Seismic energy distribution and hazard assessment in underground coal mines using statistical energy analysis

This study proposes a method for hazard assessment in mines based on seismic energy distribution. To minimize the influence of external factors on conventional methods, a long-term large-scale seismicity observation was carried out in nine underground coal mines in China. A significant amount of data from seismic events were obtained and used as the statistical sample. For ease of analysis, the seismic energy was formatted by uniform criteria. A distribution-free hypothesis test was applied to determine the probable pattern of the seismic sample. The probability distribution of seismic datasets, the energy characteristics of abnormal seismic events and their commonality with rock burst were discussed. Hazardous seismic outliers were identified based upon the statistical rule. Finally, the seismic energy gradient was determined, and the weighted energy eigenvalue was created to balance the hazard assessment. Our main findings show that the randomization of seismic events is restrained. Seismic energy distribution is abnormal and inconsistent with other common distribution types. Both the anomalous critical values used for identifying the seismic outliers and the weighted energy eigenvalue of a continually increasing energy gradient played a positive role in evaluating its hazard level. The new assessment method has been shown in this study to be objective and effective.