联合信息融合和解析方法的微震源定位研究
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摘要
针对现有微震源定位算法大多基于均匀速度假设以及采用迭代解法导致计算量大且稳健性不佳的不足,通过对走时方程的变换和求解,推导了考虑速度各向异性的微震源解析解,提出了一种新的微震源定位方法。新方法由6个有效检波器数据实现定位。考虑到波速特征的复杂性,将随机模拟方法应用于产生大量震源备选解,并从信息融合角度对最终震源解进行探讨,将粗大误差判别准则和聚类分析方法用于获取最终的震源解。通过算例验证表明:提出的解析方法正确合理,且采用的信息融合方法科学合理,并建议在实际应用中采用粗大误差判别准则确定最终微震源。
Aiming at the shortcomings of the existing micro source localization algorithm based on the uniform speed assumption and the iterative method leading to large amount of calculation and poor robustness,a new method of micro source location considering the velocity anisotropy was proposed through the transformation of time distance equation.The new method used six effective detector data to implement positioning. Stochastic simulation method was applied to produce a large number of source alternative solutions considering the complexity of wave velocity characteristics. Final source solution was discussed from the angle of information fusion,the gross error criterion and the clustering analysis method was used to obtain the source solution. The examples show that the analytical method is correct and reasona ble,and the information fusion method is scientific and reasonable,and suggest the final micro source is determined through gross error criterion.
Aiming at the shortcomings of the existing micro source localization algorithm based on the uniform speed assumption and the iterative method leading to large amount of calculation and poor robustness,a new method of micro source location considering the velocity anisotropy was proposed through the transformation of time distance equation.The new method used six effective detector data to implement positioning. Stochastic simulation method was applied to produce a large number of source alternative solutions considering the complexity of wave velocity characteristics. Final source solution was discussed from the angle of information fusion,the gross error criterion and the clustering analysis method was used to obtain the source solution. The examples show that the analytical method is correct and reasona ble,and the information fusion method is scientific and reasonable,and suggest the final micro source is determined through gross error criterion.
引文
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[14]蔡国军,刘松玉,童立元,等.基于聚类分析理论的CPTU土分类方法研究[J].岩土工程学报,2009,31(3):416-424.CAI Guojun,LIU Songyu,TONG Liyuan,et al.Soil classification using CPTU data based upon cluster analysis theory[J].Chinese Journal of Geotechnical Engineering,2009,31(3):416-424.
[15]朱权洁,姜福兴,缪华祥,等.基于聚类分析的微震定位二次优化研究[J].采矿与安全工程学报,2014,31(2):196-202.ZHU Quanjie,JIANG Fuxing,MIU Huaxiang,et al.Quadratic opti-mization of mining microseismic source positioning based on cluster analysis[J].Journal of Mining&Safety Engineering,2014,31(2):196-202.
[16]高永涛,吴庆良,吴顺川,等.基于误差最小原理的微震震源参数反演[J].中南大学学报(自然科学版),2015,46(8):3054-3060.GAO Yongtao,WU Qingliang,WU Shunchuan,et al.Source param-eters inversion based on minimum error principle[J].Journal of Central South University(Science and Technology),2015,46(8):3054-3060.
[17]李绍红,吴礼舟,杨戒,等.微震源定位的两步反演方法研究[J].岩石力学与工程学报,2017,36(7):1710-1717.LI Shaohong,WU Lizhou,YANG Jie,et al.A two-step inver-sion method for micro-seismic source location[J].Chinese Journal of Rock Mechanics and Engineering,2017,36(7):1710-1717.
[18]李楠,王恩元,李保林,等.传感器台网布设对震源定位的影响规律及机制研究[J].中国矿业大学学报,2017,46(2):229-236.LI Nan,WANG Enyuan,LI Baolin,et al.Research on the influence law and mechanisms of sensors network layouts for the source loca-tion[J].Journal of China University of Mining and Technology,2017,46(2):229-236.
[19]巩思园,窦林名,曹安业,等.煤矿微震监测台网优化布设研究[J].地球物理学报,2010,53(2):457-465.GONG Siyuan,DOU Linming,CAO Anye,et al.Study on opti-mal configuration of seismological observation network for coal mine[J].Chinese Journal of Geophysics,2010,53(2):457-465.
[2]姜福兴,尹永明,朱权洁,等.单事件多通道微震波形的特征提取与联合识别研究[J].煤炭学报,2014,39(2):229-237.JIANG Fuxing,YIN Yongming,ZHU Quanjie,et al.Feature extrac-tion and classification of mining microseismic waveforms viam-ulti-channels analysis[J].Journal of China Coal Society,2014,39(2):229-237.
[3]汤国水,朱志洁,韩永亮,等.基于微震监测的双系煤层开采覆岩运动与矿压显现关系[J].煤炭学报,2017,42(1):212-218.TANG Guoshui,ZHU Zhijie,HAN Yongliang,et al.Relationship be-tween overburden strata movement and strata behavior during dual system seam mining based on microseismic monitoring technology[J].Journal of China Coal Society,2017,42(1):212-218.
[4]LI X B,DONG L J.Comparison of two methods in acoustic emission source location using four sensors without measuring sonic speed[J].Sensor Letters,2011,9(5):1501-1505.
[5]LI J,WU S C,GAO Y T,et al.An improved multidirectional veloci-ty model for micro-seismic monitoring in rock engineering[J].Jour-nal of Central South University,2015,22(6):2348-2358.
[6]李楠,王恩元,孙珍玉,等.基于L1范数统计的单纯形微震震源定位方法[J].煤炭学报,2014,39(12):2431-2438.LI Nan,WANG Enyuan,SUN Zhenyu,et al.Simplex microseismic source location method based on L1 norm statistical standard[J].Journal of China Coal Society,2014,39(12):2431-2438.
[7]李罗兰,何川,谭玉阳.微地震观测系统及震源定位目标函数研究[J].北京大学学报(自然科学版),2017,53(2):329-343.LI Luolan,HE Chuan,TAN Yuyang.Study of recording system and objective function for microseismic source location[J].Acta Scien-tiarum Naturalium Universitatis Pekinensis,2017,53(2):329-343.
[8]林峰,李庶林,薛云亮,等.基于不同初值的微震源定位方法[J].岩石力学与工程学报,2010,29(5):996-1002.LIN Feng,LI Shulin,XUE Yunliang,et al.Microseismic sources lo-cation methods based on different initial values[J].Chinese Journal of Rock Mechanics and Engineering,2010,29(5):996-1002.
[9]陈炳瑞,冯夏庭,李庶林,等.基于粒子群算法的岩体微震源分层定位方法[J].岩石力学与工程学报,2009,28(4):740-749.CHEN Bingrui,FENG Xiating,LI Shulin,et al.Microseismic sources location with hierarchical strategy based on particle swarm optimiza-tion[J].Chinese Journal of Rock Mechanics and Engineering,2009,28(4):740-749.
[10]张向东,王帅,赵彪,等.二层水平介质中震源的精确定位[J].岩土工程学报,2014,36(6):1044-1050.ZHANG Xiangdong,WANG Shuai,ZHAO Biao,et al.Precise posi-tioning in double-layer horizontal media[J].Chinese Journal of Geotechnical Engineering,2014,36(6):1044-1050.
[11]张向东,王帅,贾宝新.二层水平介质球面波正反演联用与震源定位[J].岩土工程学报,2015,37(2):225-234.ZHANG Xiangdong,WANG Shuai,JIA Baoxin.Positioning of seis-mic sources combined with forward and inversion of spherical wave in double-layer horizontal media[J].Chinese Journal of Geotechni-cal Engineering,2015,37(2):225-234.
[12]刘明贵,杨永波.信息融合技术在边坡监测与预报系统中的应用[J].岩土工程学报,2005,27(5):607-610.LIU Minggui,YANG Yongbo.Application of information fusion in slope monitoring and prediction system[J].Chinese Journal of Geotechnical Engineering,2005,27(5):607-610.
[13]熊艳艳,吴先球.粗大误差四种判别准则的比较和应用[J].大学物理实验,2010,23(1):66-68.XIONG Yanyan,WU Xianqiu.The generalizing application of four judging criterions for gross errors[J].Physical Experiment of Col-lege,2010,23(1):66-68.
[14]蔡国军,刘松玉,童立元,等.基于聚类分析理论的CPTU土分类方法研究[J].岩土工程学报,2009,31(3):416-424.CAI Guojun,LIU Songyu,TONG Liyuan,et al.Soil classification using CPTU data based upon cluster analysis theory[J].Chinese Journal of Geotechnical Engineering,2009,31(3):416-424.
[15]朱权洁,姜福兴,缪华祥,等.基于聚类分析的微震定位二次优化研究[J].采矿与安全工程学报,2014,31(2):196-202.ZHU Quanjie,JIANG Fuxing,MIU Huaxiang,et al.Quadratic opti-mization of mining microseismic source positioning based on cluster analysis[J].Journal of Mining&Safety Engineering,2014,31(2):196-202.
[16]高永涛,吴庆良,吴顺川,等.基于误差最小原理的微震震源参数反演[J].中南大学学报(自然科学版),2015,46(8):3054-3060.GAO Yongtao,WU Qingliang,WU Shunchuan,et al.Source param-eters inversion based on minimum error principle[J].Journal of Central South University(Science and Technology),2015,46(8):3054-3060.
[17]李绍红,吴礼舟,杨戒,等.微震源定位的两步反演方法研究[J].岩石力学与工程学报,2017,36(7):1710-1717.LI Shaohong,WU Lizhou,YANG Jie,et al.A two-step inver-sion method for micro-seismic source location[J].Chinese Journal of Rock Mechanics and Engineering,2017,36(7):1710-1717.
[18]李楠,王恩元,李保林,等.传感器台网布设对震源定位的影响规律及机制研究[J].中国矿业大学学报,2017,46(2):229-236.LI Nan,WANG Enyuan,LI Baolin,et al.Research on the influence law and mechanisms of sensors network layouts for the source loca-tion[J].Journal of China University of Mining and Technology,2017,46(2):229-236.
[19]巩思园,窦林名,曹安业,等.煤矿微震监测台网优化布设研究[J].地球物理学报,2010,53(2):457-465.GONG Siyuan,DOU Linming,CAO Anye,et al.Study on opti-mal configuration of seismological observation network for coal mine[J].Chinese Journal of Geophysics,2010,53(2):457-465.