Optimizing Airborne Electromagnetic (AEM) Inversions for Hydrogeological Investigations using a Transdisciplinary Approach

Abstract

High-resolution hydrogeophysical data are increasingly acquired as part of investigations to underpin groundwater mapping. However, optimization of AEM data requires careful consideration of AEM system suitability, calibration, validation and inversion methods. In modern laterally-correlated inversions of AEM data, the usefulness of the resulting inversion models depends critically on an optimal choice of the vertical and horizontal regularization of the inversion. Set the constraints too tight, and the resulting models will become overly smooth and potential resolution is lost. Set the constraints too loose, and spurious model details will appear that have no bearing on the hydrogeology. There are several approaches to an automatic choice of the regularization level in AEM inversion based predominantly on obtaining a certain pre-defined data misfit with the smoothest possible model. However, we advocate a pragmatic approach to optimizing the constraints by an iterative procedure involving all available geological, hydrogeological, geochemical, hydraulic and morphological data and understanding. In this approach, in a process of both confirming and negating established interpretations and underlying assumptions, the inversion results are judged by their ability to support a coherent conceptual model based on all available information. This approach has been essential to the identification and assessment of MAR and groundwater extraction options in the Broken Hill Managed Aquifer Recharge project.