Cross-related microseismic location based on improved particle swarm optimization and the double-difference location method of jointed coal rock mass

Abstract

The location algorithm is the core of microseismic monitoring, and the location results directly influence the effectiveness of the subsequent source analysis. We introduced the double-difference (DD) location method in seismic location into microseismic monitoring. We built a travel time equation of the layered velocity model using the ray-tracing theory and analyzed the waveform cross-correlation of the microseismic data using a generalized cross-correlation (GCC) technique. The improved particle swarm algorithm was successfully conducted to improve the randomness of the initial location. We then adopted the DD location method to precisely locate the secondary location, and it showed better location accuracy and computational efficiency than that by a traditional location algorithm based on the simplified geological model. The theoretical simulation and practice results in deep mining show that the proposed method significantly increased the location accuracy, and the results were concentrated and consistent with the field results. Moreover, we verified the importance of the velocity model for location accuracy. This algorithm also increased the ease of identifying fracture regions, providing the necessary theoretical and technical support for the source location of the jointed coal rock mass in deep mining.