Abstract
Rock burst prediction is a worldwide challenge that we have long tried to overcome. This study tentatively proposed a method to regionally predict rock burst hazards using microseismic energy attenuation. To verify the feasibility of the proposal, first, the mechanism of microseismic energy propagation and attenuation in rock medium was explored, and dominant attenuation characteristics of microseismic waves were analyzed. Second, a spatial attenuation model of microseismic energy was established, and the average energy attenuation coefficient for each wave path was defined. A 3D seismic energy attenuation inversion algorithm was put forward, and the corresponding computation matrix was developed. Third, a continuous microseismic field investigation was carried out in a deep coal mine. Seismic energy attenuation coefficient was confirmed using the calibrated focus position and energy determination. Based on data discretization processing, energy attenuation inversion and tomography, potential rock burst hazard regions were strictly zoned in mining areas. Finally, regional prediction results obtained from the microseismic energy attenuation were compared with the direct measurement results obtained from the classical drilling dust method to verify the reliability of proposed approach. It turns out that rock burst hazard regions predicted by the microseismic energy attenuation agreed well with the objective hazardous situations. Seismic energy attenuation coefficient is a significant evaluation factor that directly mirrors the inelastic performance of rock medium. Energy attenuation coefficient threshold used for determining the rock burst hazard regions was 3.0 km−1. Reliability of the seismic energy attenuation inversion and tomography was closely related to the spatial distribution of microseisms in a localized region. The optimum spatial density of microseisms was 0.2 m−3. Regional rock burst prediction using microseismic energy attenuation is an effective approach for revealing potential hazardous regions in deep mining conditions. This approach improves the pertinence of geological hazard prevention and provides a beforehand reference for targeted hazard management.
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