Ross S. Brodie

Using airborne EM and borehole NMR data to map the transmissivity of a shallow semi-confined aquifer, western NSW.

The Broken Hill Managed Aquifer Recharge (BHMAR) project aimed to define key groundwater resources and aquifer storage options in the lower Darling River floodplain of western NSW. The project was multi-disciplinary and utilised airborne electromagnetics (AEM), borehole nuclear magnetic resonance (NMR) and LiDAR DEM data and lithological, hydrostratigraphic and hydrochemical information to develop a suite of hydrogeological and groundwater property maps and products. This abstract discusses the methods and results of estimating the transmissivity of the semi-confined target aquifer. Hydrostratigraphy and hydraulic texture classes were mapped by interpreting the AEM data in conjunction with borehole geophysics and lithological information. Aquifer transmissivity was statistically derived by combining borehole NMR hydraulic conductivity estimates with the mapped 3D distribution of texture classes and hydrostratigraphic units. Using a statistical and GIS approach, the derived aquifer thicknesses in the key areas ranged from 20 - 40 m and the lower and upper transmissivity bounds ranged from 1 to 10 m2/d, and 10 m2/d to 1000 m2/d, respectively.

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

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.