GEOSTATISTICAL SIMULATION OF ORE GRADE IN A DEPOSIT WITH MULTI-CORRELATED METALS

Master’s Dissertation
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dc.contributor.authorTshimangadzo NDOUen_ZA
dc.date.accessioned2026-09-09T12:19:12Z
dc.date.issued2025en_ZA
dc.descriptionGeostatistical simulation methods are increasingly used in mineral resources estimation. However, applying such methods to simulate the grades of metals that are strongly correlated within a deposit remains challenging. Therefore, it is desirable to develop improved geostatistical simulation methods for such a case. Previous research has explored transformation methods to remove or reduce the complexity of relationships among variables. Multivariate transformations, such as minimum/maximum autocorrelation factors (MAF) and projection pursuit multivariate transformation (PPMT), are widely applied in the field of geosciences to handle the correlation among variables prior to simulation with independent methods. This study evaluated the performance of two transformation methods, PPMT and MAF, within the Turning Bands Simulation (TBSIM) framework. The analysis focused on Fe and Al2O3, which are strongly negatively correlated in the dataset. The assessments considered accuracy, time efficiency, and the effectiveness of the transformations in managing variable dependency. The results indicate that neither the MAF nor the PPMT, nor the TBSIM framework was able to fully reproduce the correlation among Fe and Al 2O3. Nonetheless, the MAF proved more effective than the PPMT, as it handled the complexity of correlated variables more consistently. The PPMT was able to reproduce only Al2O3 after back-transformation, while its performance for Fe was less reliable.
dc.identifier.urihttp://hdl.handle.net/11660/13385
dc.publisherUniversity of the Free Stateen_ZA
dc.rights.holderUniversity of the Free Stateen_ZA
dc.titleGEOSTATISTICAL SIMULATION OF ORE GRADE IN A DEPOSIT WITH MULTI-CORRELATED METALSen_ZA
dc.typeDissertation

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