Abstract
A statistical modeling approach was applied to airborne geophysical data to locate areas favorable for gold mineralization in Rio das Velhas Greenstone Belt, Quadrilatero Ferrifero (QF). A positive spatial coincidence exists between banded iron formation (BIF) host-rocks, structures, and mineralogy that are indicative of gold mineralization. Quantitative relationships between airborne geophysical and geological data with known gold occurrences were determined and combined to produce predictive models to explore for Archean oxide-BIF-hosted deposits. Results map areas within exposed and subsurface rocks favorable for gold mineralization. Selected target areas for gold mineralization were checked in the field and provide validation that encourages future ground follow-up in the Rio das Velhas Greenstone Belt. The approach used in this study has shown great capability for linking geological and geophysical data and illustrates an approach that may significantly increase the odds of exploration success in the area.
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