Microseismic monitoring technology is widely used in mine ground pressure monitoring as an effective non-destructive method, but the traditional underground microseismic monitoring method is complicated to install and costly. To make the installation of geophones easy and to reduce the cost, a surface microseismic system is used in this paper to monitor microseismic events. In addition, our group has developed a microseismic signal processing software (MS software), which can collect the microseismic events, signal denoising, location, and source parameter calculation. To improve the location accuracy of microseismic events, a source-scanning algorithm (SSA) for microseismic event localization integrates a differential evolution (DE) algorithm to improve computational efficiency and is embedded into the MS software. In this location algorithm, a stratified velocity model is obtained using cross-hole transmission acoustic logging, replacing the conventional single average velocity model. Then, the SSA optimized by the DE algorithm is used to locate the microseismic events, and the localized locations are verified against known blast locations. Finally, to interpret and quantify the microseismic hazards induced by mining, the source parameters of microseismic events are analyzed. The study shows that this algorithm has high location accuracy, with errors ranging between 18.10 and 40.75 m when comparing the location coordinates to known blasting events. The microseismic events are mainly distributed in the shallow F1 fault zone and two locations at 800 to 1000 m depth due to the influence of the combined tectonic and construction disturbances. The moment magnitude Mw of microseismic events at depths of 800 to 1000 m is larger than that of those at the shallow F1 fault zone. At the same moment magnitude Mw, the corner frequency fc and stress drop ∆σ are larger, and the source radius rc is smaller for the deeper microseismic events. The linear growth rate of the source radius rc with moment magnitude Mw is greater for microseismic events at the shallow F1 fault zone than for those at depths of 800 to 1000 m. The study found that stress drop increases with depth, likely due to higher in-situ stress and rock strength at greater depths, which facilitate more abrupt failure and greater stress release during rupture. Microseismic events with large stress drops are more likely to be associated with stronger rockbursts at those locations. Consequently, monitoring stress drop can improve early warning systems for rockburst events.

Microseismic Source Location Method and Microseismic Event Source Parameter Characteristic Analysis for Surface Microseismic System

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发表日期：

2025年7月29日

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Chang Wang,
Xingdong Zhao,
Qiankun Zhu,
Wenlong Yu,
Tong Wu

摘要

Microseismic monitoring technology is widely used in mine ground pressure monitoring as an effective non-destructive method, but the traditional underground microseismic monitoring method is complicated to install and costly. To make the installation of geophones easy and to reduce the cost, a surface microseismic system is used in this paper to monitor microseismic events. In addition, our group has developed a microseismic signal processing software (MS software), which can collect the microseismic events, signal denoising, location, and source parameter calculation. To improve the location accuracy of microseismic events, a source-scanning algorithm (SSA) for microseismic event localization integrates a differential evolution (DE) algorithm to improve computational efficiency and is embedded into the MS software. In this location algorithm, a stratified velocity model is obtained using cross-hole transmission acoustic logging, replacing the conventional single average velocity model. Then, the SSA optimized by the DE algorithm is used to locate the microseismic events, and the localized locations are verified against known blast locations. Finally, to interpret and quantify the microseismic hazards induced by mining, the source parameters of microseismic events are analyzed. The study shows that this algorithm has high location accuracy, with errors ranging between 18.10 and 40.75 m when comparing the location coordinates to known blasting events. The microseismic events are mainly distributed in the shallow F1 fault zone and two locations at 800 to 1000 m depth due to the influence of the combined tectonic and construction disturbances. The moment magnitude M_w of microseismic events at depths of 800 to 1000 m is larger than that of those at the shallow F1 fault zone. At the same moment magnitude M_w, the corner frequency f_c and stress drop ∆σ are larger, and the source radius r_c is smaller for the deeper microseismic events. The linear growth rate of the source radius r_c with moment magnitude M_w is greater for microseismic events at the shallow F1 fault zone than for those at depths of 800 to 1000 m. The study found that stress drop increases with depth, likely due to higher in-situ stress and rock strength at greater depths, which facilitate more abrupt failure and greater stress release during rupture. Microseismic events with large stress drops are more likely to be associated with stronger rockbursts at those locations. Consequently, monitoring stress drop can improve early warning systems for rockburst events.