Microseismic source location method based on a velocity model database and statistical analysis

被引：5
作者：
Chen B.-R. [1 ,2 ]
Li T. [1 ,2 ]
Zhu X.-H. [1 ,2 ]
Wei F.-B. [1 ,2 ]
Wang X. [1 ,2 ]
Xie M.-X. [3 ]
机构：
[1] State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan
[2] University of Chinese Academy of Sciences, Beijing
[3] Beiminghe Iron Mine of Minmetals Hanxing Mining Co., Ltd., Wu’an, 056300, Hebei
来源：
Arabian Journal of Geosciences | 2021年 / 14卷 / 19期
基金：
中国国家自然科学基金;
关键词：
Illegal mining; Microseismic source location; Rock mechanics; Statistical analysis; Velocity model database;
D O I：
10.1007/s12517-021-08311-9
中图分类号：
学科分类号：
摘要：
Matching the velocity model to the actual engineering and geological conditions and improving the accuracy and stability of the microseismic (MS) source location remain challenges for scientists. An MS source location method based on a velocity model database and statistical analysis, named LM-VMD-SA, is proposed in this study. The method firstly divides the monitoring area into different subareas based on four influencing factors and creates an initial velocity model database by assigning an initial velocity to each sensor combination. Secondly, blasting tests are carried out in each subarea, where the velocity model database is inverted using a location error optimization method based on the pattern search algorithm (LEOM-PSA). The initial velocity model database for each subarea is updated by the velocity model database of the blasting events in the same subarea, and a velocity model database is constructed. Then, the velocity models for all sensor combinations of an MS event are called from the velocity model database for the corresponding subarea by matching the sensor combination of the MS event, and all corresponding solutions of the MS event are solved by the ND-N method. Finally, the three-dimensional coordinates of MS source are identified by utilizing the log-logistic (3P) distribution probability density function. According to blasting tests in the Beiminghe Iron Mine, the location accuracy of the proposed method is 20.88% and 18.24% higher than that of the traditional method and subarea method, respectively. The application of the proposed method to the Beiminghe Iron Mine revealed the illegal mining activities at −125 m and −155 m level, providing effective technical support for mineral resources protection and mining safety. © 2021, Saudi Society for Geosciences.
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