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ExxonMobil sets record in high performance oil and gas reservoir computing
ExxonMobil, working with the National Center for Supercomputing Applications (NCSA), has achieved a major breakthrough with proprietary software using more than four times the previous number of processors used on complex oil and gas reservoir simulation models to improve exploration and production results.
As announced in February 2017, the breakthrough in parallel simulation used 716,800 processors, the equivalent of harnessing the power of 22,400 computers with 32 processors per computer. ExxonMobil geoscientists and engineers can now make better investment decisions by more efficiently predicting reservoir performance under geological uncertainty to assess a higher volume of alternative development plans in less time.
The record run resulted in data output thousands of times faster than typical oil and gas industry reservoir simulation. It was the largest number of processor counts reported by the oil and gas industry, and one of the largest simulations reported by industry in engineering disciplines such as aerospace and manufacturing.
The major breakthrough in parallel simulation results in dramatic reductions in the amount of time previously taken to study oil and gas reservoirs. Reservoir simulation studies are used to guide decisions such as well placement, the design of facilities and development of operational strategies to minimize financial and environmental risk. To model complex processes accurately for the flow of oil, water, and natural gas in the reservoir, simulation software must solve a number of complex equations. Current reservoir management practices in the oil and gas industry are often hampered by the slow speed of reservoir simulation.
ExxonMobil’s scientists worked closely with the NCSA to benchmark a series of multi-million to billion cell models on NCSA’s Blue Waters Super Computer. This new reservoir simulation capability efficiently uses hundreds of thousands of processors simultaneously and will have dramatic impact on reservoir management workflows.