Targeting of Gold Deposits in Amazonian Exploration Frontiers using Knowledge- and Data-Driven Spatial Modeling of Geophysical, Geochemical, and Geological Data

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.

Prospectivity analysis of orogenic gold deposits in Saqez-Sardasht Goldfield, Zagros Orogen, Iran

“…Airborne radiometric data are capable to map felsic igneous rocks, which contain high amounts of radioactive elements (i.e., Th, K and U) and the related hydrothermal activities (Silva et al, 2003;de Souza Filho et al, 2007;Magalhães and Souza Filho, 2012;Almasi et al, 2014). In this regard, the ratio of K/Th (after Airo, 2001Airo, , 2007) is used to recognize the above-mentioned geological features.…”

Nickel Prospective Modelling Using Fuzzy Logic on Nova Brasilândia Metasedimentary Belt, Rondônia, Brazil

“…The geochemical maps of Co and Ni were interpolated on a regular grid with cells of 500 m using GeoData Analysis System (GeoDAS) (Cheng, 2000), with a minimum of three samples within a radius of 10 km (Andrade, 2008) the phenomenon (eg, mineral deposit) (Bonham-Carter, 1994;Harris et al, 2001;Nóbrega, 2001;Porwal et al, 2003;Nykanen & Ojala, 2007;Carrino et al, 2011;Magalhães & Souza Filho, 2012;Silva et al, 2012).…”

Airborne Geophysical Data Analysis Applied to Geological Interpretation in the Alta Floresta Gold Province, Mt

“…Similar classes (fuzzy clusters) are grouped together according the statistical behavior of the data, without needing training points (e.g. Looney & Yu, 2000;Lammoglia, 2006;Magalhães & Souza Filho, 2012). The method was used in order to refine the geological interpretation to ensure careful individualization of the rocks found in the study area.…”