Mechanism of time-lapse electrical resistivity tomography (ERT) response to mining-induced fracture evolution in shallow coal seams: a coupled DEM-FEM study

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Authors: Yuteng Li, Jianyuan Cheng, Zhengfei Wu, Jiajia Zhao
Cited by: 0
References: 14

Abstract

Introduction Dynamic monitoring of the Water Flowing Fractured Zone (WCFZ) is critical for preventing water hazards in shallow coal seams, yet mapping the complex spatiotemporal evolution of mining-induced fractures to electrical signals remains challenging. Methods This study proposes a time-lapse electrical forward modeling strategy coupling Discrete Element Method (DEM) and Finite Element Method (FEM) via Digital Image Processing (DIP). A UDEC “Brick” meshing strategy was employed to simulate overburden mechanics, while a DIP-based pixel mapping technique reconstructed true resistivity models preserving geometric anisotropy for Pole-Dipole simulations in COMSOL. Results Results reveal the “vertical initiation-penetration-compaction recovery” mechanism and its distinct electrical signatures. Specifically, the full penetration stage (220 m) forms short-circuit channels inducing strong low-resistivity anomalies. In the stable mining stage (400 m), the apparent resistivity section exhibits a typical “strong-side, weak-center” differentiation controlled by the “O-ring” theory. Quantitative imaging of time-lapse resistivity change rate confirms that boundary tensile zones maintain a high negative change rate of approximately -40%, while the central compacted zone recovers to about -10%. Discussion This study validates the feasibility of using time-lapse electrical resistivity tomography (ERT) to quantitatively evaluate the “damage-recovery” state of the goaf, providing a theoretical basis for precise water hazard monitoring.

Fields of Study & Subjects

Geophysical and Geoelectrical Methods Geoscience and Mining Technology Electrical and Bioimpedance Tomography

Publication details

Journal / source
Frontiers in Earth Science
Volume
14
Publication date
27 February 2026
Language
EN