Probabilistic Modelling of Geologically Complex Veins of the Barberton Greenstone Complex at Fairview Mine, South Africa

Abstract

Achieving accurate estimations of recoverable tonnage relies on a robust geological modelling process. To ensure this accuracy, it is crucial to incorporate information from exploration, grade control, and sampling, considering well-identified mineralization controls. However, modelling the geology of complex orebodies, especially veins, poses challenges due to their intricate mineral accumulation processes and variable structural complexities. Fairview Mine’s Main Reef Complex (MRC) reef is highly discontinuous, with most of the valuable mineralized zone concentrated within localized ore shoots that intersect various lithologies, exemplifying these challenges. This study aimed to improve the modelling of veins at the mine, striving for a more accurate representation of the mineralization zones. To achieve this, a hybrid approach was employed, combining a deterministic method based on minimum curvature interpolation with a probabilistic method using anisotropic inverse distance weighting for categorical/discrete variables. The subsequent tonnage estimates showed a robust correlation with actual production output. The initial deterministic model established the large-scale geological trend, providing a foundation for estimating a probabilistic model. The iterative nature of probabilistic modelling allowed for the analysis of various probable options, facilitating the selection of the model that best captured the underlying geology. This approach enabled robust mathematical modelling while incorporating valuable input from geological knowledge and expectations.

Keywords

• vein modelling
• anisotropic inverse distance weighting
• probabilistic modelling
• minimum curvature interpolation
• Barberton
• geological modelling