煤矿掘进巷道微震监测b值优化及煤岩识别预警

b-value Optimization and Information Identification and Early Warning of Tunning in Coal Mine Roadway

随着采掘工作面开采深度和强度的增加,煤矿井下微震事件与灾害风险在持续增高。结合漳村煤矿掘进巷道微震监测数据,对掘进面前方区域微震事件b值优化分析和信息识别分类,提出了基于最小二乘法的变分档根方算法,从“时、空、强”3个角度对断层区域进行了b值、震源的讨论分析,提高了b值准确性。为微震事件的分类识别提供了方法和思路,更好地利用微震数据指导矿方安全生产和防护。

With the increase of mining depth and intensity of mining face,the risk of microseismic events and disasters in underground coal mines continues to increase.Combined with the microseismic moni⁃toring data of the tunneling roadway in Zhangcun Coal Mine,the b-value optimization analysis and informa⁃tion recognition classification of the microseismic events in the area in front of the tunneling face are carried out.A variational root-square algorithm based on the least square method is proposed.A variational rootsquare algorithm based on the least square method is proposed.The b-value and source of the fault area are analyzed from the three angles of′time,space and strength′,and the accuracy of the b-value is optimized.The research improves the reliability of microseismic monitoring and early warning and better guides mine safety production.