# Uncertainty of the 2D Resistivity Survey on the Subsurface Cavities
## 3 Results and Discussion
### Model Accuracy, Resolution, and Sensitivity
#### 3.3.1 Model Accuracy
Figure 6 shows the moderate correlation between the inverted images and the actual models. The obtained anomaly sizes were noticeably overestimated, whereas the anomaly depths were underestimated by about 0.4-1.3 m with regard to actual cavity models. In Figures 7, 8, 9 and 10c,d, the artefacts were clearly observed on the shallow part of the inverted models, particularly on the DD models. However, the resistivity imaging showed the intermediate cavity anomalies, the size overestimation and depth underestimation were limited the proper inference of the cavity information. In contrast, the deeper cavity models set at 10.2 m (T\({}_{5}\)) and 12.2 m (T\({}_{6}\)) depths were not recovered adequately by any of the arrays (Figures 7, 8, 9 and 10e,f). The obtained image correlations to the real model were weak (Figure 6). As shown in Figures 7, 8, 9 and 10e,f, the anomaly sizes were highly overestimated, making it very challenging to interpret the cavity geometries without prior subsurface information. The result also showed about 1.6-3.0 m anomaly depth underestimation relative to the actual cavity locations. As the cavity depth increases, significant resistivity underestimation occurred in anomaly zones. Furthermore, the shallow parts of the final models were contaminated by patched inversion artefacts. These poor model accuracies can lead to inappropriate interpretation in resistivity imaging. The anomaly responses of different arrays for a particular air-filled cavity were also examined graphically. We produced a one-dimensional (1D) horizontal resistivity profile from the inverted model of the cavity T\({}_{2}\), which crossed the mid-point of the cavity at 4.2 m depth (as shown in Figure 11). We extracted the resistivity values along the 1D profile for the DD, PD, WS, and PP arrays. The DD array showed the highest (steepest) anomaly gradient over the cavity zone, with the peak resistivity value of 2220 \(\Omega\)-m. In contrast, the PP array exhibited the lowest (gentlest) anomaly gradient, with the peak resistivity value of 1400 \(\Omega\)-m. The 1D profile of the PD and WS arrays showed moderate anomaly gradients that have the peak resistivity value of 1850 and 1700 \(\Omega\)-m, respectively. Figure 10: Inverted resistivity model using pole-pole (PP) array for the cavity targets: (**a**) T\({}_{1}\), (**b**) T\({}_{2}\), (**c**) T\({}_{3}\), (**d**) T\({}_{4}\), (**e**) T\({}_{5}\), (**f**) T\({}_{6}\). The rectangular boxes indicate the actual air-filled cavities. The broken lines represent the DOI threshold depths. The arrays that provided the steep anomaly gradient can recover cavity boundaries more accurately, while the arrays that yield the gentle anomaly gradient prevent the inference of the cavity boundaries. The 1D resistivity profiles were also used to assess the effect of air-filled cavity depth on the anomaly response of the arrays. Since the DD model provides the highest anomaly gradient, we used its models to generate 1D horizontal profiles for different depth cavity cases (Figure 12). The resistivity profile data were extracted along the profile lines that pass via the mid-points of the cavities T\({}_{1}\), T\({}_{2}\), T\({}_{3}\), T\({}_{4}\), T\({}_{5}\), and T\({}_{6}\) at depths of 2.2, 4.2, 6.2, 8.2, 10.2, and 12.2 m, respectively. The shallower cavity models showed a more robust resistivity amplitude than the cavity set at the relatively deeper position. For instance, the upper cavity T\({}_{1}\) indicates the maximum anomaly amplitude with the peak resistivity value of 6470 \(\Omega\cdot\)m. In comparison, the bottom cavity T\({}_{6}\) exhibits a minimum anomaly amplitude with a peak resistivity value of 1080 \(\Omega\cdot\)m. The substantial decrease in resistivity amplitude (gradient) as an increase in cavity depth can limit obtaining the anomaly geometries (Figure 12). Furthermore, the depth of investigation (DOI) index may show variation based on the type of arrays and the resistivity distributions of the survey domain.