Research on 1-D forward modeling and inversion of TEM Considering induced polarization effects
The transient electromagnetic (TEM) method, as an efficient geophysical exploration technique, plays a crucial role in mineral resource exploration, environmental engineering, and geological hazard assessment. TEM forward modeling and inversion sometimes neglect the subsurface medium's induced...
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| Published in: | Journal of applied geophysics Vol. 241; p. 105844 |
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| Format: | Journal Article |
| Language: | English |
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Elsevier B.V
01.10.2025
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| ISSN: | 0926-9851 |
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| Abstract | The transient electromagnetic (TEM) method, as an efficient geophysical exploration technique, plays a crucial role in mineral resource exploration, environmental engineering, and geological hazard assessment. TEM forward modeling and inversion sometimes neglect the subsurface medium's induced polarization (IP) effects. This may result in inaccurate interpretation of the subsurface electrical structure. To address this issue, this study conducts TEM forward modeling and inversion incorporating IP effects, aiming to improve TEM data's inversion accuracy and interpretability under geological conditions involving polarizable bodies. First, based on the Cole-Cole complex resistivity model, 1-D TEM forward modeling considering IP effects is implemented, and the accuracy and reliability of the algorithm are validated. Subsequently, nonlinear optimization algorithms are applied to process TEM data during the inversion, with a focus on comparing and analyzing the inversion performance of the particle swarm optimization (PSO) algorithm and the velocity pausing particle swarm optimization (VPPSO) algorithm in some layered medium models. The results demonstrate that although the computational efficiency of the VPPSO algorithm is slightly lower than that of the PSO algorithm, it exhibits significant advantages in convergence speed, global search capability, and noise resistance. Finally, inversion experiments using field data further validate the effectiveness and practicality of the VPPSO algorithm. The research works in this article provide new methods for TEM exploration of subsurface polarizable bodies.
•Develop 1D forward modeling algorithm accounting for IP effects.•Use nonlinear optimization for 1D inversion with polarization considerations.•Apply VPPSO inversion to measured data, reflecting surface electrical structure accurately. |
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| AbstractList | The transient electromagnetic (TEM) method, as an efficient geophysical exploration technique, plays a crucial role in mineral resource exploration, environmental engineering, and geological hazard assessment. TEM forward modeling and inversion sometimes neglect the subsurface medium's induced polarization (IP) effects. This may result in inaccurate interpretation of the subsurface electrical structure. To address this issue, this study conducts TEM forward modeling and inversion incorporating IP effects, aiming to improve TEM data's inversion accuracy and interpretability under geological conditions involving polarizable bodies. First, based on the Cole-Cole complex resistivity model, 1-D TEM forward modeling considering IP effects is implemented, and the accuracy and reliability of the algorithm are validated. Subsequently, nonlinear optimization algorithms are applied to process TEM data during the inversion, with a focus on comparing and analyzing the inversion performance of the particle swarm optimization (PSO) algorithm and the velocity pausing particle swarm optimization (VPPSO) algorithm in some layered medium models. The results demonstrate that although the computational efficiency of the VPPSO algorithm is slightly lower than that of the PSO algorithm, it exhibits significant advantages in convergence speed, global search capability, and noise resistance. Finally, inversion experiments using field data further validate the effectiveness and practicality of the VPPSO algorithm. The research works in this article provide new methods for TEM exploration of subsurface polarizable bodies.
•Develop 1D forward modeling algorithm accounting for IP effects.•Use nonlinear optimization for 1D inversion with polarization considerations.•Apply VPPSO inversion to measured data, reflecting surface electrical structure accurately. |
| ArticleNumber | 105844 |
| Author | Fu, Nengyi Xu, Zhengyu Fu, Zhihong Wu, Muyang Yuan, Zhanbo |
| Author_xml | – sequence: 1 givenname: Zhanbo surname: Yuan fullname: Yuan, Zhanbo organization: School of Electrical Engineering, Chongqing University, Chongqing 400044, China – sequence: 2 givenname: Muyang surname: Wu fullname: Wu, Muyang email: muyangwu@qq.com organization: School of Electrical Engineering, Chongqing University, Chongqing 400044, China – sequence: 3 givenname: Nengyi surname: Fu fullname: Fu, Nengyi organization: Department of Electrical and Computer Engineering, University of Tulsa, OK 74115, USA – sequence: 4 givenname: Zhengyu surname: Xu fullname: Xu, Zhengyu email: xuzhengyu@cqu.edu.cn organization: School of Electrical Engineering, Chongqing University, Chongqing 400044, China – sequence: 5 givenname: Zhihong surname: Fu fullname: Fu, Zhihong organization: School of Electrical Engineering, Chongqing University, Chongqing 400044, China |
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| Keywords | Transient electromagnetic (TEM) method Inversion 1-D forward modeling Induced polarization (IP) effects Nonlinear optimization algorithm |
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