Abstract

Microseismic (MS) source location is a fundamental and critical task in mine MS monitoring. The traditional ray tracing-based location method can be easily affected by many factors, such as multi-ray path effects, waveform focusing and defocusing of wavefield propagation, and low picking precision of seismic phase arrival. By contrast, the Gaussian beam reverse-time migration (GBRTM) location method can effectively and correctly model the influences of multi-path effects and wavefield focusing and defocusing in complex 3D media, and it takes advantages of the maximum energy focusing point as the source location with the autocorrelation imaging condition, which drastically reduces the requirements of signal-to-noise ratio (SNR) and picking accuracy of P-wave arrival. The Gaussian beam technique has been successfully applied in locating natural earthquake events and hydraulic fracturing-induced MS events in one-dimensional (1D) or simple two-dimensional (2D) velocity models. The novelty of this study is that we attempted to introduce the GBRTM technique into a mine MS event location application and considered utilizing a high-resolution tomographic 3D velocity model for wavefield back propagation. Firstly, in the synthetic test, the GBRTM location results using the correct 2D velocity model and different homogeneous velocity models are compared to show the importance of velocity model accuracy. Then, it was applied and verified by eight location premeasured blasting events. The synthetic results show that the spectrum characteristics of the recorded blasting waveforms are more complicated than those generated by the ideal Ricker wavelet, which provides a pragmatic way to evaluate the effectiveness and robustness of the MS event location method. The GBRTM location method does not need a highly accurate picking of phase arrival, just a simple detection criterion that the first arrival waveform can meet the windowing requirements of wavefield back propagation, which is beneficial for highly accurate and automatic MS event location. The GBRTM location accuracy using an appropriate 3D velocity model is much higher than that of using a homogeneous or 1D velocity model, emphasizing that a high-resolution velocity model is very critical to the GBRTM location method. The average location error of the GBRTM location method for the eight blasting events is just 17.0 m, which is better than that of the ray tracing method using the same 3D velocity model (26.2 m).

Highlights

  • As mineral resources exploitation goes deeper, the influence of dynamic disasters, such as fault slip, rockburst, and large area instability of rock mass becomes more and more serious [1,2,3]

  • We introduced the Gaussian beam reverse-time migration (GBRTM) technique into locating a mine microseismic event and considered a tomographic complex 3D velocity model

  • In order to better illustrate the effect of velocity model accuracy for the GBRTM location method, the synthesized waveforms generated by 2D test model combined with different homogeneous velocity the synthesized waveforms generated by 2D test model combined with different homogeneous models for migration are treated as comparisons

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Summary

Introduction

As mineral resources exploitation goes deeper, the influence of dynamic disasters, such as fault slip, rockburst, and large area instability of rock mass becomes more and more serious [1,2,3]. This results in Sensors 2020, 20, 2676; doi:10.3390/s20092676 www.mdpi.com/journal/sensors. Signals, we can analyze characteristic parameters of these dynamic activities, such as event excitation time, source location, event magnitude, and focal mechanism. Based on these basic parameters, we can further infer the stress states of rock mass and take effective prevention and control. According to differences in constructing objective functions (only using the travel time of specified seismic phase or the waveform information of finite band width), location methods can be generally classified into two categories, i.e., ray tracing-based location methods based on travel time and migration-based location methods using waveform processing

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