Adaptive Focusing Gravity Inversion based on Multi-Evaluation-Driven Mechanism

Gravity is pivotal in fundamental geological surveys and resource and energy exploration, yet volumetric and superposition effects of the gravity field have long posed a technical bottleneck in achieving high vertical resolution. Although boundary resolution is enhanced by applying mathematical transformations to the density model within a regularized stabilization framework and by constructing a focusing reweighting matrix, traditional focusing algorithms still rely heavily on subjective judgment in setting the focusing interval and deciding whether piecewise focusing is required. Such subjectivity reveals a lack of quantitative analysis. An innovative adaptive focusing iterative algorithm based on the minimum-support principle is introduced, integrating four quantitative assessment methods—Mean Square Error, Edge Sharpness Operator, overall Gradient Evaluation Operator, and Variance Evaluation Operator—to adaptively determine an optimal focusing strategy. Numerical simulations indicate that the approach not only automatically adjusts the focusing interval but also achieves high-resolution detection of target anomalous bodies. Tests conducted on real data from the Dahongshan area confirm that the method can finely characterize anomalous bodies in that region.