## 3 Synthetic Test  
To test the proposed 3D GSWI location method, the 3D velocity model inverted through ray tracing tomography based on P wave travel-time data by [PERSON] et al. [50] and shown in Section 4.1 was selected as the target velocity model. Moreover, velocity models with different smoothing scales were used to verify the importance of velocity model accuracy to the 3D GSWI location method. In this method, a 3D spatial Gaussian function has been used for smoothing the original high-resolution velocity model, and the standard deviation is used to define the length of smoothing scale. This different smoothing length approximately reflects the different resolution limit of the ray-based tomographic model obtained from transmission wave data with various signal frequency content [51], while high and low velocity anomalies that are incorrectly positioned may result in a large location error are not considered in this paper. That is, we only conducted a specific qualitative assessment to consider the influence of insufficient resolution of inverted velocity model on GSWI location errors. 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 figure shows that with the increase of smoothing lengths, the smoothed velocity models gradually tend to be homogeneously distributed, which are characterized by the ray paths from the source to each sensor that gradually become straight lines. The 17.5 m smoothing obtained a 0 m location error, as when a relatively accurate velocity model is used for location, the waveform information related to source location could still be reasonably explored and inverted by the grid search and waveform inversion-based location method. When the model error increases (the smoothing length continues to increase), the source information contained in the data cannot be inverted or stacked correctly, and the location error introduced by velocity error appears. Location errors caused by reduction of velocity model accuracy do not follow a monotonous change law, due to location result is also being controlled by some other factors, such as specific triggered sensor geometric distribution and inhomogeneity of velocity structures near the source location. Furthermore, the overall location error increases with the decrease of velocity model accuracy (Figure 2), which confirms the necessity of an accurate 3D velocity model to waveform inversion-based location in regions with complex geological structural property. In addition, the errors of SGWI location results in this synthetic test with a small number of test events are all within 40 m. It is complicated to perform a completely quantitative analysis explaining the coupling effect between the location error and the current velocity model inaccuracy (such as by smoothing). The systematic location error analysis will be left to the future. Figure 1: Grid search and waveform inversion-based (GSWI) location results under different velocity model smoothing scales. (**a**) Velocity models under different smoothing scales and ray paths from source to each triggered sensor. The 2D slices of 3D tomographic velocity models showing here are determined by the summation least square of the vertical distances from all sensors. The backgrounds are the smoothed velocity models with smoothing lengths equaling to 35, 70, 140 and 210 m, respectively. The dotted lines show the ray tracing paths from the source location to corresponding triggered sensors.