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Open AccessArticle

Parallel Simulation of Audio- and Radio-Magnetotelluric Data

1
Center for Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Moscow 191205, Russia
2
Applied Computational Geophysics Lab, Moscow Institute of Physics and Technology, Dolgoprudny 141701, Russia
3
Institute of Earth Sciences, Saint-Petersburg University, St. Petersburg 199034, Russia
*
Author to whom correspondence should be addressed.
Minerals 2020, 10(1), 42; https://doi.org/10.3390/min10010042
Received: 22 November 2019 / Revised: 25 December 2019 / Accepted: 27 December 2019 / Published: 31 December 2019
(This article belongs to the Special Issue Geophysics for Mineral Exploration)
This paper presents a novel numerical method for simulation controlled-source audio-magnetotellurics (CSAMT) and radio-magnetotellurics (CSRMT) data. These methods are widely used in mineral exploration. Interpretation of the CSAMT and CSRMT data collected over an area with the complex geology requires application of effective methods of numerical modeling capable to represent the geoelectrical model of a deposit well. In this paper, we considered an approach to 3D electromagnetic (EM) modeling based on new types of preconditioned iterative solvers for finite-difference (FD) EM simulation. The first preconditioner used fast direct inversion of the layered Earth FD matrix (Green’s function preconditioner). The other combined the first with a contraction operator transformation. To illustrate the effectiveness of the developed numerical modeling methods, a 3D resistivity model of Aleksandrovka study area in Kaluga Region, Russia, was prepared based on drilling data, AMT, and a detailed CSRMT survey. We conducted parallel EM simulation of the full CSRMT survey. Our results indicated that the developed methods can be effectively used for modeling EM responses over a realistic complex geoelectrical model for a controlled source EM survey with hundreds of receiver stations. The contraction-operator preconditioner outperformed the Green’s function preconditioner by factor of 7–10, both with respect to run-time and iteration count, and even more at higher frequencies. View Full-Text
Keywords: geophysical electromagnetic modelling; CSAMT; CSRMT; CSEM geophysical electromagnetic modelling; CSAMT; CSRMT; CSEM
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Yavich, N.; Malovichko, M.; Shlykov, A. Parallel Simulation of Audio- and Radio-Magnetotelluric Data. Minerals 2020, 10, 42.

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