Location error based seismic cluster analysis and its application to burst damage assessment in underground coal mines

Abstract Coal bursts have emerged as the most critical mining hazard for underground coal mines around the world. Seismic monitoring and seismic clustering analysis are the cornerstones to develop an understanding of and to quantify coal burst hazards. The prerequisite to successfully detect seismic clustering behaviours is the accuracy of locating seismic events, which however can be a challenging task in underground coal mines. Therefore, the characteristics of location errors of seismic events and their impact on clustering results should be explicitly investigated and considered in seismic cluster analysis. Based on nine months of seismic data and 24 coal bursts from a longwall panel, this paper considers location errors and proposes a modified seismic clustering method to improve the results available for coal burst hazard assessment. The location errors in the area of interest were firstly assessed using the emulation testing method. Within the determined location errors, the clustering possibility between seismic events was calculated. The characteristics of the possible seismic clustering along with mining, named as “the Number of Possible Clustered Events” ( NPCE ), were investigated. The results showed that location errors presented large variations and strong anisotropic patterns in the longwall panel, with values ranging from 20 to more than 80 m. The NPCE result presented an improved detection on seismic clustering behaviour, and the high NPCE values also indicated a strong correlation with coal burst damages observed at the mine. Several intensive seismic clustering zones were observed in more than two months prior to the longwall passing these locations, which suggest that the method can be used for the medium to long term seismic hazard assessment .