3-D Inversion of Airborne Electromagnetic Data Based on Adaptive Octree Meshes

Abstract

Airborne electromagnetic (AEM) inversion is a key approach for reconstructing subsurface resistivity structures in geologically complex regions. Owing to the complexity of subsurface media, the conventional 1-D and 2-D inversion approaches are insufficient for resolving these geological structures. The development of fully 3-D inversion methodologies is necessary. However, in large-scale 3-D AEM inversions, the structured meshes impose severe limitations on local refinement, constraining mesh design and parameterization. Here, we present a 3-D inversion framework for AEM data based on an adaptive octree discretization. The forward and adjoint modeling are performed using a vector finite-element (FE) formulation on octree meshes, enabling flexible local meshes guided by the system footprint and thereby reducing degrees of freedom while improving computational efficiency. An adaptive mesh-refinement strategy is further incorporated to dynamically balance inversion accuracy and computational cost. Synthetic experiments demonstrate that the adaptive octree approach outperforms the conventional uniform-mesh strategies in recovering anomaly geometry, delineating structural boundaries and reducing computational expenses. Application to an AEM field dataset acquired from the Lofoten–Vesterlen region of Norway successfully resolves multiple conductive structures that are consistent with prior geological knowledge, confirming the robustness and suitability of the method for large-scale surveys. These results highlight the potential of octree-based adaptive inversion to substantially enhance both accuracy and efficiency in 3-D AEM imaging.