Inversion of electric field component E_x in the SOTEM method based on the improved particle swarm optimization algorithm

Authors

ZHANG Jifeng, College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China; National Engineering Research Center for Offshore Oil and Gas Exploration, Beijing 100028, China; Integrated Geophysical Simulation Lab of Chang’an University, Xi’an 710054, ChinaFollow
CHEN Changjian, College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
LI Yuteng, CCTEG Xi’an Research Institute (Group) Co., Ltd., Xi’an 710077, China; CCTEG China Coal Research Institute, Beijing 100013, ChinaFollow
YOU Xiran, College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China
MA Ziben, College of Geological Engineering and Geomatics, Chang’an University, Xi’an 710054, China

Abstract

Objective The inversion of the horizontal electric field component in the grounded-source short offset transient electromagnetic (SOTEM) method using traditional algorithms is prone to fall into local extrema. To address this challenge, this study proposed an improved particle swarm optimization (PSO) algorithm that integrates the center of gravity reverse learning strategy. Methods Based on the center of gravity reverse learning strategy, the improved PSO algorithm can dynamically adjust learning factors and the value of the adaptive inertia weight, thus improving the global search capability and convergence efficiency effectively. The performance of the improved PSO algorithm was verified using the typical three-, five-, and seven-layered geoelectric models constructed in this study.Results and Conclusions The results of this study indicate that for the five- and seven-layered geoelectric models, the damped least squares method yielded average inversion errors of 0.34% and 4.68%, respectively, while the improved PSO algorithm yielded average inversion errors of 0.21% and 0.87%, respectively. This suggests that the improved PSO algorithm significantly improved the identification accuracy of complex geoelectric structures. Under the conditions of multi-layer (≥5) initial inversion intervals and wide search intervals, the improved PSO algorithm yielded average inversion errors of less than 5% for both three- and five-layered geoelectric models, substantiating its effectiveness. Inversion was conducted for the measured data from a certain mining area using the damped least squares method and the improved PSO algorithm. The inversion results demonstrate that the improved PSO algorithm outperformed the damped least squares method, with the inversion results of the improved PSO algorithm agreeing well with the electrical structure of the known ore body. The results of this study will provide theoretical support for improving the resolution of SOTEM in mineral exploration.

Keywords

grounded-source short-offset transient electromagnetic (SOTEM) method, particle swarm optimization (PSO) algorithm, inversion, electric field component Ex

DOI

10.12363/issn.1001-1986.24.11.0702

Recommended Citation

ZHANG Jifeng, CHEN Changjian, LI Yuteng, et al. (2025) "Inversion of electric field component E_x in the SOTEM method based on the improved particle swarm optimization algorithm," Coal Geology & Exploration: Vol. 53: Iss. 4, Article 19.
DOI: 10.12363/issn.1001-1986.24.11.0702
Available at: https://cge.researchcommons.org/journal/vol53/iss4/19

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