# Detection of Rock Mass Defects Using Seismic Tomography
## 3 Synthetic Experiment
### Delineation of Non-Empty Anomalous Areas  
A total of 12 synthetic tests were carried out for four geometric sizes, multiplying three velocity structures. The geometry size of the original model is provided in Figure 3a, which shows a circular area with a radius of 30 mm in a 100 mm \(\times\) 100 mm square plane. The abnormal region mentioned in this section refers to the circular region. The area outside the circle is defined as the normal region. The wave velocity of the normal zone is 4.5 km/s. We tested three scenarios with abnormal region wave speeds of 1.5 km/s, 2.5, km/s, and 3.5 km/s. The actual radius of the anomalous zone is considered unknown information in the inversion. When preparing the prior models, we successively set the initial iteration radius to 10 mm, 20 mm, 30 mm, and 40 mm, as shown in Figure 3b. In each test, the wave velocity in the abnormal area in the prior model is the same as in the original model; the only difference is the range of the abnormal area. Twelve sensors are arranged around the plane at positions of 10 mm, 50 mm, and 90 mm on each side (shown as triangles in Figure 3). In total, in this 100 mm \(\times\) 100 mm square plane, 100 AE event locations are randomly generated using a uniform distribution (indicated by green crosses in Figure 3), ensuring each position within the given area has an equal probability of event occurrence. After event generation, the distances between adjacent events are calculated to verify whether these distances follow a uniform distribution or meet the expected distribution, thereby confirming the spatial randomness of the events. The plane is divided into 40 \(\times\) 40 coarse grids, and each coarse cell is divided into a 10 \(\times\) 10 refined grid. The standard deviation is 0 for both survey picks and event picks. The maximum number of iterations, the residual tolerance to ceasing iteration, and the quasi-Newton step size are set to 10, 1 \(\times\) 10\({}^{6}\), and 1.0, respectively. The standard deviations on \(\ln(V_{h})\) and \(E\) are 0.1. The standard deviations on \(\sigma_{x}\), \(\sigma_{y}\), \(\sigma_{z}\), and \(\sigma_{t_{0}}\) are 0.2. The correlation length \(\lambda\) is 5. According to the method described in Section 2 and the parameter configurations introduced above, the wave velocity field in each scenario is inversed. Figure 2: The schematic diagram of the workflow for identifying rock mass anomalies and their boundaries using seismic tomography at the experimental scale. Figure 3: Geometry and velocity of the original model (**a**) and prior models (**b**) and the inversion results (**c**). The green crosses and the triangles indicate the location of the AE events and the sensors, respectively. The colored lines show the ray paths. The text labels in subplot (**c**) explain the configuration of the prior model in the following format: [normal velocity, abnormal velocity, radius of the abnormal area]. Figure 3 shows the inversion results for the scenarios investigated using the original model (an abnormal zone radius of 30 mm with wave speeds of 1.5 km/s, 2.5 km/s, and 3.5 km/s) and four prior models (an abnormal zone radius of 10 mm, 20 mm, 30 mm, and 40 mm). The inversion results were examined in two stages: first, the accuracy of the velocity images was quantified; second, the reliability of the boundary recognition was analyze. To analyze the accuracy of the inversions, we first determined the velocity value of each node in the inversion results and separately calculated the velocity distribution within the actual range of the normal area (inner radius: 30 mm) and the abnormal area (outer radius: 30 mm), as shown in Figure 4a. The inversion accuracy of the normal area is significantly higher than that of the abnormal area. We noted that, except for Tests 4 and 8, the inversion results in the normal area are all distributed around 4.5 km/s. The inversion accuracy of the anomalous zone is affected by the initial iteration size (prior model) and the true normal-abnormal velocity difference.