Three-Dimensional Mineral Prospectivity Modeling with Geometric Restoration: Application to the Jinchuan Ni–Cu–(PGE) Sulfide Deposit, Northwestern China

Structural deformation is ubiquitous throughout geological history. For a mineral deposit that underwent structural deformation after its formation, its geological architecture may have been severely distorted from its original geometry. Due to lack of concern for this fact, the effectiveness of existing mineral prospectivity methods could be limited in areas that experienced structural deformation. This paper proposes a three-dimensional (3D) mineral prospectivity modeling method with geometric restoration. An energy-based geometric restoration approach is presented to restore the existing geometry of geological architecture to the original one according to a series of prior constraints. To represent the original ore-forming environment, the original mineralization distribution and the predictor variables are estimated from the restored 3D geological models. Then, Random Forest is applied to build the mineral prospectivity model that associates predictor variables with the original mineralization distribution. The proposed method was applied to the world-class Jinchuan Ni–Cu–(PGE) sulfide deposit, which underwent significant off-fault deformation after its formation. It was found that, by restoration of the geometry of geological objects and the mineralization distribution, the predictor variables are more reasonable and significant to indicate spatial associations to the mineralization at Jinchuan. This led to a more accurate prospectivity model with superior evaluation metrics (AUCs, F1 scores, kappa coefficients, and PR curves, etc.) compared with the prospectivity model built without geometric restoration. Therefore, 3D mineral prospectivity modeling with geometric restoration is probably much more effective and reliable in quantifying spatial associations with mineralization and in targeting subsurface orebodies in areas that underwent structural deformation.