Targeted inversion of airborne electromagnetic data for improved imaging of large-scale hydrogeologic structures

Abstract Airborne electromagnetic (AEM) surveys provide rapid, basin-scale coverage for groundwater studies, yet conventional L2-norm inversions often fail to resolve thin but important hydrogeologic units such as the Corcoran Clay in California's Central Valley. We introduce a targeted inversion approach that incorporates prior geological knowledge using sparse-norm regularization to improve imaging of thin, sharply bounded structures. Applied to AEM data from the Kaweah Subbasin and calibrated with a small number of high-quality wells, the targeted inversion produces a much thinner and better-resolved Corcoran Clay compared to conventional L2-norm inversion. The resulting thickness and depth estimates align with the existing groundwater model and outperform interpretations based solely on well data, especially where the clay becomes discontinuous. These results demonstrate how targeted inversion can extract more accurate and decision-relevant information from large AEM datasets, and highlight opportunities for future integration of prior knowledge and AI-driven techniques in AEM inversion workflows.