黄土坡铜锌矿微震监测技术应用与灾害预警方法研究

Application and Research of Microseismic Monitoring Technology and Disaster Early Warning Methods in Huangtupo Copper and Zinc Mine

黄土坡铜锌矿位于新疆哈密地区,采用地下开采方式开采矿石,该矿山附近存在另外一家矿山企业,2个矿山同时产生的开采扰动使得该矿山面临着复杂的地压环境。为了对黄土坡铜锌矿井下多处采空区附近的地压灾害进行预警,引进微震监测系统,对采空区周边及生产作业区域围岩稳定性进行实时监测。采用优化的台网布设方案改善微震监测系统的性能,并在微震信号自动识别技术的基础上,对地压活动进行实时分析,保证分析结果的时效性。基于微震监测多参数分析方法,结合一次现场真实地压险情提出了一套微震监测地压灾害预警分析方法,该方法能够实现地压提前预警,给矿山人员提供了逃生时间,在地下开采矿山地压监测中具有推广意义。

Huangtupo copper and zinc mine located southwest of Hami City,Xinjiang Uygur Autonomous Region,China.It is an underground mine,and there are several goaves in the mining area.There is another mine nearby the area,which is also mining ore.The mining activities of two mines have caused a great disturbance to the pressure environment in the area. Therefore,MicroSeis microseismic monitoring system was introduced to give early warning of the ground pressure disaster that may be caused by goaves in Huangtupo copper and zinc mine.This system monitors the stability of surrounding rock around the goaves and production area in real-time.The microseismic monitoring system has the advantages of broad range,high sensitivity,non-contact,and multiparameters analysis.In order to ensure the reliability and real-time performance of the microseismic system,the system was optimized.Using network analysis tools to optimize the best microseismic network layout scheme,than the event positioning accuracy is effectively guaranteed. In this paper,through network analysis,the optimized positioning accuracy of the center practice is about 5 m,and the positioning accuracy of the production operation area is within 10 m,which can fully meet the requirements of ground pressure monitoring and disaster early warning. Microseismic systems always pick up signals in rock masses indiscriminately.However,there are many production noise signals in the general engineering environment,such as blasting signals,mechanical vibration signals,and electrical interference signals.In the aspect of signal recognition,the traditional approach is to rely on manual methods for identification and classification,with low efficiency.Therefore,an artificial intelligence method was proposed to identify the microseismic signals. This automatic identification model ensures the real-time performance of the microseismic system and is the basis of disaster early warning. The early warning method of microseismic monitoring technology is based on quantitative seismology.Moreover,quantitative seismology is based on the development of rock mechanics,seismology,and statistics. In this paper,seismological parameters such as microseismic event activity rate,spatial distribution characteristics,seismic moment,energy,and b value were used to analyze ground pressure activity.At the same time,a set of early warning and analysis methods of microseismic monitoring ground pressure disaster was put forward. This method can realize early warning of ground pressure,provide time for evacuation of mine personnel,and effectively grasp the development trend of ground pressure. Furthermore,it can guide mine personnel to go into the mine for production in a safe time,so it has the significance of popularization in the monitoring of underground mine pressure.