Abstract
Geostatistical modeling of total and oxide copper grades in copper porphyry deposits presents challenges arising from inherent inequality constraints and soft variations across geological domains. The conventional joint simulation approach, while addressing the interdependence of these grades, often yields patchy and unstructured geological domain results. To address these challenges, we propose a comprehensive methodology. Firstly, a change of variable technique is applied to overcome the inequality constraint, ensuring that the simulation results align with the natural relationship between oxide and total copper grades. Secondly, our methodology introduces a novel joint simulation approach, incorporating supergene and hypogene zones as controlling geological domains. This enables the reproduction of the soft variation of grades along mineralization zone boundaries. Thirdly, soft geological data, crucial for capturing long-range geological features, are integrated into the model. Leveraging an implicit geological modeling approach, our methodology incorporates soft geological data to enhance the realism of simulated results. This inclusive approach addresses the challenge of patchy and unstructured simulation outcomes. We validate our proposed methodology using real data from a copper porphyry deposit, conducting both local and global statistical assessments. Comparative analyses with traditional modeling approaches highlight the effectiveness of our methodology in overcoming the complexities associated with total and oxide copper grade modeling in porphyry deposits.