Parallel fully implicit chemical potential-based modeling of unconventional shale gas reservoirs

Gang Qiu, Haijian Yang, Jisheng Kou, Shuyu Sun

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The design of novel mathematical models and state-of-the-art simulators for unconventional shale gas reservoirs plays an increasingly important role in the current energy mix of the world’s growing energy demand. In this paper, we present a robust and scalable framework, which is based on the chemical potential-based modeling and the fully implicit method (FIM), to model and simulate this highly nonlinear flow transport problem on a large scale. In the proposed approach, a thermodynamically consistent mathematical model of gas flow in shale formations, which employs the gas density and the chemical potential gradient, is developed to satisfy the second law of thermodynamics and meanwhile guarantee the energy dissipation property. And then the family of fully implicit finite element algorithms is utilized to accurately capture the complicated flow physics behind the transport process in shale media on high resolution grids. In particular, our approach further enhances the numerical formulation by proposing the family of Newton–Krylov methods for efficiently computing, and the parallel implementation of the simulator is achieved by using the domain decomposition technique. Numerical experiments are presented to demonstrate the robustness and parallel scalability of the solution strategies for several interesting shale gas flow problems in two or three dimensions. With the proposed parallel method, large-scale reservoir simulation can be obtained on the Shaheen-II supercomputer with up to 40 960 processors, which enables to achieve a good strong scalability by saving more than 90 percent of computing time, when the problem size is enlarged to hundreds of millions of degrees of freedom.
Original languageEnglish (US)
Pages (from-to)211531
JournalGeoenergy Science and Engineering
StatePublished - Feb 16 2023


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