Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powe...Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.展开更多
Fault is a common geological structure that has been revealed in the process of underground coal excavation and mining.The nature of its discontinuous structure controls the deformation,damage,and mechanics of the coa...Fault is a common geological structure that has been revealed in the process of underground coal excavation and mining.The nature of its discontinuous structure controls the deformation,damage,and mechanics of the coal or rock mass.The interaction between this discontinuous structure and mining activities is a key factor that dominates fault reactivation and the coal burst it can induce.This paper first summarizes investigations into the relationships between coal mining layouts and fault occurrences,along with relevant conceptual models for fault reactivation.Subsequently,it proposes mechanisms of fault reactivation and its induced coal burst based on the superposition of static and dynamic stresses,which include two kinds of fault reactivations from:mining-induced quasi-static stress(FRMSS)-dominated and seismic-based dynamic stress(FRSDS)-dominated.These two kinds of fault reactivations are then validated by the results of experimental investigations,numerical modeling,and in situ microseismic monitoring.On this basis,monitoring methods and prevention strategies for fault-induced coal burst are discussed and recommended.The results show that fault-induced coal burst is triggered by the superposition of high static stress in the fault pillar and dynamic stress from fault reactivation.High static stress comes from the interaction of the fault and the roof structure,and dynamic stress can be ascribed to FRMSS and FRSDS.The results in this paper could be of great significance in guiding the monitoring and prevention of fault-induced coal bursts.展开更多
Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been...Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.展开更多
基金provided by the State Key Research Development Program of China (No.2016YFC0801403)Key Research Development Program of Jiangsu Provence (No.BE2015040)+1 种基金National Natural Science Foundation of China (Nos.51674253,51734009 and 51604270)Natural Science Foundation of Jiangsu Province (No.BK20171191)
文摘Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.
基金This research was carried out by the following funded projects:National Natural Science Foundation of China(51604270,51874292,and 51804303)Fundamental Research Funds for the Central Universities(2017QNA26)+2 种基金Natural Science Foundation of Jiangsu Province(BK20180643)Independent Research Projects of State Key Laboratory of Coal Resources and Safe Mining,China University of Mining and Technology(SKLCRSM15X04)The first author also acknowledges the China Postdoctoral Council International Postdoctoral Exchange Fellowship Program(20170060).
文摘Fault is a common geological structure that has been revealed in the process of underground coal excavation and mining.The nature of its discontinuous structure controls the deformation,damage,and mechanics of the coal or rock mass.The interaction between this discontinuous structure and mining activities is a key factor that dominates fault reactivation and the coal burst it can induce.This paper first summarizes investigations into the relationships between coal mining layouts and fault occurrences,along with relevant conceptual models for fault reactivation.Subsequently,it proposes mechanisms of fault reactivation and its induced coal burst based on the superposition of static and dynamic stresses,which include two kinds of fault reactivations from:mining-induced quasi-static stress(FRMSS)-dominated and seismic-based dynamic stress(FRSDS)-dominated.These two kinds of fault reactivations are then validated by the results of experimental investigations,numerical modeling,and in situ microseismic monitoring.On this basis,monitoring methods and prevention strategies for fault-induced coal burst are discussed and recommended.The results show that fault-induced coal burst is triggered by the superposition of high static stress in the fault pillar and dynamic stress from fault reactivation.High static stress comes from the interaction of the fault and the roof structure,and dynamic stress can be ascribed to FRMSS and FRSDS.The results in this paper could be of great significance in guiding the monitoring and prevention of fault-induced coal bursts.
文摘Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.
