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Mutobvu, Tyson, Pretorius, Hendrik, Muller, Charles Johannes, Mabala, Mahlomola Isaac (2024) Probabilistic Modelling of Geologically Complex Veins of the Barberton Greenstone Complex at Fairview Mine, South Africa. Minerals, 14 (4) doi:10.3390/min14040343

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Reference TypeJournal (article/letter/editorial)
TitleProbabilistic Modelling of Geologically Complex Veins of the Barberton Greenstone Complex at Fairview Mine, South Africa
JournalMinerals
AuthorsMutobvu, TysonAuthor
Pretorius, HendrikAuthor
Muller, Charles JohannesAuthor
Mabala, Mahlomola IsaacAuthor
Year2024Volume<   14   >
Issue<   4   >
URL
DOIdoi:10.3390/min14040343Search in ResearchGate
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Mindat Ref. ID17232227Long-form Identifiermindat:1:5:17232227:0
GUID0
Full ReferenceMutobvu, Tyson, Pretorius, Hendrik, Muller, Charles Johannes, Mabala, Mahlomola Isaac (2024) Probabilistic Modelling of Geologically Complex Veins of the Barberton Greenstone Complex at Fairview Mine, South Africa. Minerals, 14 (4) doi:10.3390/min14040343
Plain TextMutobvu, Tyson, Pretorius, Hendrik, Muller, Charles Johannes, Mabala, Mahlomola Isaac (2024) Probabilistic Modelling of Geologically Complex Veins of the Barberton Greenstone Complex at Fairview Mine, South Africa. Minerals, 14 (4) doi:10.3390/min14040343
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Abstract/NotesAchieving 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.

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LocalityCitation Details
Fairview Mine, Bickenhall Farm, Barberton, Mbombela Local Municipality, Ehlanzeni District Municipality, Mpumalanga, South Africa

Mineral Occurrences

LocalityMineral(s)
Fairview Mine, Bickenhall Farm, Barberton, Mbombela Local Municipality, Ehlanzeni District Municipality, Mpumalanga, South Africa Arsenopyrite, Chert, Conglomerate, Gneiss, Granite, Granodiorite, Greenschist, Greenstone, Greywacke, Muscovite, Native Gold, Pyrite, Pyrrhotite, Quartz, Sandstone, Schist, Sericite, Shale


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