A two-grid preconditioner with an adaptive coarse space for flow simulations in highly heterogeneous media

TL;DR

This paper introduces a robust two-grid preconditioner with an adaptive spectral coarse space for efficient flow simulations in highly heterogeneous porous media, improving convergence and mass conservation.

Contribution

It develops a novel two-grid preconditioner with an adaptive spectral coarse space based on GMsFEM for flow problems in heterogeneous media.

Findings

Preconditioner is highly robust across different flow scenarios.

Numerical results demonstrate improved efficiency and convergence.

Effective in both Darcy and two-phase flow simulations.

Abstract

In this paper, we consider flow simulation in highly heterogeneous media that has many practical applications in industry. To enhance mass conservation, we write the elliptic problem in a mixed formulation and introduce a robust two-grid preconditioner to seek the solution. We first need to transform the indefinite saddle problem to a positive definite problem by preprocessing steps. The preconditioner consists of a local smoother and a coarse preconditioner. For the coarse preconditioner, we design an adaptive spectral coarse space motivated by the GMsFEM (Generalized Multiscale Finite Element Method). We test our preconditioner for both Darcy flow and two phase flow and transport simulation in highly heterogeneous porous media. Numerical results show that the proposed preconditioner is highly robust and efficient.