基于到时时空分布的微震震源定位算法

李明虎，陈  卫，蔡  珣

基于到时时空分布的微震震源定位算法

李明虎，陈卫，蔡珣

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出版历程
- 网络出版日期: 2023-08-30
- 刊出日期: 2023-08-22

Micro-seismic source location algorithm based on spatio-temporal distribution of arrival times

LI Minghu

摘要

摘要: 为了提高微震震源定位精度和算法鲁棒性，研究了基于到时的定位算法的目标函数构建和时空区域信息使用。仿真实验基于Numpy，采用理想到时+随机扰动来模拟生产情况。结果表明：到时定位算法中常用的L1和L2目标函数对实际震源存在偏离且偏离现象非常普遍。为了减轻伪震源问题，使用到时偏差的似然函数作为基础函数，聚合时空邻域的单点基础函数作为目标函数；新构建的4维区域分布算法（Distribution of 4-Dimention Area Algorithm, D4DA）在2次标定炮定位中将定位误差分别降低了14%和26%。
- 微震 /
- 震源定位 /
- 目标函数 /
- 区域分布 /
- 到时
Abstract: In order to improve the precision of the micro-seismic hypocenter location and the robustness of algorithms, the objective function construction and spatiotemporal region information use of the location algorithm based on time are studied. The simulation experiment is based on Numpy, the perfect arrival times subjoining random disturbance is used to simulate production situation. Result shows that the L1 and L2 objective functions deviate from the hypocenter and the deviation is quite common. To alleviate the pseudo source problem, the likelihood function of arrival times deviation is used as the basic function, and the information of space-time neighborhood is then combined as the new objective function. The distribution of 4-dimension area algorithm （Ｄ４ＤＡ） reduces the positioning errors by 14% and 26% respectively in the two calibration gun positioning.
- micro-seismic /
- hypocenter location /
- objective function /
- regional distribution /
- arrival time

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［1］　窦林名，田鑫元，曹安业，等.我国煤矿冲击地压防治现状与难题［J］.煤炭学报，2022，47（1）:152-171. DOU Linming, TIAN Xinyuan, CAO Anye, et al. Present situation and problems of coal mine rock burst prevention and control in China［J］. Journal of China Coal Society, 2022, 47（1）: 152-171. ［2］　GEIGER L. Probability method for the determi-nation of earthquake epicenters from arrival time only［J］. Bulletin Saint Louis University, 1912, 8（1）: 60-71. ［3］　PRUGGER A F, GENDZWILL D J. Microearthquake location: a nonlinear approach that makes use of a simplex stepping procedure［J］. Bulletin of the Seismological Society of America, 1988, 78（2）: 799-815. ［4］　WALDHAUSER F, ELLSWORTH W. A double-difference earthquake location algorithm: method and application to the Northern Hayward fault California［J］. Translated World Seismology, 2003, 90: 1353-1368. ［5］　ARTMAN B, PODLADTCHIKOV I, WITTEN B. Source location using time-reverse imaging［J］. Geophysical Prospecting, 2010, 58（5）: 861-873. ［6］　KAO Honn, SHAN Shaoju. The source-scanning algorithm: mapping the distribution of seismic sources in time and space［J］. Geophysical Journal International, 2004, 157（2）: 589-594. ［7］　DREW J, WHITE R S, TILMANN F, et al. Coalescence microseismic mapping［J］. Geophysical Journal International, 2013, 195（3）: 1773-1785. ［8］　万永革.地震学导论［M］.北京：科学出版社，2016：330-331. ［9］　HU Ge, MENKE William, POWELL Christine. Polarization tomography for P wave velocity structure in southern California［J］. Journal of Geophysical Research: Solid Earth, 1994, 99: 15245-15256. ［10］　CROSSON Robert. Crustal structure modeling of earthquake data: 1. Simultaneous least squares estimation of hypocenter and velocity parameters［J］. Journal of Geophysical Research, 1976, 81（17）: 3036-3046. ［11］　GOT Jean Luc, OKUBO P Okubo. New insights into Kilauea's volcano dynamics brought by large-scale relative relocation of microearthquakes［J］. Journal of Geophysical Research: Solid Earth, 2003, 108: 2337-2349. ［12］　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, MIAO Huaxiang, et al. Quadratic optimization of mining microseismic source positioning based on cluster analysis［J］. Journal of Mining & Safety Engineering, 2014, 31（2）: 196-202. ［13］　宋维琪，高艳珂，朱海伟.微地震资料贝叶斯理论差分进化反演方法［J］.地球物理学报，2０１３，５６（４）：１３31-1339. SONG Weiqi, GAO Yanke, ZHU Haiwei. The differential evolution inversion method based on Bayesian theory for micro-seismic data［J］. Chinese Journal of Geophysics, 2013, 56（4）: 1331-1339. ［14］　盛冠群，李振春，王维波，等.水力压裂微地震粒子群差分进化定位算法［J］.石油学报，201４，３５（６）：１１７2-1181. SHENG Guanqun, LI Zhenchun, WANG Weibo, et al. A source location method for microseismic monitoring based on particle swarm optimization combined with differential evolution algorithm［J］. Acta Petrolei Sinica, 2014, 35（6）: 1172-1181. ［15］　李薇薇，龚仁彬，周相广，等.基于深度学习UNet++网络的初至波拾取方法［J］.地球物理学进展，２０２１，３６（１）：187-194. LI Weiwei, GONG Renbin, ZHOU Xiangguang, et al. 2021. UNet++: a deep-neural-network-based seismic arrival time picking method［J］. Progress in Geophysics, 2021, 36（1）: 187-194. ［16］　QU Shan, GUAN Zhe, VERSCHUUR Eric, et al. Automatic high-resolution microseismic event detection via supervised machine learning［J］. Geophysical Journal International, 2020, 222（3）: 1881-1895. ［17］　陈浩，李磊，王秀明．微地震监测技术研究进展—震源成像的相对定位法［Ｊ］．应用声学，２０１８，３７（１）：３４－４１． CHEN Hao, LI Lei, WANG Xiuming. Research progress of microseismic monitoring technology: waveform-based relative location methods［J］. Journal of Applied Acoustics, 2018, 37（1）: 34-41. ［18］　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 optimal configuration of seismological observation network for coal mine［J］. Chinese Journal of Geophysics. 2010, 53（2）: 457-465. ［19］　李楠.微震震源定位的关键因素作用机制及可靠性研究［D］.徐州：中国矿业大学，2014.

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文章访问数: 31
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基于到时时空分布的微震震源定位算法

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Micro-seismic source location algorithm based on spatio-temporal distribution of arrival times

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