Targeting of Gold Deposits in Amazonian Exploration Frontiers using Knowledge- and Data-Driven Spatial Modeling of Geophysical,Geochemical, and Geological Data |
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Authors: | Lucíola Alves Magalhães Carlos Roberto Souza Filho |
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Institution: | (1) Institute of Geosciences (IG), P.O. box 6152, State University of Campinas - UNICAMP, Campinas, SP, 13083-970, Brazil |
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Abstract: | This paper reports the application of weights-of-evidence, artificial neural networks, and fuzzy logic spatial modeling techniques
to generate prospectivity maps for gold mineralization in the neighborhood of the Amapari Au mine, Brazil. The study area
comprises one of the last Brazilian mineral exploration frontiers. The Amapari mine is located in the Maroni-Itaicaiúnas Province,
which regionally hosts important gold, iron, manganese, chromite, diamond, bauxite, kaolinite, and cassiterite deposits. The
Amapari Au mine is characterized as of the orogenic gold deposit type. The highest gold grades are associated with highly
deformed rocks and are concentrated in sulfide-rich veins mainly composed of pyrrhotite. The data used for the generation
of gold prospectivity models include aerogeophysical and geological maps as well as the gold content of stream sediment samples.
The prospectivity maps provided by these three methods showed that the Amapari mine stands out as an area of high potential
for gold mineralization. The prospectivity maps also highlight new targets for gold exploration. These new targets were validated
by means of detailed maps of gold geochemical anomalies in soil and by fieldwork. The identified target areas exhibit good
spatial coincidence with the main soil geochemical anomalies and prospects, thus demonstrating that the delineation of exploration
targets by analysis and integration of indirect datasets in a geographic information system (GIS) is consistent with direct
prospecting. Considering that work of this nature has never been developed in the Amazonian region, this is an important example
of the applicability and functionality of geophysical data and prospectivity analysis in regions where geologic and metallogenetic
information is scarce. |
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