Concealed structure identification by mining‐induced strata behavior based on microseismic monitoring

Abstract

Concealed structures in underground coal mines pose significant hazards by concentrating stress and facilitating fluid inrush, making their detection particularly challenging in complex mining environments. This study presents a novel approach that combines microseismic (MS) monitoring, channel wave seismic (CWS) detection, and stress simulation to identify concealed structures. By leveraging real-time seismic signatures of rock fracturing and guided wave propagation in the coal seam, along with stress-field modeling, this multi-modal technique effectively detects and cross-validates structural anomalies. In a case study, the spatiotemporal evolution of recorded MS events revealed two distinct clusters of seismicity and energy release. One of these clusters, located in an area where no faults were previously mapped, led to the prediction of a concealed structure characterized by abnormal stress fields and incipient fault activation. CWS surveys further identified guided wave propagation anomalies in the same zone, consistent with disruptions in the coal seam caused by a fault. Stress field modeling confirmed that only the model incorporating a concealed structure produced stress concentration patterns that aligned with the observed MS energy density distribution. This consistency between observed MS energy density and simulated stress concentrations strongly supported the fault hypothesis. The integrated method was validated through physical exploration, which confirmed previously hidden small normal faults in the predicted zone. The results demonstrate that combining real-time microseismic monitoring of rock fracture events, stress-field modeling, and CWS detection provides an effective tool for the early identification of concealed geological faults.