Comprehensive evaluation of rockburst risk by multiparameter characteristics based on microseismic signals: A case study

Abstract Nowadays, the seismological monitoring system in China is a valuable tool in the rockburst risk evaluation for deep coal mines. In the past, only parameters, like source location and energy, are widely used to estimate the risk level of rockburst. Sometimes, it is effective; however, some other important physical parameters, such as apparent stress drop, static stress drop, P‐wave velocity, and moment tensor, should also be included in order to improve the accuracy of risk assessment. In this study, these parameters are calculated using mine tremor signals recorded in the LW35001 workface of Liangbaosi Coal Mine. These calculations provide an overall identification of periodical stress distribution and rock mass energy‐releasing type under high concentrated stress. Via linear moment tensor inversion procedure, the source mechanism of mine tremors and stress state of the rock mass is determined whether it is risk or not to underground roadway. This comprehensive analysis provides a specific guidance for rockburst prevention for coal mine management, that is, knowing when and where measures must be taken to decrease the risk level or induce the occurrence of rockburst under control.

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Publication Details

Journal
Energy Science & Engineering
Published
2024-10-01
DOI
https://doi.org/10.1002/ese3.1909
Primary Topic
Rock Mechanics and Modeling
Type
article
Field-Weighted Citation Impact
0.00
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article

Comprehensive evaluation of rockburst risk by multiparameter characteristics based on microseismic signals: A case study

Shun Hu, Rupei Zhang, Xinyuan Tian, Xiufeng Zhang et al.
Energy Science & Engineering
Rock Mechanics and Modeling
article

Comprehensive evaluation of rockburst risk by multiparameter characteristics based on microseismic signals: A case study

Shun Hu, Rupei Zhang, Xinyuan Tian, Xiufeng Zhang, Yong‐yuan Li
article en

Abstract

Abstract Nowadays, the seismological monitoring system in China is a valuable tool in the rockburst risk evaluation for deep coal mines. In the past, only parameters, like source location and energy, are widely used to estimate the risk level of rockburst. Sometimes, it is effective; however, some other important physical parameters, such as apparent stress drop, static stress drop, P‐wave velocity, and moment tensor, should also be included in order to improve the accuracy of risk assessment. In this study, these parameters are calculated using mine tremor signals recorded in the LW35001 workface of Liangbaosi Coal Mine. These calculations provide an overall identification of periodical stress distribution and rock mass energy‐releasing type under high concentrated stress. Via linear moment tensor inversion procedure, the source mechanism of mine tremors and stress state of the rock mass is determined whether it is risk or not to underground roadway. This comprehensive analysis provides a specific guidance for rockburst prevention for coal mine management, that is, knowing when and where measures must be taken to decrease the risk level or induce the occurrence of rockburst under control.

Energy Science & EngineeringVol. 12(10)
China University of Mining and Technology (CN), Huaneng Clean Energy Research Institute (CN), Shandong Lianxing Energy Group (China) (CN)
Openalex Percentile: Top 82%
Rock Mechanics and Modeling
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Comprehensive evaluation of rockburst risk by multiparameter characteristics based on microseismic signals: A case study — Shun Hu, Rupei Zhang, et al. · Energy Science & Engineering (2024) | TGRS Research Map | TGRS