**4. Results**

*4.1. Three-Dimensional Primary Geochemical Halo Anomaly Data Volume Modeling Based on the C-V Model*

This section adopts the multifractal C-V model to analyze the spatial anomalous structure of elements and provides single-element anomaly signatures for the subsequent deep prediction.

Taking the ore-forming element Au as an example:

Using the ordinary kriging interpolation method [138–140], with the experimental variogram fitted to build a 3D data volume model of Au (Figure 5), the Au content value observably does not obey the normal distribution (Figure 6a). Therefore, the multifractal C-V model was carried out to identify Au anomalies.

Through counting the variation of volume with Au content, the lgAu-lgV scatter diagram was generated and lg-lg lines were fitted by the least square method (Figure 3b). Meanwhile, the fractal dimension can be obtained as follows:

*Minerals* **2022**, *12*, x FOR PEER REVIEW 11 of 31

The slopes of the lines correspond to fractal dimensions, and the inflection points are threshold values of geochemical abnormal intensity as shown in Table 1 and Figure 6b. *Minerals* **2022**, *12*, x FOR PEER REVIEW 11 of 32

**Figure 5.** Three-dimensional data volume model of Au. **Figure 5.** Three-dimensional data volume model of Au. Meanwhile, the fractal dimension can be obtained as follows:

**Figure 6.** (**a**) Histogram of the frequency distribution of Au. (**b**) lgAu-lgV curve of the 3D data volume model. **Figure 6.** (**a**) Histogram of the frequency distribution of Au. (**b**) lgAu-lgV curve of the 3D data volume model.


(**a**) (**b**) The slopes of the lines correspond to fractal dimensions, and the inflection points are **Table 1.** Fractal characteristics of 3D Au data volume model.

**Table 1.** Fractal characteristics of 3D Au data volume model. **Anomaly Classes Fractal Dimension R Square (R<sup>2</sup> ) Inflection Point Au (ppb)** Background area 0.2375 0.7304 1.0876 12.2349 Middle anomaly 10.697 0.9878 2.9049 803.3411 Internal anomaly 59.571 0.9707 3.0202 1047.6108 The orebody is compared with the outside anomalies, central anomaly and internal anomaly area by superposition, as shown in Figure 7b,c, and the three show a good spatial correlation with the orebody.

Outer anomalies 2.6262 0.9816 2.5137 326.3623 Middle anomaly 10.697 0.9878 2.9049 803.3411

Outer anomalies 2.6262 0.9816 2.5137 326.3623

The orebody is compared with the outside anomalies, central anomaly and internal anomaly area by superposition, as shown in Figure 7b,c, and the three show a good spatial

The orebody is compared with the outside anomalies, central anomaly and internal anomaly area by superposition, as shown in Figure 7b,c, and the three show a good spatial

correlation with the orebody.

*Minerals* **2022**, *12*, x FOR PEER REVIEW 12 of 32

**Figure 7.** Three-dimensional model of Au anomaly data volume in Zaozigou gold deposit. (**a**) outer anomalies of Au. (**b**) Middle anomalies of Au. (**c**) Inner anomalies of Au. **Figure 7.** Three-dimensional model of Au anomaly data volume in Zaozigou gold deposit. (**a**) outer anomalies of Au. (**b**) Middle anomalies of Au. (**c**) Inner anomalies of Au. **Figure 7.** Three-dimensional model of Au anomaly data volume in Zaozigou gold deposit. (**a**) outer anomalies of Au. (**b**) Middle anomalies of Au. (**c**) Inner anomalies of Au.

The middle and inner anomalies are mainly distributed inside and around the orebody, which accurately reflects the spatial spreading of the orebody and its trend. The middle and inner anomalies are mainly distributed inside and around the orebody, which accurately reflects the spatial spreading of the orebody and its trend. The middle and inner anomalies are mainly distributed inside and around the orebody, which accurately reflects the spatial spreading of the orebody and its trend.

On this basis, this study analyzed and visualized the 3D anomalous structures of the remaining 11 elements using the above model (Figure 8; Table 2). On this basis, this study analyzed and visualized the 3D anomalous structures of the remaining 11 elements using the above model (Figure 8; Table 2). On this basis, this study analyzed and visualized the 3D anomalous structures of the remaining 11 elements using the above model (Figure 8; Table 2).

**Figure 8.** lg-lg graph of the 3D data volume model. **Figure 8.** lg-lg graph of the 3D data volume model.


**Table 2.** Fractal characteristics of remaining elements in 3D data volume model.

Note: The cut-off value unit of Hg and Ag is ppb, others are ppm.

Figure 9 shows that the middle anomalies of As and Sb are mainly distributed near the elevation of 1700~1900 m. The middle anomalies of Ag, Cu, Pb and Zn have close relationship to the orebody. W, Mo, Co and Bi have two concentrations, the first one is located near the surface and the second one is distributed near the elevation of 2500 m. The Zaozigou gold deposit has multi-phase mineralization, forming a complicated spatial distribution of elements, while the C-V model can better identify the anomaly for recognizing the pattern of the primary geochemical halo in the Zaozigou gold deposit.

**Figure 9.** The middle anomalies distribution in Zaozigou gold deposit. **Figure 9.** The middle anomalies distribution in Zaozigou gold deposit.
