Self-Structural Constraint Joint Inversion of Aeromagnetic and Gradient Data: Enhanced Imaging for Gold Deposits in Western Henan, China

Innovative magnetic techniques are pivotal for advancing mineral exploration. This study presents a self-structural constraint (SSC) method that jointly inverts aeromagnetic and gradient data to resolve high-resolution magnetic susceptibility models for concealed ores. The SSC framework integrates gradient structures from multi-component data as mutual constraints, enhancing signal differentiation and noise suppression. Unstructured tetrahedral grids and Poisson-derived analytical expressions address complex terrains, enabling robust inversions. Synthetic tests show SSC improves resolution by 40%–60% over conventional methods and resists 10% Gaussian noise. Applied to gold exploration in western Henan, China, SSC delineated concealed ore bodies (300–2000 m depth) along NE- and NW-trending faults, correlating with andesite-hosted magnetic anomalies. Combined with volcanic facies analysis, magma migration through these faults provided metallogenic materials and structural traps. The SSC-derived 3D model identified new drill targets, bridging geophysical imaging with geological processes. This advancement enhances the detection of deep, structurally controlled mineralization, offering a transformative tool for resource discovery.