Advanced three-dimensional electromagnetic modelling using a nested integral equation approach. Issue 1 (19th February 2021)

• Record Type: Journal Article
• Authors: Chen, Chaojian; Kruglyakov, Mikhail; Kuvshinov, Alexey
• Is Part Of: Geophysical journal international. Volume 226:Issue 1(2021)
• Page Start: 114
• Page End: 130
• Publication Date: 2021-02-19
• Subjects: Electromagnetic theory -- Geomagnetic induction -- Magnetotellurics -- Numerical modelling; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggab072
• Languages: English
• ISSNs: 0956-540X

Abstract

SUMMARY: Most of the existing 3-D electromagnetic (EM) modelling solvers based on the integral equation (IE) method exploit fast Fourier transform (FFT) to accelerate the matrix–vector multiplications. This in turn requires a laterally uniform discretization of the modelling domain. However, there is often a need for multiscale modelling and inversion, for instance, to properly account for the effects of non-uniform distant structures and, at the same time, to accurately model the effects from local anomalies. In such scenarios, the usage of laterally uniform grids leads to excessive computational loads, in terms of both memory and time. To alleviate this problem, we developed an efficient 3-D EM modelling tool based on a multinested IE approach. Within this approach, the IE modelling is first performed at a large domain and on a (laterally uniform) coarse grid, and then the results are refined in the region of interest by performing modelling at a smaller domain and on a (laterally uniform) denser grid. At the latter stage, the modelling results obtained at the previous stage are exploited. The lateral uniformity of the grids at each stage allows us to keep using the FFT for the acceleration of matrix–vector multiplications. An important novelty of the paper is the development of a 'rim domain' concept that further improves the performance of the multinested IE approach. We verify the developed tool on both idealized and realistic 3-D conductivity models, and demonstrate its efficiency and accuracy.