Automatic picking method of microseismic first arrival time based on improved support vector machine

• Published in: Gong kuang zi dong hua = Industry and mine automation Vol. 49; no. 3; pp. 63 - 69
• Main Authors: LI Tieniu, HU Binxin, LI Huakun, GENG Wencheng, HAO Pengcheng, JI Xubo, SUN Zengrong, ZHU Feng, ZHANG Hua, YANG Chengquan
• Format: Journal Article
• Language: Chinese
• Published: Editorial Department of Industry and Mine Automation 01.03.2023
• Subjects: first arrival of microseism; grid search method; microseismic monitoring; particle swarm optimization algorithm; support vector machine; the arrival time of the first wave
• ISSN: 1671-251X
• DOI: 10.13272/j.issn.1671-251x.2022050081

The microseismic first arrival time picking is an important prerequisite for the high-precision positioning of the microseismic source. The traditional manual picking method is inefficient. The automatic picking method is difficult to pick the arrival time of the first wave accurately under the condition of low signal-to-noise ratio. In order to solve the above problems, an automatic picking method of microseismic first arrival time based on improved support vector machine (SVM) is proposed. Firstly, the method carries out normalization processing, linear correction and proper clipping on original microseismic data. The method marks different categories of the data by taking the amplitude, the energy and the energy ratio of adjacent moments of the microseismic data as features. Secondly, the method adopts a particle swarm optimization (PSO) algorithm and a grid search method to optimize the penalty parameters and the kernel function parameters of the SVM. The method carries out large-range fast positioning on