ELECTROMETRIC DATA DERIVED FROM AIRBORNE GEOPHYSICAL SURVEYS IN THE NORTHWESTERN REGION OF THE BUKANTAU AREA

This doctoral dissertation presents a comprehensive investigation of electrometric indicators using airborne transient electromagnetic (TEM) surveys. Advanced inversion algorithms (neural networks, Bayesian schemes, and deep learning) were developed to analyze apparent resistivity at depths of 30–50 m. A statistical analysis of resistivity distribution was performed, large-scale structures (granitoid bodies, faults, carbonate ridges) were characterized, and mineralization prospects were evaluated by integrating AEM data with hydrogeological models. The findings support an optimal strategy for subsequent ground geophysical and geochemical exploration.