Kokpiang Tan

Using AEM and GMR Methods for Non-Invasive, Rapid Reconnaissance Mapping and Characterisation of Groundwater Systems in the Kimberley Region, Northern Australia

The East Kimberley Region of north-western Australia has been identified as a priority for potential agricultural development. Within this region, the Ord Bonaparte Plain is remote, with limited access in an area of great cultural and environmental sensitivity. Initially, spatio-temporal mapping using remote sensing (and potential field) data, combined with data on the deeper basin geology was used to plan an airborne electromagnetics (AEM) survey. The relatively resistive nature of the basin sediments has enabled the AEM to map the hydrostratigraphy to depths of 300-500m, except in the coastal zone affected by seawater intrusion. Two overlying aquifers, separated by a faulted, ‘leaky’ aquitard, have been identified. The AEM and remote sensing data were subsequently used to plan a ground magnetic resonance (GMR) survey. The latter has enabled a water table map to be constructed in an area with almost no drilling, while also enabling key aquifer properties to be determined. The target aquifer has a high free water content and high transmissivity. The GMR results have been validated by drilling, borehole Nuclear Magnetic Resonance (NMR), and induction logging. Integration of AEM, GMR and temporal (Landsat) remote sensing data has enabled rapid mapping and characterisation of the groundwater system in a data-poor, culturally and environmentally sensitive area. These data have also revealed complex faulting within and bounding the aquifer system, delineated the sea-water intrusion interface, and mapped groundwater dependent ecosystems. These data have been used to target drilling and pump testing that will inform groundwater modelling, water allocations and development decisions.

An Integrated Hydrogeophysical Approach to Exploring for Groundwater Resources in Southern Northern Territory

In Australia’s semi-arid and arid interior, groundwater resources provide water supply security for agriculture and community consumptive use and are critical for underpinning economic development. . The Southern Stuart Corridor Project in central Australia, is an inter-disciplinary study which aims to better characterise regional groundwater systems and identify the location, quantity and quality of new groundwater resources. The main aims of the project are(1) to de-risk investment in development of a potential agricultural precinct in the Western Davenport Basin, and expansion of horticulture in Ti-Tree Basin, (2) to identify future water supplies for Alice Springs and Tennant Creek, and (3) for regional water supplies for mineral resource development. The project is funded by Geoscience Australia (GA) as part of the Exploring for the Future (EFTF) Programme. The project integrates airborne electromagnetic (AEM), ground geophysics (ground magnetic resonance (GMR) and borehole geophysics (Induction, gamma and nuclear Magnetic Resonance (NMR)) with drilling and pump testing; hydrochemistry and geochronology; and geomorphic, geological, hydrogeological and structural mapping and modelling. Advancements in temporal remote sensing technologies for surface hydrology, vegetation and landscape mapping are also used to facilitate the identification of recharge and discharge zones and groundwater-dependent vegetation. This paper reports on initial AEM inversion results for the Alice Springs, Ti-Tree Basin, Western Davenport and Tennant Creek areas and the use of a machine learning approach for rapid geological and hydrogeological interpretation of the AEM data. These machine learning approaches have the potential to significantly reduce interpretation time and facilitate the rapid delivery of project results.

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.