The influence of supervised and unsupervised methods in the analysis of low density stream sediments in the regional prospecting of pegmatites in the state of Espírito Santo, Araçuaí Orogen - Eastern Pegmatite Province of Brazil

• Published in: Chemie der Erde 2024-11, Vol.84 (4), p.126181, Article 126181
• Main Authors: da Costa, Flávia Compassi, Ribeiro, Brener Otávio Luiz, Leão, Lucas Pereira, de Paiva-Silva, Paulo Augusto, Scholz, Ricardo
• Format: Article
• Language: English
• Subjects: Pegmatite; Principal component analysis; Regional geochemical prospection; Stream sediment
• ISSN: 0009-2819
• DOI: 10.1016/j.chemer.2024.126181

The state of Espírito Santo is located in Brazil southeastern and it is geologically inserted in the Eastern Brazilian Pegmatite Province in the Araçuaí Orogen. This province is one of the most important pegmatite provinces in the world, known mainly for the occurrence of gem-quality minerals and high grade lithium deposits. Although Espírito Santo has a geological framework with many granite intrusions similar to those hosting mineralized pegmatites in Minas Gerais, it hasn't been acknowledged as a potential pegmatitic area. There are reports of mineralization of beryl (aquamarine), topaz, amethyst, and chrysoberyl in the state's mineral history. I this research we use regional stream sediment geochemical data of the Espirito Santo State, to create prospective geochemical maps to map gemological pegmatites. To do so, primary descriptive statistical analyses as well as Pearson and Spearman correlations and Principal Component Analysis (PCA) were used to select elements associated with pegmatites. The geochemical prospectivity mapping was carried out by supervised and unsupervised approaches. The supervised method was based on integration of the elements by C-A fractal models, used to define the geochemical thresholds, and fuzzy logic methodology to integrate weighted geochemical maps. The unsupervised approach, however, was based on interpolation of the representative principal component scores. All models were validated using the Prediction Area plot (P-A plot). The results of our research showed that unsupervised methodology overperformed the other weighted supervised models, with a prediction rate of 78.14 % and prospectivity of 0.87. The final results also show a pegmatite prospectivity map for the Espirito Santo state, that indicates a great exploration potential for gemological minerals.) [Display omitted]