Constraint Energy Minimizing Generalized Multiscale Finite Element Method for multi-continuum Richards equations

TL;DR

This paper introduces a novel multiscale finite element method combining constraint energy minimization with GMsFEM to efficiently solve complex nonlinear multi-continuum Richards equations in heterogeneous fractured media, demonstrating accurate results with minimal basis functions.

Contribution

The paper develops a new multiscale approach using CEM-GMsFEM for nonlinear multi-continuum Richards equations, including novel basis function construction and theoretical convergence analysis.

Findings

Error converges with coarse-grid size alone

Few oversampling layers and basis functions suffice

Method effectively captures high-contrast channels

Abstract

In fluid flow simulation, the multi-continuum model is a useful strategy. When the heterogeneity and contrast of coefficients are high, the system becomes multiscale, and some kinds of reduced-order methods are demanded. Combining these techniques with nonlinearity, we will consider in this paper a dual-continuum model which is generalized as a multi-continuum model for a coupled system of nonlinear Richards equations as unsaturated flows, in complex heterogeneous fractured porous media; and we will solve it by a novel multiscale approach utilizing the constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM). In particular, such a nonlinear system will be discretized in time and then linearized by Picard iteration (whose global convergence is proved theoretically). Subsequently, we tackle the resulting linearized equations by the CEM-GMsFEM and obtain proper offline multiscale basis functions to span the multiscale space (which contains the pressure solution). More specifically, we first introduce two new sources of samples, and the GMsFEM is used over each coarse block to build local auxiliary multiscale basis functions via solving local spectral problems, that are crucial for detecting high-contrast channels. Second, per oversampled coarse region, local multiscale basis functions are created through the CEM as constrainedly minimizing an energy functional. Various numerical tests for our approach reveal that the error converges with the coarse-grid size alone and that only a few oversampling layers, as well as basis functions, are needed.