Reservoir simulation with scalable grid computing

Abstract

Larger, expandable high performance computing (HPC) clusters which are of different generations and performance speeds are provided for reservoir simulation. This provides scalability and flexibility for running computation-intensive reservoir simulation jobs on HPC machines. Availability of larger numbers of processors in a processor pool makes simulation of giant models possible and also reduces fragmentation when multiple jobs are run. A hardware performance based domain decomposition is performed which results in computation load balancing. The reservoir domain is decomposed efficiently to reduce communication overhead. Adaptive detection of the available mix of computation resources is performed, and reservoir simulation decomposition methodology adjusts the distribution of load based on the available hardware and different processor generation resources to minimize the reservoir simulation runtime.