Аннотация
The Kargoba mineral occurrence in East Kazakhstan covers an area of 25.5 km2 and is characterized by rugged mountainous terrain at elevations of 800–1,013 m above sea level. This study presents a methodology for high-resolution unmanned aerial vehicle (UAV)-based aeromagnetic surveying aimed at targeting copper-molybdenum mineralization. The study sought to identify geophysical targeting criteria and refine the boundaries of prospective zones. The survey was conducted using a DJI Matrice 300 RTK quadcopter equipped with a Geoshark MG30GM quantum magnetometer. Magnetic-field interpretation included derivative-based transforms, namely the tilt derivative (TDR), first vertical derivative (VDR), and total horizontal derivative (THDR), as well as three-dimensional modeling of magnetic sources. Six anomalous zones were delineated. Zone A-2 was identified as the highest-priority exploration target, exhibiting an anomaly amplitude of up to 500 nT and a spatial association with a granodiorite intrusion. The following criteria were established for targeting porphyry mineralization: anomaly amplitudes of 200–500 nT, horizontal gradients exceeding 3 nT/m, anomaly strike lengths of 0.5–2 km, spatial association of positive and negative magnetic anomalies, and spatial correlation with hydrothermal alteration zones. Comparison of the identified anomalies with published data from the Lavrion district in Greece supported the applicability of the selected approach. A key diagnostic feature is the spatial association of anomalies of opposite polarity, reflecting the structural and geological controls on mineralization. The high spatial resolution of the aeromagnetic survey at Kargoba enables more precise delineation of prospective mineralized zones and more effective positioning of exploration drillholes. The use of a UAV considerably facilitates and accelerates surveying in rugged and inaccessible terrain. Compared with conventional ground surveys and crewed airborne surveys, it reduces survey time and costs while maintaining high data quality. The proposed approach therefore offers a cost-effective, lower-risk means of targeting concealed mineralized bodies and extends the capabilities of mineral exploration in remote regions.