A comparison of mixed multiscale finite element methods for multiphase transport in highly heterogeneous media

TL;DR

This paper systematically compares two mixed multiscale finite element methods for simulating multiphase transport in highly heterogeneous media, focusing on their accuracy and computational efficiency using the SPE10 benchmark.

Contribution

The paper provides a comprehensive comparison of MMsFEM and MGMsFEM, highlighting their differences in basis functions, accuracy, and computational costs in a complex three-dimensional benchmark.

Findings

Both methods achieve good accuracy in simulations.

MGMsFEM with online basis functions offers improved accuracy.

Computational costs vary depending on basis function complexity.

Abstract

In this paper, we systemically review and compare two mixed multiscale finite element methods (MMsFEM) for multiphase transport in highly heterogeneous media. In particular, we will consider the mixed multiscale finite element method using limited global information, simply denoted by MMsFEM, and the mixed generalized multiscale finite element method (MGMsFEM) with residual driven online multiscale basis functions. Both methods are under the framework of mixed multiscale finite element methods, where the pressure equation is solved in the coarse grid with carefully constructed multiscale basis functions for the velocity. The multiscale basis functions in both methods include local and global media information. In terms of MsFEM using limited global information, only one multiscale basis function is utilized in each local neighborhood while multiple basis are used in MGMsFEM. We will test and compare these two methods using the benchmark three-dimensional SPE10 model. A range of coarse grid sizes and different combinations of basis functions (offline and online) will be considered with CPU time reported for each case. In our numerical experiments, we observe good accuracy by the two above methods. Finally, we will discuss and compare the advantages and disadvantages of the two methods in terms of accuracy and computational costs.