Abstract. An intelligent method is presented for locating microseismic source based on particle swarm optimization (PSO) concept. It eliminates microseismic source locating errors caused by 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 modeled arrival times and 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, the PSO algorithm displays faster convergence and higher accuracy of microseismic source positioning. 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.
Evaluation of particle swarm optimization in synthesis of shear wave velocity using conventional well log data
