变权重连接P波和S波到时数据的微震震源Bayes定位方法及应用

P-and S-wave arrival time combined Bayesian location method for a microseismic event

微震震源定位是微震监测领域的一项关键性技术,传统的矿山微震定位方法采用基于P波或S波的走时射线追踪定位算法。然而,可用于微震事件定位的到时数据少,致使定位结果误差偏大。联合P波和S波到时的目标函数可取得更好的定位结果。已有研究面临着以下几个挑战:1)联合权重应该是一个由P波和S波到时数据质量决定的自由参数;2)对同一微震事件定位时,使用的全部到时数据中含有不良数据。为此,本文提出了一种变权重连接P波和S波到时数据的贝叶斯定位方法用于微震震源定位。为减少异常到时数据的影响,每次迭代随机选择80%的到时数据。本文使用2个理论事件和8个矿山爆破事件对所提出方法进行了测试。模拟结果表明,当分别在P波和S波的走时数据中添加2 ms和4 ms的高斯噪声时,采用本文方法的平均定位误差仅为9.96 m。应用结果表明,与单P波贝叶斯定位方法和单S波贝叶斯定位方法相比,采用本文方法的平均定位误差为31.97 m,定位精度分别提高了25.40%和60.78%。

Microseismic(MS)source location is a critical technology in MS monitoring.Traditionally,P-wave or S-wave travel time-based ray-tracing algorithms are adopted for a mine MS event location.However,only a few data are available for an MS event location usually,which may result in a large location error.A P-and S-wave arrival time combined objective function can obtain a relatively better location result.However,previous studies have encountered several challenges:1)the combined weighting should be a free parameter determined by the quality of P-and S-wave arrival time data;2)all the arrival times including bad data are adopted for an MS event location.To handle this,a P-and S-wave arrival time combined Bayesian location(P_SBL)method has been proposed for an MS event location.To reduce the influence of large picking errors,80%of arrival time data were randomly selected in each iteration.Two synthetic events and eight blasting events were used to test the proposed method.Synthetic results show that the average location error of the P_SBL method is only 9.96 m,when 2 and 4 ms Gaussian noises were separately included for the P-wave and S-wave travel time data.The application results demonstrate that the average location error of the P_SBL method is 31.97 m,which improves the location accuracy by 25.40%and 60.78%compared with the P_BL and S_BL methods,respectively.