矿山微地震四线交错观测系统与面波速度成像  

Four-line staggered grid survey layout of mine micro-seismic and surface wave velocity structure imaging

作　　者：李晓斌 杨振威[2] 云美厚[2] 杨双安[1,2] LI Xiaobin;YANG Zhenwei;YUN Meihou;YANG Shuangan(Collaborative Innovation Center of Coalbed Methane and Shale Gas for Central Plains Economic Region,Henan Province,Jiaozuo 454003,China;School of Resources and Environment,Henan Polytechnic University,Jiaozuo 454003,China)

机构地区：[1]中原经济区煤层(页岩)气河南省协同创新中心,河南焦作454003 [2]河南理工大学资源环境学院,河南焦作454003

出　　处：《煤炭学报》2019年第S02期643-649,共7页Journal of China Coal Society

基　　金：国家自然科学基金资助项目(41772375);河南省自然科学基金资助项目(182300410006);河南省教育厅基础研究计划资助项目(14A440009)。

摘　　要：矿山动力灾害微地震监测中,矿山采掘活动及周围机械振动亦是重要震源,地震波在传播过程,面波能量强、信号容易获得,同样携带有大量地层信息,由于矿井微地震事件和采掘活动具有时间和空间随机性特点,空间自相关法适用于从复杂的环境噪声中提取面波信息。基于空间自相关理论基础,设计了针对矿井监测环境的四线交错网格微地震监测台阵观测系统,通过从观测数据中提取圆形观测数据集、窄带滤波、计算空间自相关系数、拟合面波频散曲线等处理过程,构建观测煤层面波速度结构反演成像的方法;在理论分析基础上,在义马集团所属矿山的微地震事件、采掘活动和环境噪声等杂散信号中采集数据,抽取圆形观测道集,将各数据段通过中心频率不同的窄带滤波处理,分别提取各个频率成分,并对各个频率成分计算中心测点与圆周上各点之间的空间自相关系数,通过计算空间自相关函数及其Bessel函数等步骤拟合出相速度频散曲线。试验分析表明,矿山微地震四线交错网格通过实时记录强噪声干扰环境下矿山岩层断裂产生的微震波和采掘活动产生的环境噪声,提取有效信息反演微地震传播过程中携带的围岩速度地球物理特性等,面波速度成像与煤层厚度分布具有良好的一致性,能够较好地反映工作面地速度结构。由于面波不受高速层屏蔽作用的影响,对煤层等低速层有较强的分辨能力,能够查明煤层破碎带、采空区、陷落柱等低速层,并圈定速度异常体的边界,对保障发生矿山安全生产具有重要意义。Micro-seismic monitoring technique is an important mean for the safety of coal mine.Both mining activity and mechanical vibration are regarded as sources which take plenty geological information of coal and rock medium through seismic waves traveling time and space.During the seismic wave propagation,surface wave signals have the characteristics of strong energy,low frequency,slow attenuation and easy to collect.Because of the time and space randomness of mine micro-seismic events and mining activities,the spatial autocorrelation method is suitable for extracting surface wave information from complex ambient noise.This paper introduces a four-wire staggered grid survey layout for the mine micro-seismic monitoring based on the theory of spatial autocorrelation method.Firstly,the theoretical methods includes extracting the circular observation data set,narrowband filtering,calculating the spatial autocorrelation coefficient,calculating the phase velocity,fitting the phase velocity dispersion curve and calculating the velocity structure of coal seam etc.Secondly,some field data are collected from the scattered signals of interference such as micro-seismic events and mining activities,and each data segment is processed by narrowband filtering with different center frequencies to acquire each frequency component respectively.Thirdly,the spatial autocorrelation coefficients between the central observation point and the circular observation point were calculated for each frequency component.Finally,the dispersion curve of surface wave phase velocity is obtained by spatial autocorrelation function and Bessel function.The experimental results showed that the surface wave velocity imaging has a good consistency with the thickness distribution of coal seam,which can better reflect the velocity structure of coal mine working surface.Since the surface wave is not affected by the shielding effect of the high-speed layer,it has a strong resolution ability to the low-speed layer such as coal seam,which can identify the low-speed

关 键 词：面波成像 微地震监测 矿山环境噪声 观测系统 空间自相关 

分 类 号：P315.3[天文地球—地震学]