scholarly journals Research Developments and Prospects on Microseismic Source Location in Mines

Engineering ◽  
2018 ◽  
Vol 4 (5) ◽  
pp. 653-660 ◽  
Author(s):  
Jiulong Cheng ◽  
Guangdong Song ◽  
Xiaoyun Sun ◽  
Laifu Wen ◽  
Fei Li
Keyword(s):  
Source Location ◽  
Microseismic Source Location

scholarly journals Microseismic source location in tunnels: Effect of arrival-time picking

2020 ◽  
Vol 570 ◽  
pp. 052049
Author(s):  
Guang-Liang Feng ◽  
Ya-Xun Xiao ◽  
Man-Qing Lin ◽  
Yang Yu ◽  
Yu Fu
Keyword(s):  
Arrival Time ◽  
Source Location ◽  
Microseismic Source Location ◽  
Arrival Time Picking

scholarly journals The adaptive particle swarm optimization technique for solving microseismic source location parameters

2019 ◽  
Vol 26 (3) ◽  
pp. 163-173 ◽  
Author(s):  
Hong-Mei Sun ◽  
Jian-Zhi Yu ◽  
Xing-Li Zhang ◽  
Bin-Guo Wang ◽  
Rui-Sheng Jia
Keyword(s):  
Particle Swarm Optimization ◽  
Wave Velocity ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Source Location ◽  
P Wave ◽  
Swarm Optimization ◽  
Arrival Times ◽  
P Wave Velocity ◽  
Microseismic Source Location

Abstract. An intelligent method is presented for locating a microseismic source based on the particle swarm optimization (PSO) concept. It eliminates microseismic source locating errors caused by the inaccurate velocity model of the earth medium. The method uses, as the target of PSO, a global minimum of the sum of squared discrepancies between differences of modeled arrival times and differences of measured arrival times. The discrepancies are calculated for all pairs of detectors of a seismic monitoring system. Then, the adaptive PSO algorithm is applied to locate the microseismic source and obtain optimal value of the P-wave velocity. The PSO algorithm adjusts inertia weight, accelerating constants, the maximum flight velocity of particles, and other parameters to avoid the PSO algorithm trapping by local optima during the solution process. The origin time of the microseismic event is estimated by minimizing the sum of squared discrepancies between the modeled arrival times and the measured arrival times. This sum is calculated using the obtained estimates of the microseismic source coordinates and P-wave velocity. The effectiveness of the PSO algorithm was verified through inversion of a theoretical model and two analyses of actual data from mine blasts in different locations. Compared with the classic least squares method (LSM), the PSO algorithm displays faster convergence and higher accuracy of microseismic source location. Moreover, there is no need to measure the microseismic wave velocity in advance: the PSO algorithm eliminates the adverse effects caused by error in the P-wave velocity when locating a microseismic source using traditional methods.

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