Machine learning in subsurface physical properties and lithofacies prediction in a mining context

Machine learning in subsurface physical properties and lithofacies prediction in a mining context

Abstract To address energy challenges linked to decarbonization, geosciences are focusing more on advancing mineral resource exploration and exploitation. This study uses the Iberian Pyrite Belt, one of the world’s largest metallogenic provinces, as a test site to: (a) develop predictive models of p...

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Main Authors: A. Balaguera, M. Torné, R. Carbonell, A. Martí, J. Vergés, M. J. Jurado, P. Sánchez-Pastor, A. Farci, D. Davoise, S. Rodríguez
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Machine learning
Rock properties prediction
Lithofacies classification
Massive sulfide deposits
Exploration mining and Iberian pyrite belt
Online Access:https://doi.org/10.1038/s41598-025-11953-4
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https://doi.org/10.1038/s41598-025-11953-4

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