To accurately interpret microseismic events and alleviate time localization deviations caused by background noise filtering, this study improves the time localization picking accuracy of microseismic signals is enhanced while preserving the background noise. The time window energy is calculated to quickly locate the arrival and end times of the signal, and the time-frequency characteristics of the signal are analyzed to identify instantaneous frequency mutation points, thus achieving precise time localization of the signal. We propose a time localization picking method (TWE-TFC) based on the joint integration of time window energy (TWE) and time-frequency characteristics (TFC). The performance of this method is validated using simulated signals, model test signals, and field monitoring signals, and it is compared with the STA/LTA method, the AIC method, and the two independent methods—the TWE and TFC methods. The research findings indicate that: (1) Distinct mutation characteristics in signal energy and instantaneous frequency are exhibited when mine seismic signals arrive at and depart from the geophone, which are crucial for achieving accurate time localization picking; (2) Characteristics of the arrival and end times of the mine seismic signals cannot be fully represented in a single time or frequency domain, which requires integrating time-frequency domain characteristic parameters to improve time localization accuracy; (3) Compared to the STA/LTA method and the AIC method, the proposed TWE-TFC method improves the picking accuracy of the signal arrival time by more than 67.76% and improves the capability to pick signal end time; (4) In comparison to the standalone TWE and TFC methods, the average time localization picking error of the TWE-TFC method is reduced by more than 68.11%.
Zhou et al. (Sun,) studied this question.