Scholarly record
AI-ASSISTED STRUCTURAL INTELLIGENCE FOR MINING PROJECTS: INTEGRATING PETROLEUM SUBSURFACE METHODS, DIGITAL INTERPRETATION AND GEOMECHANICAL MODELLING IN THE CAUCASUS AND BALKAN REGIONS
Abstract
Mining projects in structurally complex geological environments are significantly affected by uncertainty related to fault systems, fracture networks and groundwater pathways. This uncertainty directly impacts exploration efficiency, slope stability and operational safety. This paper presents an integrated workflow combining petroleum-style subsurface interpretation, AI-assisted digital geological analysis and geomechanical modelling. The approach focuses on transforming heterogeneous geological datasets into coherent structural intelligence applicable to mining decision-making. A pilot framework is proposed for structurally complex regions of the Caucasus and the Balkans, where geological conditions require integrated interpretation techniques. The results demonstrate that combining structural geology, digital tools and engineering validation significantly improves targeting, reduces uncertainty and enhances economic outcomes.
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