Multivariate Early Warning Method for Rockburst Monitoring Based on Microseismic Activity Characteristics - Yu, Qun; Zhao, Danchen; Xia, Yingjie; Jin, Shengji; Zheng, Jian; Meng, Qingkun; Mu, Chaoqian; Zhao, Jingchi (Frontiers in Earth Science, 2022)
The monitoring of rockburst is one of the worldwide problems in underground engineering and how to effectively predict and early warn the occurrence of rockburst disasters has become an urgent problem to be solved. In this paper, the high rockburst occurrence section of the deep diversion tunnel of Jinping Hydropower Station on yalong River is taken as the research object. Based on the microseismic monitoring technology and combined the principle of seismology with qualitative analysis and quantitative calculation, the distribution law of "time, space and intensity" of microseismic activity and the change law of source parameters time series are used as the precursor characteristics of rockburst early warning. Based on these, the internal relationship between microseismic activity and rockburst micro-fracture was studied. The monitoring results show that the rockburst occurred before has obvious micro rupture precursors. The microseismic activity is a self-organizing process from spatial disordered dispersion to ordered concentration. The abnormal changes of source parameters such as density of microseismic events, seismic energy density, the cumulative volume, energy index, 3S index and b values can be used as a warning identification of rockburst. Therefore, the multivariate early warning method for rockburst monitoring based on the comprehensive analysis of source parameters in deep tunnel is proposed. The prediction accuracy of this method is up to 80.6%, and it can provide reference for the rockburst prediction, warning, and safe construction of such tunnel engineering.