*3.3. Method for Predicting Deep Gold Resource Potential in the Ore-Controlling Fault Zones Based on Shallow Resources*

### 3.3.1. Methodological Overview

According to the trend extrapolation principle, this predictive method was designed to extrapolate the resources in the deep prediction areas with metallogenic conditions similar to the shallow parts from the statistical analysis of the proven resources in the shallow parts.

#### 3.3.2. Predictive Factors

The main predictive factors include ore-controlling faults, the cumulative proven gold resources at an elevation of approximately −2000 m and above, the average gold content per unit area at an elevation of approximately −2000 m and above, and the area of ore-controlling faults at an elevation of −5000–−2000 m on the vertical longitudinal projection map.

The deep resources were estimated using this equation: deep resources = ore-bearing rate × the area of the deep prediction areas. In this equation, the ore-bearing rate is equal to the average gold content per unit area in the shallow part, and the area of the deep prediction areas is equal to the area of ore-controlling faults at an elevation of −5000–−2000 m on the vertical longitudinal projection map. In other words, the vertical longitudinal projection map was obtained by cutting a 3D geological model. Then, the average gold content per unit area (i.e., ore-bearing rate) was determined based on the distribution of orebodies at different depths in the vertical longitudinal projection map. Subsequently, the boundaries of the ore-controlling faults in the vertical longitudinal projection map were reasonably determined based on the prediction depth, and then the area of the faults was accordingly calculated. Finally, the potential gold resources in the deep part were estimated by making an analogy with those in the known shallow area.

#### 3.3.3. Prediction Process

The resource potential of deep-seated gold deposits of a fault was predicted as follows: 3D geological modeling → obtaining the statistics of accumulative proven resources in the shallow part using the 3D geological model → obtaining the vertical longitudinal projection map by cutting the 3D geological model → obtaining the statistics of the ore-bearing rate → determining the area of the deep prediction areas → estimating the resources in the deep part.
