An improved multistage preconditioner on GPUs for compositional reservoir simulation

Abstract

The compositional model is often used to describe multicomponent multiphase porous media flows in the petroleum industry. The fully implicit method with strong stability and weak constraints on time-step sizes is commonly used in mainstream commercial reservoir simulators. In this paper, we develop an efficient multistage preconditioner for the fully implicit compositional flow simulation. The method employs an adaptive setup phase to improve the parallel efficiency on GPUs. Furthermore, a multicolor Gauss–Seidel algorithm based on the adjacency matrix is applied in the algebraic multigrid methods for the pressure part. Numerical results demonstrate that the proposed algorithm achieves good parallel speedup while yielding the same convergence behavior as the corresponding sequential version.