煤炭工程 ›› 2020, Vol. 52 ›› Issue (11): 114-119.doi: 10.11799/ce202011023

• 研究探讨 • 上一篇    下一篇

基于微震事件“时-频-能”特征分析的工作面隐伏断层预测研究

解嘉豪   

  1. 中煤能源研究院有限责任公司
  • 收稿日期:2019-07-11 修回日期:2019-10-21 出版日期:2020-11-16 发布日期:2020-12-16
  • 通讯作者: 解嘉豪 E-mail:xiejiahaocumt@163.com

Prediction of Hidden Faults in Working Face Based on Time-Frequency-Energy Characteristic Analysis of Microseismic Events

  • Received:2019-07-11 Revised:2019-10-21 Online:2020-11-16 Published:2020-12-16

摘要: 为了弄清煤矿井下无法被有效探测的隐伏断层,依据大量的微震事件分析,提出了使用微震监测预测工作面隐伏断层探测的方法,采用离散傅里叶变换(DDT)、一维离散小波变换(DWT)和能量密度法实现微震事件的时域、频域及能域曲线之间的转化。研究结果表明,微震事件的时域曲线呈现波峰少、震动持续时间长、尾波发育的特征|频域曲线呈现频段集中于0~20Hz、单峰的特征|能域曲线呈现“缺震”区间增多、波动时间变长的特征时,工作面前方可能存在隐伏断层。据此分析了星村煤矿3307工作面微震事件波形曲线的突变原因,推断工作面前方存在隐伏断层,工作面后续揭露的F2隐伏断层验证了此推断。

关键词: 微震事件, “时-频-能”特征, 隐伏断层, 冲击地压

Abstract: Influenced by the accuracy of geophysical prospecting, some small faults in coal mine can not be effectively detected, which poses a serious threat to the safety of underground production. Accurate prediction of hidden faults is an urgent need for safe mining in working face. Based on the analysis of a large number of microseismic events, this paper shows that microseismic monitoring can be used as an auxiliary monitoring method for detecting hidden faults in working face. The main methods are: DDT, DWT and energy density methods are used to transform the time domain, frequency domain and energy domain curves of microseismic events, and the "time-frequency-energy" characteristic analysis method of microseismic events is proposed. Based on this method, the difference of "time-frequency-energy" characteristics between the curves measured before and after faults for the same microseismic event is analyzed. Research shows that: in the time domain, there are many peaks of microseismic events before faults, short duration of vibration, undeveloped coda, and the opposite is true after faults. In the frequency domain, the frequency band of microseismic events before faults is complete, and the low, medium and high frequency bands are distributed. The frequency domain curve shows multi-peak characteristics, while the microseismic events after faults are concentrated in the frequency band of 0-20Hz, showing a sharp single peak characteristic. Faults play a similar role of "low-pass filtering" for microseismic events. In the energy domain, the energy of microseismic events before faults has the characteristics of short-term, full-frequency and continuous propagation, while after faults, the energy of microseismic events is opposite. Based on this, the abrupt change reason of microseismic event waveform curve in 3307 working face of a mine is analyzed. It is inferred that there are hidden faults interfering with the propagation of vibration wave in front of the working face. The F2 hidden faults exposed subsequently in the working face verify this inference.

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