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
赵东升 1宋浩伟 2朱峰 2赵伟 1赵慧亮 1程冠宇 1胡宾鑫 2马鑫楠 2孙增荣3
作者信息
- 1. 山西潞安环保能源开发股份有限公司漳村煤矿
- 2. 齐鲁工业大学(山东省科学院)激光研究所
- 3. 山东盛隆安全技术有限公司
- 折叠
摘要
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.
Abstract
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 root-square 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.
关键词
微震监测/b值优化/信息识别/监测预警Key words
microseismic monitoring/b-value optimization/information identification/tunneling roadway引用本文复制引用
基金项目
山东省科技型中小企业创新能力提升工程项目(2023TSGC0106)
出版年
2024
NETL
NSTL
万方数据