Full-GPU Reservoir Simulation Delivers on its Promise for Giant Carbonate Fields

Simulation of carbonate fields presents challenges due to the underlying multi-scale heterogeneities and consequent stiff nature of the flow equations. This paper highlights the principles of a full-GPU (Graphics Processing Unit) reservoir simulator, currently approaching feature parity with traditional CPU-based codes. The approach exhibits fine-grained parallelism beyond that of CPU-based and hybrid CPU-GPU solutions; consequent performance improvements enable modeling of giant carbonate fields with limited computing resources. Additionally, large black-oil models are memory-bound, and GPU bandwidth has shown significant progress with every generational release of new hardware. Performance will keep improving without changes in the code base, which has not been observed with CPU codes in almost two decades.

Computational performance of a full-GPU black-oil reservoir simulator is benchmarked against legacy and modern parallel CPU simulators, for two giant gas and oil carbonate reservoirs. Results for the gas reservoir indicate a ∼7.3x chip-to-chip speed improvement (one GPU vs. to 16 CPU cores), and ∼5.5x for the oil reservoir, both against the fastest reference simulator. These results suggest that full-GPU codes are ready to simulate complex carbonate models of commercial grade, with exceptional performance, which should encourage the industry to pursue research and development efforts geared towards this approach.