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2005 News Stories

• GADU/GNARE Uses TeraGrid For Protein Sequence Analysis
• TeraGyroid: Gyroids on the TeraGrid
• TeraShake: Simulating a Big Shake in Southern California Basins
• Seismic Modeling and Oil Reservoir Simulations with TeraGrid
• Improving Groundwater Cleanup Decision-Making with TeraGrid
• Harnessing TeraGrid to the Sky: Understanding Dark Energy
• AMANDA and TeraGrid: Exploring the Violent Universe
• TeraGrid Science Gateways: NanoHUB
• Identifying Brain Disorders with TeraGrid

News

Seismic Modeling and Oil Reservoir Simulations with TeraGrid

While oil prospecting used to rely on hunches and luck, oil companies today demand intelligent ways to surmise the geological features of the ground and choose ideal places for their equipment. Using TeraGrid resources, a multidisciplinary team - led by the University of Texas at Austin's Mary Wheeler, the Ohio State University's Joel Saltz, and Rutgers University's Manish Parashar - is at work on software tools that improve oil reservoir management.

The approach relies on subdividing a hypothetical reservoir into a mesh of blocks. Wells, pumps, and other equipment are associated with individual blocks, and an approximate model of the blocks' fluid dynamics is created. Equipment is moved in order to compare the oil recovery efficiency of different configurations. This process could yield billions of possible configurations, so a dynamic, data-driven optimization system narrows the field. Middleware tools manage the data produced from a rough sampling and identify starting points for more comprehensive searches. Dynamic steering tools allow on-the-fly searches within these subsections. Sophisticated optimization algorithms guide these searches by comparing configurations.

Identifying the best possible configurations requires a massive number of jobs. Because these can run independently, TeraGrid resources at different sites can be used simultaneously NCSA helped port the reservoir simulation and optimization codes to TeraGrid machines and built a toolkit that simplifies execution across multiple systems. The toolkit shows where calculations are taking place, which are complete, which have failed, and which are ongoing - no small feat when orchestrating work across hundreds of processors at multiple sites. They used resources at NCSA, SDSC, Caltech and TACC.

The team completed a set of about 25,000 reservoir optimization runs in less than a week, yielding more than eight terabytes of data stored on NCSA systems, ready to be integrated into the reservoir models. The team is looking to create 10 times that in the short term, and a thorough seismic survey of an area would require petabytes of storage. This research is supported by the National Science Foundation's Information Technology Research program, the Department of Energy, and the Department of Defense.

CAPTION
Visualizations of oil reservoir simulations at various stages in an optimization. Pumps, represented by asterisks, push oil toward wells, represented by small white circles that draw oil from the ground. Blue areas indicate areas of high water concentration. Brown areas indicate areas of high oil concentration. By the end of the simulations, there is not much oil left in the reservoir, and what is left has been swept toward the wells.

Image courtesy of the University of Texas at Austin's Center for Subsurface Modeling and The Ohio State University's Multiscale Computing Lab.

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