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A New Geochemistry Exploration Method to Identify Deep VMS-Type Deposits - Application to the Cu-Zn Neves-Corvo Deposit, Iberian Pyrite Belt

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ABSTRACT: Mineral exploration in the Iberian Pyrite Belt follows increasingly deeper targets. The present study introduces an innovative methodology for the detection and identification of blind metallic mineral deposits, in particular volcanogenic massive sulfides based on surface rock coatings. This approach follows the identification pathways of upward metal escape routes and metal distribution in rock fractures located in different anisotropic or isotropic planes above the Neves-Corvo VMS deposit ore lenses, using VP-SEM-EDS and XRD. Coatings are dominated by poorly crystalline to amorphous phases, with goethite and birnessite as the main Fe- and Mn-bearing minerals. Copper, zinc and lead are systematically enriched in coatings developed above or near the ore bodies, reflecting chalcopyrite, sphalerite and galena acidic leaching. Tin shows a restricted and heterogeneous distribution, while Ni and Co display no systematic relationship with the ore bodies. Barium and late Ba-Pb-(Zn) mineralization along fault zones record VMS mineralization. Lead isotopic coating signatures overlap those of IPB massive sulfide deposits, confirming a dominant VMS-derived contribution. Fe-Mn coatings were formed by precipitation from ascending meteoric fluids that leached metals from massive sulfides, their alteration halos, and surrounding lithologies, preserving the geochemical footprint of buried mineralization. This approach constitutes a new patented exploration tool.

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Palavras-chave

Geochemistry Rocks Mineral exploration Mineralization Massive sulfide deposits Geochronology Iberian Pyrite Belt

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Citação

Morais, I., Albardeiro, L., Rosado, L., Mirão, J., Matos, J. X., Batista, M. J., Silva, T., Barrulas, P., & de Oliveira, D. (2026). A New Geochemistry Exploration Method to Identify Deep VMS-Type Deposits - Application to the Cu-Zn Neves-Corvo Deposit, Iberian Pyrite Belt. In: Minerals, 2026, vol. 16 (6), article 607. https://doi.org/10.3390/min16060607

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MDPI

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