An Efficient and Scalable Finite Element Method for 3-D Transient Electromagnetic Forward Modeling Using a Robust Iterative Solver

The transient electromagnetic method (TEM) is a widely used technique for metallic mineral, geothermal, and other natural resource exploration. With the continuous development of exploration technologies, the demand for accurate subsurface models and broader application environments presents significant challenges for the forward modeling of TEM, necessitating higher precision forward modeling strategies and faster computation methods. This paper proposes a subspace iterative solution method based on flexible generalized minimal residual(FGMRES) method, utilizing domain decomposition method for parallel acceleration. Specifically, we optimized the grid for long-period transient electromagnetic response calculations, selecting a set of highly adaptable modeling parameters that reduce grid degrees of freedom without compromising accuracy. Furthermore, we replaced the commonly used second-order schemes with a third-order backward Euler difference scheme and conducted forward modeling tests with different time steps, resulting in a more reasonable time step length that improves computational efficiency. The effectiveness of the algorithm was validated by comparing the layered model with semi-analytical solutions and the three-dimensional model with previous results. The comparison results with other open-source codes and numerical experiments on large-scale models indicate that our method achieves high accuracy and efficiency for both simple and complex models, while requiring relatively less memory.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Geoscience and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/tgrs.2025.3594486
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

An Efficient and Scalable Finite Element Method for 3-D Transient Electromagnetic Forward Modeling Using a Robust Iterative Solver

Zhengguang Liu, Yu Gu, Xin Gao, Chaojian Chen et al.
IEEE Transactions on Geoscience and Remote Sensing
Structural Health Monitoring Techniques
article

An Efficient and Scalable Finite Element Method for 3-D Transient Electromagnetic Forward Modeling Using a Robust Iterative Solver

Zhengguang Liu, Yu Gu, Xin Gao, Chaojian Chen, Ruijin Kong, Zhuo Chen, Xiao Xiao, Jingtian Tang
article en

Abstract

The transient electromagnetic method (TEM) is a widely used technique for metallic mineral, geothermal, and other natural resource exploration. With the continuous development of exploration technologies, the demand for accurate subsurface models and broader application environments presents significant challenges for the forward modeling of TEM, necessitating higher precision forward modeling strategies and faster computation methods. This paper proposes a subspace iterative solution method based on flexible generalized minimal residual(FGMRES) method, utilizing domain decomposition method for parallel acceleration. Specifically, we optimized the grid for long-period transient electromagnetic response calculations, selecting a set of highly adaptable modeling parameters that reduce grid degrees of freedom without compromising accuracy. Furthermore, we replaced the commonly used second-order schemes with a third-order backward Euler difference scheme and conducted forward modeling tests with different time steps, resulting in a more reasonable time step length that improves computational efficiency. The effectiveness of the algorithm was validated by comparing the layered model with semi-analytical solutions and the three-dimensional model with previous results. The comparison results with other open-source codes and numerical experiments on large-scale models indicate that our method achieves high accuracy and efficiency for both simple and complex models, while requiring relatively less memory.

IEEE Transactions on Geoscience and Remote SensingVol. 63
Central South University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 80%
Structural Health Monitoring Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.