End-to-End Mineral Exploration with Artificial Intelligence and Ambient Noise Tomography

arXiv:2403.15095v1 Announce Type: cross
Abstract: This paper presents an innovative end-to-end workflow for mineral exploration, integrating ambient noise tomography (ANT) and artificial intelligence (AI) to enhance the discovery and delineation of mineral resources essential for the global transition to a low carbon economy. We focus on copper as a critical element, required in significant quantities for renewable energy solutions. We show the benefits of utilising ANT, characterised by its speed, scalability, depth penetration, resolution, and low environmental impact, alongside artificial …

abstract ambient ant artificial artificial intelligence arxiv carbon copper cs.lg discovery economy exploration focus global intelligence low noise paper physics.geo-ph resources transition type workflow