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The adaptive particle swarm optimization technique for solving microseismic source location parameters
Nonlinear Processes in Geophysics ( IF 1.7 ) Pub Date : 2019-07-15 , DOI: 10.5194/npg-26-163-2019
Hong-Mei Sun , Jian-Zhi Yu , Xing-Li Zhang , Bin-Guo Wang , Rui-Sheng Jia

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.

中文翻译:

求解微震震源定位参数的自适应粒子群优化技术

摘要。提出了一种基于粒子群优化(PSO)概念的微震源定位智能方法。它消除了由于地球介质速度模型不准确而导致的微震源定位误差。该方法使用建模的到达时间的差异与测量的到达时间的差异之间的差异平方和的全局最小值作为PSO的目标。针对地震监测系统的所有检测器对计算差异。然后,应用自适应PSO算法定位微震源并获得P波速度的最优值。PSO算法通过调整惯性权重、加速常数、粒子最大飞行速度等参数,避免PSO算法在求解过程中被局部最优解困。微震事件的起源时间是通过最小化建模的到达时间和测量的到达时间之间的差异平方和来估计的。该总和是使用获得的微震源坐标和 P 波速度的估计值来计算的。通过理论模型的反演和不同位置的矿井爆破实际数据的两次分析,验证了PSO算法的有效性。与经典的最小二乘法 (LSM) 相比,PSO 算法显示出更快的收敛速度和更高的微震源定位精度。此外,无需提前测量微震波速:PSO算法消除了传统方法定位微震源时因纵波速度误差带来的不利影响。
更新日期:2019-07-15
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