Abstract
High-accuracy determination of a microseismic (MS) location is the core task in MS monitoring. In this study, a 3D multi-scale grid Green’s function database, depending on recording wavefield frequency band for the target mining area, is pre-generated based on the reciprocity theorem and 3D spectral element method (SEM). Then, a multi-scale global grid search strategy is performed based on this pre-stored Green’s function database, which can be effectively and hierarchically processed by searching for the spatial location. Numerical wavefield modeling by SEM effectively overcomes difficulties in traditional and simplified ray tracing modeling, such as difficult wavefield amplitude and multi-path modeling in 3D focusing and defusing velocity regions. In addition, as a key step for broadband waveform simulation, the source-time function estimated from a new data-driven singular value decomposition averaged fractional derivative based wavelet function (DD-SVD-FD wavelet) was proposed to generate high-precision synthetic waveforms for better fitting observed broadband waveform than those by simple and traditional source-time function. Combining these sophisticated processing procedures, a new robust grid search and waveform inversion-based location (GSWI location) approach is integrated. In the synthetic test, we discuss and demonstrate the importance of 3D velocity model accuracy to waveform inversion-based location results for a practical MS monitoring configuration. Furthermore, the average location error of the 3D GSWI location for eight real blasting events is only 15.0 m, which is smaller than error from 3D ray tracing-based location (26.2 m) under the same velocity model. These synthetic and field application investigations prove the crucial role of 3D velocity model, finite-frequency travel-time sensitivity kernel characteristics and accurate numerical 3D broadband wavefield modeling for successful MS location in a strong heterogeneous velocity model that are induced by the presence of ore body, host rocks, complex tunnels, and large excavations.
Highlights
Mine microseismic (MS) monitoring can effectively evaluate the risks of a mining area and optimize production plan, in which MS location is a fundamental indicator parameter to study the fracturing location of rock mass, understand crack extension law, focal mechanism inversion, and analyze characteristics of mining activities [1,2,3]
We introduced 3D waveform inversion for mine microseismic event location and applied a multi-scale grid search algorithm based on global optimization into source location problem in a complex 3D local region
The average correlation travel time misfit of the modeled waveforms excited from MS-GSWI source location is error obtained by Wang et al [6] using 3D ray tracing-based location method is reduced to 26.2 m, smaller than that of the premeasured source location, which may be caused by currently inaccurate which confirms the importance of velocity model accuracy to a mine MS location
Summary
Mine microseismic (MS) monitoring can effectively evaluate the risks of a mining area and optimize production plan, in which MS location is a fundamental indicator parameter to study the fracturing location of rock mass, understand crack extension law, focal mechanism inversion, and analyze characteristics of mining activities [1,2,3]. Sci. 2020, 10, 7205 theoretical and picked arrival time of specified seismic phases. Ray tracing-based location methods are set up on the basis of geometrical ray approximation for high-frequency wave propagating, which have inherent difficulties in modeling multi-path effects and focusing and defocusing effects of realistic broadband wavefield propagation in complex velocity structure. They could be affected by large arrival time picking errors. The wave equation-based location can directly utilize the recording broadband waveform data, that is, it does not require the high-accuracy arrival time picking of specified seismic phase. Wave equation-based location methods usually fall into two categories, i.e., wavefield reverse-time migration-based location [7] and waveform inversion-based location [8]
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