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• W4229692722 abstract "Parallel Reservoir Simulation on Shared and Distributed Memory System Wei Liu; Wei Liu Baker Atlas GEOScience, Baker Hughes Inc. Search for other works by this author on: This Site Google Scholar Jianwen Cao; Jianwen Cao RDCPS, Academia Sinica Search for other works by this author on: This Site Google Scholar Alberto Mezzatesta; Alberto Mezzatesta Baker Atlas GEOScience, Baker Hughes Inc. Search for other works by this author on: This Site Google Scholar Peng Zhu Peng Zhu RDCPS, Academia Sinica Search for other works by this author on: This Site Google Scholar Paper presented at the International Oil and Gas Conference and Exhibition in China, Beijing, China, November 2000. Paper Number: SPE-64797-MS https://doi.org/10.2118/64797-MS Published: November 07 2000 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Liu, Wei, Cao, Jianwen, Mezzatesta, Alberto, and Peng Zhu. Parallel Reservoir Simulation on Shared and Distributed Memory System. Paper presented at the International Oil and Gas Conference and Exhibition in China, Beijing, China, November 2000. doi: https://doi.org/10.2118/64797-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Oil and Gas Conference and Exhibition in China Search Advanced Search AbstractComputational efficiency is a major subject in large-scale reservoir simulations. Parallel simulation has gained popularity in recent years. Complex geological environments and production management demand new mathematics and science in various computational environments.This paper presented a parallel simulation algorithm and data processing developed for shared and distributed memory systems. The preconditioned Krylov subspace method with hybrid preconditioner based on domain decomposition was constructed to solve the large-scale linear system resulted from black-oil simulator techniques.Based on a fully implicit, three-dimensional, three-phase black-oil reservoir simulator, this project focused on the numerical intensive linear solver. The parallel algorithm is scalable and applicable to both shared and distributed memory systems. Numerical tests were performed on both multi-CPU workstations and PC clusters. A message passing interface (MPI) library was adopted for all message passing functionality in both shared and distributed memory environments. Input/output parallelism and localism are presented in these hardware setups.Numerical results from benchmark models and field application examples are presented for both the multi-CPU SGI Power Challenger and a Linux based Intel PC cluster. Results show that the speedup factor is significant. The simulation performance increases with the number of processors and only decreases due to the limitations introduced by message passing activities.IntroductionComputational efficiency has become more and more important in large-scale reservoir simulation. It is easy to conjecture that this trend will continue in the future. In the last few years, the performance of parallel reservoir simulation research has been significantly improved. Applications of parallel simulator to field cases have been intensively addressed in many publications1–16. However, complex geological environments and production management in large-scale reservoir simulation increasingly demands higher field resolution and larger computational resources.Reservoir simulation uses a numerical material balance approach to generate realistic development scenarios. Complex geological structures, associated with various development schemes, require higher computational efficiency to more realistically characterize the reservoirs. Currently, many large-scale reservoir simulations are still limited by the computer CPU time and memory requirements. Moreover, reservoir description data often comes in finely gridded geostatistical models containing more grid cells than can be efficiently handled. The process of upscaling geostatistical grid cells to coarse reservoir simulation grids has become common practice. However, this limited resolution in describing reservoir models can introduce uncertainties and inaccuracies in simulation results. Keywords: challenger, simulation, preconditioner, memory system, upstream oil & gas, linear system, power challenger, parallel reservoir simulation, communication cost, equation Subjects: Reservoir Simulation This content is only available via PDF. 2000. Society of Petroleum Engineers You can access this article if you purchase or spend a download." @default.
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• W4229692722 title "Parallel Reservoir Simulation on Shared and Distributed Memory System" @default.
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