AI-Driven Targeting and LOZA Geophysical Integration

An integrated two-phase exploration program combining AI-driven mineral targeting with advanced geophysical validation.

Phase 1 focused on AI-based analysis of multi-source datasets, including spectral, structural, and geochemical indicators, to delineate initial target zones and mineralisation trends.

Phase 2 incorporated gas anomaly modelling and high-resolution LOZA-2N geophysical profiling. The study identified active methane anomalies, along with strong spectral responses associated with malachite and arsenopyrite, indicating both oxide and sulphide mineralisation signatures.

LOZA-2N profiling delineated multiple anomalous subsurface zones, interpreted as structurally controlled mineralised bodies. These zones are predominantly consistent with stratiform copper–gold mineralisation, with superimposed IOCG-style mineralisation signatures linked to hydrothermal overprinting.

The integration of AI targeting, gas anomalies, spectral indicators, and LOZA geophysics enabled the definition of coherent mineralised corridors and high-confidence drill targets, providing a robust foundation for follow-up exploration and drilling.