Relocating Mining Microseismic Earthquakes in a 3-D Velocity Model Using a Windowed Cross-Correlation Technique

Abstract

Microseismic source location is a fundamental research interest in real-time microseismic monitoring and hazard risk assessment, and it provides the basis for determining the fracture zones and calculating seismic source parameters of the microseismicity (e.g., the event magnitude, the focal mechanism). In the present work, we carefully relocate some microseismic earthquakes that occurred in the Yongshaba mine (China) using the shooting 3-D ray-tracing (3D-RT) method based on a high-resolution 3-D velocity model, which is determined by a large amount of seismic data. Furthermore, a semiautomatic waveform cut method based on the cross-correlation (CC) technique (WCC) is developed for a quick, robust and precise determination of the direct P-phase relative delay times. Compared with the full waveform crosscorrelation (FWCC)-based method, the WCC-based method is free from the influence of complex later-phase waveform spectra. To verify the proposed method, we artificially generate the locations of 892 synthetic microseismic events, the P-phase travel times of which are calculated based on the given 3-D velocity model and the 3-D ray-tracing technique. The relocated hypocentres of these synthetic events obtained by the developed method are improved compared with those obtained by a homogeneous velocity model and the straight line-ray tracing based L1 norm time difference (TD) method (HV-SL-TD1), as well as those obtained by the 3-D velocity model and the straight line-ray tracing based L1 norm and L2 norm TD methods (3D-SL-TD1 and 3D-SL-TD2). Finally, we apply the proposed method to eight experimental blasts with pre-measured locations. The synthetic and application tests show that, despite some multi-path phenomena existing in the ray-tracing methods, the WCC-based method performs as well as the experienced manual picking method, and the results obtained by the 3D-RT location have smaller location errors (∼30 m) than those of the homogeneous velocity model-based methods (>40 m). The TD-based method is slightly better than the trigger time (TT)-based method when using the same norm, and the location precision of the L1 norm-based methods have a better resilience to larger picking errors than that of the L2 norm-based methods. Further improvements can be obtained by improving the resolution of the 3-D velocity model and including spatial voids in the model (e.g., tunnels and cavities) for the inversion.

High-Accuracy Location of Microseismic Events in a Strong Inhomogeneous Mining Environment by Optimized Global Full Waveform Inversion

“…In order to further improve fitting performance for complex waveforms, we put forward a new approach to obtain the source-time function based on observed waveforms themselves, namely the DD-SVD-FD wavelet estimation. The detailed steps are shown as follows: firstly, each recording waveform containing the first half period of P-phase arrival is cut by the semiautomatic windowing method proposed by Wang et al [6]: (1) A two passes, four-poles, 200 Hz lowpass Butterworth filter was conducted to the recorded signal. 2We manually picked a rough time T 1 before the P-phase arrival and a rough time T 2 after the first peak amplitude; (3) The T 2 is automatically extended to the next zero amplitude time T 3 ; (4) The windowed waveform corresponds to the filtered time series in the time interval [T 1 , T 3 ].…”

“…Velocity model 2D slices under different smoothing scales are shown in Figure 1a. The synthetic test was carried out using the premeasured locations (locations measured before the blasting events) of eight practical blasting events and their corresponding sensors (Table 1 in [6]), and the waveform dataset was generated by the unsmoothed target 3D velocity model with 120 Hz dominant frequency referring to the data spectrum analysis. The location of blasting event 8 is taken as the example and its waveform inversion-based location results are demonstrated in Figure 1.…”

“…The multi-scale grid generation introduced above combining with the multi-frequency-band grid search strategy, as described in Section 2.4, can gradually optimize the location results and keep a reasonable amount of Green's function storage and computational cost. [6]). The background is a 2D sliced plane of the 3D velocity model, which is determined through the least square vertical distance from all sensors to the plane.…”

“…Taking the black star in Figure 4 as the source location and setting the source as an explosion source, and considering that the main frequency of a blasting event is usually within 250 Hz and the dominant frequency is usually within 120 Hz, a Ricker wavelet with dominant frequency 120 Hz is taken as the source-time function for SEM modeling. The time interval between adjacent wavefronts shown in Figure 4 is 0.004 s. It can be seen that the SEM method can precisely model the focusing and defocusing effects in complicated velocity regions compared with the ray tracing technique (Figure 1 in [6]): The low-velocity regions have focusing effects on the transmitted waves and produce diffraction and multi-path effects. There are defocusing effects on waves propagating through the high-velocity regions, which are usually difficult to rapidly and appropriately calculate travel-time field of waves passing through the strong high-velocity regions by using the ray-shooting method.…”

“…Moreover, they could be easily affected by large arrival time picking errors. The above shortcomings increase difficulties in an accurate location with ray tracing-based location technique [6]. In the past few years, with the development of computer technologies and improvement of numerical modeling methods, wave equation-based location methods have been gradually introduced and applied to a MS location in the fields of mining and oil-gas exploration.…”