Microseismic monitoring of rockbursts with the ensemble Kalman filter

Abstract

ABSTRACTWe introduce an algorithm to monitor seismic velocity changes associated with rockbursts in mines, through microseismic monitoring. Rockbursts are extreme events resulting from the complex interaction between mining activities and geology, and represent a significant threat to mines. In recent years, the use of passive seismic monitoring for mine safety and productivity has progressed substantially, aiming to understand and predict this hazard. In this work, additional value is given to microseismic monitoring, using it to map temporal changes of seismic velocity in the rock mass that can potentially be associated with stress changes leading to rockbursts. An application of the ensemble Kalman filter is presented for assimilating travel times of seismic P and S waves in a fast and efficient way in order to update the mine's velocity model. Combining sequential Gaussian simulation and ensemble Kalman filter techniques, we were able to monitor the occurrence of velocity changes underground. The proposed approach allows zones to be highlighted where the rock mass is under stress and where potential risk can be expected. The performance of the method was first tested on several synthetic scenarios and, subsequently, on a real 3D case of a deep mine in Canada. The application on the real data set allowed mapping a change in velocity in the area where a rockburst occurred four hours afterwards.