced petroleum reservoir simulation. Hoboken, N.J: Wiley, 2010.

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(Firm), Knovel, ed. Principles of applied reservoir simulation. 3rd ed. Amsterdam: Gulf Professional Pub., 2006.

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Reservoir simulation: Mathematical techniques in oil recovery. Philadelphia, PA: SIAM/Society for Industrial and Applied Mathematics, 2007.

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Lecture notes on applied reservoir simulation. Hackensack, N.J: World Scientific Pub., 2005.

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M, Iqbal Ghulam, and Buchwalter James L, eds. Practical enhanced reservoir engineering: Assisted with simulation software. Tulsa, Okla: PennWell Corp., 2008.

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Chavent, Guy. Mathematical models and finite elements for reservoir simulation: Single phase, multiphase and multicomponent flairs through porous media. Amsterdam: North-Holland, 1986.

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Pointe, P. R. La, and Y. Zee Ma. Uncertainty analysis and reservoir modeling. Tulsa, OK: American Association of Petroleum Geologists, 2011.

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Mazo, Aleksandr, and Konstantin Potashev. The superelements. Modeling of oil fields development. ru: INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1043236.

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This monograph presents the basics of super-element modeling method of two-phase fluid flows occurring during the development of oil reservoir. The simulation is performed in two stages to reduce the spatial and temporal scales of the studied processes. In the first stage of modeling of development of oil deposits built long-term (for decades) the model of the global dynamics of the flooding on the super-element computational grid with a step equal to the average distance between wells (200-500 m). Local filtration flow, caused by the action of geological and technical methods of stimulation, are modeled in the second stage using a special mathematical models using computational grids with high resolution detail for the space of from 0.1 to 10 m and time — from 102 to 105 C. The results of application of the presented models to the solution of practical tasks of development of oil reservoir. Special attention is paid to the issue of value transfer in filtration-capacitive properties of the reservoir, with a detailed grid of the geological model on the larger grid reservoir models. Designed for professionals in the field of mathematical and numerical modeling of fluid flows occurring during the development of oil fields and using traditional commercial software packages, as well as developing their own software. May be of interest to undergraduate and graduate students studying in areas such as "Mechanics and mathematical modeling", "Applied mathematics", "Oil and gas".

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Book chapters on the topic "Oil reservoir simulation"

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Larsen, Jesper, Lars Frellesen, John Jansson, Flemming If, Cliff Addison, Andy Sunderland, and Tim Oliver. "Parallel oil reservoir simulation." In Lecture Notes in Computer Science, 371–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-60902-4_40.

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Ewing, Richard E. "Recent Developments in Reservoir Simulation." In North Sea Oil and Gas Reservoirs — III, 233–46. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0896-6_19.

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Lake, Larry W. "A Marriage of Geology and Reservoir Engineering." In Numerical Simulation in Oil Recovery, 177–98. New York, NY: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-6352-1_13.

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Thompson, Alan M., and Garfield R. Bowen. "Parallelisation of an oil reservoir simulation." In High-Performance Computing and Networking, 20–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61142-8_525.

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Lie, Knut-Andreas, and Bradley T. Mallison. "Mathematical Models for Oil Reservoir Simulation." In Encyclopedia of Applied and Computational Mathematics, 850–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-540-70529-1_277.

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Amaziane, Brahim, and Alain Bourgeat. "Effective Behavior of Two-Phase Flow in Heterogeneous Reservoir." In Numerical Simulation in Oil Recovery, 1–22. New York, NY: Springer US, 1988. http://dx.doi.org/10.1007/978-1-4684-6352-1_1.

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Nybråten, G., E. Skolem, and K. Østby. "II. Reservoir Simulation of the Snorre Field." In North Sea Oil and Gas Reservoirs—II, 103–14. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0791-1_6.

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Bratvedt, Frode, Kyrre Bratvedt, Christian F. Buchholz, Tore Gimse, Helge Holden, Lars Holden, Rudi Olufsen, and Nils Henrik Risebro. "Three-Dimensional Reservoir Simulation Based on Front Tracking." In North Sea Oil and Gas Reservoirs — III, 247–57. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0896-6_20.

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Ran, Qiquan. "Development Characteristics of Tight Oil and Gas Reservoirs." In Unconventional Tight Reservoir Simulation: Theory, Technology and Practice, 1–33. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-32-9848-4_1.

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Henríquez, A., T. Kårstad, and T. Steihaug. "Practical Application of Super-computing in Black-Oil Reservoir Simulation." In North Sea Oil and Gas Reservoirs—II, 445–53. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0791-1_39.

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Conference papers on the topic "Oil reservoir simulation"

1

Huan, G. R. "A Flash Black Oil Model." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 1985. http://dx.doi.org/10.2118/13521-ms.

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Coats, K. H., L. K. Thomas, and R. G. Pierson. "Compositional and Black Oil Reservoir Simulation." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 1995. http://dx.doi.org/10.2118/29111-ms.

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Glimm, James, Shuling Hou, Yoon-ha Lee, David Sharp, and Kenny Ye. "Prediction of Oil Production With Confidence Intervals." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 2001. http://dx.doi.org/10.2118/66350-ms.

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Ghorayeb, Kassem, Manoch Limsukhon, Qasem M. Dashti, and Rafi M. Aziz. "Black Oil Delumping: Running Black Oil Reservoir Simulations and Getting Compositional Wellstreams in the North Kuwait Jurassic Complex." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 2009. http://dx.doi.org/10.2118/118850-ms.

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5

Stone, H. L. "Rigorous Black Oil Pseudo Functions." In SPE Symposium on Reservoir Simulation. Society of Petroleum Engineers, 1991. http://dx.doi.org/10.2118/21207-ms.

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6

Litvak, Michael Lev, and Patrick F. Angert. "Field Development Optimization Applied to Giant Oil Fields." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 2009. http://dx.doi.org/10.2118/118840-ms.

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Kozlova, A., Z. Li, J. R. Natvig, S. Watanabe, Y. Zhou, K. Bratvedt, and S. H. Lee. "A Real-Field Multiscale Black-Oil Reservoir Simulator." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 2015. http://dx.doi.org/10.2118/173226-ms.

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8

Cohen, M. F. "Finite Element Methods for Enhanced Oil Recovery Simulation." In SPE Reservoir Simulation Symposium. Society of Petroleum Engineers, 1985. http://dx.doi.org/10.2118/13512-ms.

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9

Hurst, W. "Unproduced Oil Identified in Reservoir Simulation." In SPE Symposium on Reservoir Simulation. Society of Petroleum Engineers, 1989. http://dx.doi.org/10.2118/18450-ms.

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Li, Heng, Cuong Dang, Arash Mirzabozorg, Chaodong Yang, and Long Nghiem. "Robust Optimization of ASP Flooding Under Oil Price Uncertainty." In SPE Reservoir Simulation Conference. Society of Petroleum Engineers, 2019. http://dx.doi.org/10.2118/193837-ms.

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Reports on the topic "Oil reservoir simulation"

1

Joubert, W., and R. Janardhan. Evaluation of linear solvers for oil reservoir simulation problems. Part 2: The fully implicit case. Office of Scientific and Technical Information (OSTI), December 1997. http://dx.doi.org/10.2172/555364.

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2

Sarkar, A. K., and P. S. Sarathi. Feasibility of steam injection process in a thin, low-permeability heavy oil reservoir of Arkansas -- a numerical simulation study. Office of Scientific and Technical Information (OSTI), December 1993. http://dx.doi.org/10.2172/10115261.

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3

Kamath, V., and S. Godbole. Development of a reservoir simulation for thermal recovery of heavy oils/tar sands in the presence of gas hydrates. Office of Scientific and Technical Information (OSTI), October 1988. http://dx.doi.org/10.2172/5585057.

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4

Kamath, V., and S. Godbole. Development of a reservoir simulation for thermal recovery of heavy oils/tar sands in the presence of gas hydrates. Office of Scientific and Technical Information (OSTI), October 1988. http://dx.doi.org/10.2172/5585057.

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