An efficient cascadic multigrid solver for 3-D magnetotelluric forward modelling problems using potentials

Author:

Pan Kejia1ORCID,Wang Jinxuan1,Hu Shuanggui1ORCID,Ren Zhengyong2ORCID,Cui Tao3,Guo Rongwen2ORCID,Tang Jingtian2

Affiliation:

1. School of Mathematics and Statistics, Central South University, Changsha 410083, China

2. School of Geosciences and Info-Physics, Central South University, Changsha 410083, China

3. NCMIS, LSEC, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China

Abstract

SUMMARY The fast and accurate 3-D magnetotelluric (MT) forward modelling is core engine of the interpretation and inversion of MT data. In this study, we develop an improved extrapolation cascadic multigrid method (EXCMG) to solve the large sparse complex linear system arising from the finite-element (FE) discretization on non-uniform orthogonal grids of the Maxwell’s equations using potentials. First, the vector Helmholtz equation and the scalar auxiliary equation are derived from the Maxwell’s equations using Coulomb-gauged potentials. The weighted residual method is adopted to discretize the weak formulation and assemble the FE equation. Secondly, carefully choosing the preconditioned complex stable bi-conjugate gradient method (BiCGStab) as multigrid smoother, we develop an improved EXCMG method on non-uniform grids to solve the resulting large sparse complex non-Hermitian linear systems. Finally, several examples including three standard testing models (COMMEMI3D-1, COMMEMI3D-2 and DTM1.0) and a topographic model are used to validate the accuracy and efficiency of the proposed multigrid solver. Numerical results show that the proposed EXCMG algorithm greatly improves the efficiency of 3-D MT forward modelling, is more efficient than some existing solvers, such as Pardiso, incomplete LU factorization preconditioned biconjugate gradients stabilized method (ILU-BiCGStab) and flexible generalized minimum residual method with auxiliary space Maxwell preconditioner (FGMRES-AMS), and capable to simulate large-scale problems with more than 100 million unknowns.

Funder

National Natural Science Foundation of China

Central South University

Publisher

Oxford University Press (OUP)

Subject

Geochemistry and Petrology,Geophysics

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