As part of the $225 million Exploring for the Future programme, Geoscience Australia have undertaken an investigation into the resource potential of the Officer-Musgrave-Birrindudu region. Part of this project focusses on characterising palaeovalley groundwater resources within the West Musgrave region of Australia. This record presents a three-dimensional palaeovalley model and describes the method used in its generation. Understanding the 3D architecture of palaeovalleys is an important component of conceptualising the shallow groundwater system. In this region groundwater is the only significant water resource, and is critical for supporting local communities, industries and the environment. The data products released alongside this record are a base of gridded Cenozoic surface, a grid of the thickness of the Cenozoic and polygons defining the spatial extent of palaeovalleys. The study area encompasses the upper reaches of several large palaeovalleys. These valleys incised mostly crystalline rocks of the Musgrave Province and sedimentary rocks of the adjoining basin during the late Cretaceous. Subsequently, valleys were filled by Cenozoic-aged sediments, which now form the aquifers and aquitards of the modern-day groundwater system. Palaeovalley architecture has been shaped by a complex interplay of climatic, tectonic, and geological factors over geological time. In some cases, tectonic deformation has caused tilting or disruption of palaeovalleys with implications for groundwater flow. We modelled the base of Cenozoic surface across the project area and used this geological surface to identify palaeovalleys. The modelling process used airborne electromagnetic conductivity models, borehole data and geological outcrop as model inputs. Using these data, we interpreted the base of Cenozoic along AEM flightlines, at borehole locations and at the surface where Pre-Cenozoic geology was cropping out. These data were gridded to generate the base of Cenozoic surface. This surface was then used as the basis for interpreting palaeovalley extents. The resulting model is adequate for its purpose of better understanding the groundwater system. However, the model has considerable uncertainty due to uncertainty in the model inputs and data sparsity. The model performed much better within the centre of the project area within the Musgrave Province compared to the adjoining basins.

<div>As part of the Exploring for the Future (EFTF) programme, the groundwater team undertook an in-depth investigation into characterising surface water -- groundwater interaction in the Cooper Creek floodplain using airborne electromagnetics (AEM). This work is to be released as part of the Lake Eyre Basin detailed inventory and as an EFTF extended abstract. As part of Geoscience Australia's commitment to transparent science, the scientific workflows that underpinned a large component of this investigation are to be released as a jupyter notebook. This notebook contains python code, figures and explanatory text that the reader can use to understand how the AEM data were processed, visualised, integrated with other data and interpreted.</div>

The product consists of 8,800 line kilometres of time‐domain airborne electromagnetic (AEM) geophysical data acquired over the far north part of South Australia known as the Musgrave Province. This product release includes: a) the measured AEM point located data, b) electrical conductivity depth images derived from the dataset, and c) the acquisition and processing report. The data were acquired using the airborne SkyTEM312 Dual Moment 275Hz/25Hz electromagnetic and magnetic system, which covered a survey area of ~14,000 km2, which includes the standard 1:250 000 map sheets of SG52-12 (Woodroffe), SG52-16 (Lindsay), SG53-09 (Alberga) and SG53-13 (Everard). The survey lines where oriented N-S and flown at 2km, 500m and 250m line spacing. A locality diagram for the survey is shown in Figure 1. This survey was funded by the Government of South Australia, as part of the Plan for Accelerating Exploration (PACE) Copper Initiative, through the Department of the Premier and Cabinet, (DPC) and the Goyder Institute of Water Research. Geoscience Australia managed the survey as part of a National Collaborative Framework project agreement with SA. The principal objective of this project was to capture a baseline geoscientific dataset to provide further information on the geological context and setting of the area for mineral systems as well as potential for groundwater resources, of the central part of the South Australian Musgrave Province. Geoscience Australia contracted SkyTEM (Australia) Pty. Ltd. to acquire SkyTEM312 electromagnetic data, between September and October 2016. The data were processed and inverted by SkyTEM using the AarhusInv inversion program (Auken et al., 2015) and the Aarhus Workbench Laterally Constrained Inversion (LCI) algorithm (Auken et al. 2005; Auken et al. 2002). The LCI code was run in multi-layer, smooth-model mode. In this mode the layer thicknesses are kept fixed and the data are inverted only for the resistivity of each layer. For this survey a 30 layer model was used. The thickness of the topmost layer was set to 2 m and the depth to the top of the bottommost (half-space) layer was set to 600 m. The layer thicknesses increase logarithmically with depth. The thicknesses and depths to the top of each layer are given in Table 1. The regional AEM survey data can be used to inform the distribution of cover sequences, and at a reconnaissance scale, trends in regolith thickness and variability, variations in bedrock conductivity, and conductivity values of key bedrock (lithology related) conductive units under cover. The data will also assist in assessing groundwater resource potential and the extent of palaeovalley systems known to exist in the Musgrave Province. A considerable area of the survey data has a small amplitude response due to resistive ground. It very soon becomes evident that lack of signal translates to erratic non-monotonic decays, quite opposite to the smooth transitional exponential decays that occur in conductive ground. Some sections of the data have been flown over what appears to be chargeable ground, hence contain what potentially can be identified as an Induced Polarization effect (airborne IP—AIP). For decades these decay sign changes, which characterize AIP, have not been accounted for in conventional AEM data processing and modelling (Viezzoli et al., 2017). Instead they have mostly been regarded as noise, calibration or levelling issues and are dealt with by smoothing, culling or applying DC shifts to the data. Not accounting for these effects is notable on the contractor’s conductivity-depth sections, where data can’t be modelled to fit the data hence large areas of blank-space have been used to substitute the conductivity structure. The selection of the survey area was undertaken through a consultative process involving the CSIRO, GOYDER Institute, Geological Survey of South Australia and the exploration companies currently active in the region (including industry survey partner PepinNini Minerals Ltd). The data will be available from Geoscience Australia’s web site free of charge. It will also be available through the South Australian Government’s SARIG website at https://map.sarig.sa.gov.au. The data will feed into the precompetitive exploration workflow developed and executed by the Geological Survey of South Australia (GSSA) and inform a new suite of value-added products directed at the exploration community.

These conductivity grids were generated by gridding the top 22 layers from the airborne electromagnetics (AEM) conductivity models from the Western Resource Corridor AusAEM survey (https://dx.doi.org/10.26186/147688), the Earaheedy and Desert Strip AusAEM survey (https://pid.geoscience.gov.au/dataset/ga/145265) and several industry surveys (https://dx.doi.org/10.26186/146278) from the West Musgraves. The grids resolve important subsurface features for assessing the groudnwater system including lithologial boundaires, palaeovalleys and hydrostatigraphy.

<div>Defining and characterising groundwater aquifers usually depends on the availability of data necessary to represent its spatial extent and hydrogeological properties, such as lithological information and aquifer pump test data.&nbsp;In regions where such data is of limited availability and/or variable quality, the characterisation of aquifers for the purposes of water resource assessment and management can be problematic.&nbsp;The Upper Darling River Floodplain region of western New South Wales, Australia, is an area where communities, natural ecosystems and cultural values are dependent on both surface and groundwater resources.&nbsp;Owing to a relative paucity of detailed geological and hydrogeological data across the region we apply two non-invasive geophysical techniques—airborne electromagnetics and surface magnetic resonance—to assist in mapping and characterising the regional alluvial aquifer system.&nbsp;The combination of these techniques in conjunction with limited groundwater quality data helps define an approximate extent for the low salinity alluvial aquifer in a key part of the Darling River valley system and provides insights into the relative water content and its variation within the aquifer materials.&nbsp;This work demonstrates the utility of these key geophysical data in developing a preliminary understanding of aquifer geometry and heterogeneity, thereby helping to prioritise targets for follow-up hydrogeological investigation. Presented at the 2024 Australian Society of Exploration Geophysicists (ASEG) Discover Symposium

<div>This report presents key results from the Upper Darling River Floodplain groundwater study conducted as part of the Exploring for the Future (EFTF) program in north-western New South Wales. The Australian Government funded EFTF program aimed to improve understanding of potential mineral, energy, and groundwater resources in priority areas for each resource.</div><div><br></div><div>The Upper Darling River Floodplain study area is located in semi-arid zone northwest New South Wales is characterised by communities facing critical water shortages and water quality issues, along with ecosystem degradation. As such, there is an imperative to improve our understanding of groundwater systems including the processes of inter-aquifer and groundwater-surface water connectivity. The key interest is in the fresh and saline groundwater systems within alluvium deposited by the Darling River (the Darling alluvium - DA) which comprises sediment sequences from 30 m to 140 m thick beneath the present-day floodplain.</div><div><br></div><div>The study acquired airborne, surface and borehole geophysical data plus hydrochemical data, and compiled geological, hydrometric, and remote sensing datasets. The integration of airborne electromagnetic (AEM) data with supporting datasets including surface and borehole magnetic resonance, borehole induction conductivity and gamma, and hydrochemistry data has allowed unprecedented, high resolution delineation of interpreted low salinity groundwater resources within the alluvium and highly saline aquifers which pose salination risk to both the river and fresher groundwater. Improved delineation of the palaeovalley architecture using AEM, seismic, and borehole datasets has permitted interpretation of the bedrock topography forming the base of the palaeovalley, and which has influenced sediment deposition and the present-day groundwater system pathways and gradients.</div><div><br></div><div>The integrated assessment demonstrates that the alluvial groundwater systems within the study area can be sub-divided on the basis of groundwater system characteristics relevant to water resource availability and management. Broadly, the northern part of the study area has low permeability stratigraphy underlying the river and a generally upward groundwater gradient resulting in limited zone of freshwater ingress into the alluvium around the river. A bedrock high south of Bourke partially restricts groundwater flow and forces saline groundwater from deeper in the alluvium to the surface in the vicinity of the Upper Darling salt interception scheme. From approximately Tilpa to Wilcannia, sufficiently permeable stratigraphy in hydraulic connection with the river and a negligible upward groundwater gradient allows recharge from the river, creating significant freshwater zones around the river within the alluvium.</div><div><br></div><div>Hydrometric and hydrochemical tracer data demonstrate that the alluvial groundwater systems are highly coupled with the rivers. Results support the conceptual understanding that bank-exchange processes and overbank floods associated with higher river flows are the primary recharge mechanism for the lower salinity groundwater within the alluvium. When river levels drop, tracers indicative of groundwater discharge confirm that groundwater contributes significant baseflow to the river. Analysis of groundwater levels and surface water discharge indicates that the previously identified declining trends in river discharge are likely to produce the significant decline in groundwater pressure observed across the unconfined aquifer within the alluvium. Improved quantification and prediction of groundwater-surface water connectivity, water level and flux is considered a high priority for both the Darling River and the wider Murray–Darling Basin. This information will assist in understanding and managing water resource availability in these highly connected systems, and enhance knowledge regarding cultural values and groundwater dependent ecosystems (GDEs).</div><div><br></div><div>This study identifies several aquifers containing groundwater of potentially suitable quality for a range of applications in the south of the study area between Wilcannia and Tilpa and assessed the geological and hydrological processes controlling their distribution and occurrence. Potential risks associated with the use of this groundwater, such as unsustainable extraction, impacts on GDEs, and saline intrusion into aquifers or the river, are outside the scope of this work and have not been quantified.</div>

<p>Airborne electromagnetic (AEM) data can be acquired cost-effectively, safely and efficiently over large swathes of land. Inversion of these data for subsurface electrical conductivity provides a regional geological framework for water resources management and minerals exploration down to depths of ~200 m, depending on the geology. However, for legacy reasons, it is not uncommon for multiple deterministic inversion models to exist, with differing details in the subsurface conductivity structure. This multiplicity presents a non-trivial problem for interpreters who wish to make geological sense of these models. In this article, we outline a Bayesian approach, in which various spatial locations were inverted in a probabilistic manner. The resulting probability of conductivity with depth was examined in conjunction with multiple existing deterministic inversion results. The deterministic inversion result that most closely followed the high-credibility regions of the Bayesian posterior probability was then selected for interpretation. Examining credibility with depth also allowed interpreters to examine the ability of the AEM data to resolve the subsurface conductivity structure and base geological interpretation on this knowledge of uncertainty. <p> <b>Citation:</b> Ray, A., Symington, N., Ley-Cooper, Y. and Brodie, R.C., 2020. A quantitative Bayesian approach for selecting a deterministic inversion model. In: Czarnota, K., Roach, I., Abbott, S., Haynes, M., Kositcin, N., Ray, A. and Slatter, E. (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.

<div>Much of Australia has been surveyed with low-flying airborne electromagnetic (AEM) instrumentation under Geoscience Australia’s AusAEM program. Acquired AEM data allow for imaging the earth's buried geology down to depths of 300-500 m. Such imaging is crucial for managing Australia’s subsurface minerals, energy and groundwater resources, by allowing geoscientists to build a 3D framework of the shallow geological architecture. However, individual AEM lines can be up to 500 km long, data are acquired every 10-12 m, and conventional electromagnetic conductivity imaging methods based on optimisation are unable to accurately characterise the subsurface imaging resolution. Bayesian probabilistic methods can do so, but at significant computational cost if naively used. Efficient Markov chain sampling strategies with parameter dimension reduction, which leverage the high-performance distributed computing capabilities inherent in the Julia language, have now made large scale Bayesian AEM imaging possible. In this work we show the results of imaging using the Julia-based, open-source, High Quality Geophysical Analysis (HiQGA) package, on continent-wide data using Bayesian probabilistic methods. We are unaware of any similar analysis at this scale, routinely using 41,600 cpu-cores for up to three hours in semi-embarrassingly parallel fashion on the National Computational Infrastructure’s Gadi cluster at the Australian National University. Consequently, deeper geology can be mapped, and subsurface 3D geology can be rapidly demarcated using posterior percentiles of conductivity, when contrasted with deterministic methods. Compared to the cost of AEM acquisition, extraction of subsurface information with computation at scale greatly increases the economic and social return on public AEM data acquisition. Abstract presented at the 2024 Supercomputing Asia Conference, Sydney NSW (SAC2024)

<div> A key issue for explorers in Australia is the abundant sedimentary and regolith cover obscuring access to underlying potentially prospective rocks. &nbsp;Multilayered chronostratigraphic interpretation of regional broad line-spaced (~20&nbsp;km) airborne electromagnetic (AEM) conductivity sections have led to breakthroughs in Australia’s near-surface geoscience. &nbsp;A dedicated/systematic workflow has been developed to characterise the thickness of cover and the depth to basement rocks, by delineating contact geometries, and by capturing stratigraphic units, their ages and relationships. &nbsp;Results provide a fundamental geological framework, currently covering 27% of the Australian continent, or approximately 2,085,000&nbsp;km2. &nbsp;Delivery as precompetitive data in various non-proprietary formats and on various platforms ensures that these interpretations represent an enduring and meaningful contribution to academia, government and industry.&nbsp;The outputs support resource exploration, hazard mapping, environmental management, and uncertainty attribution.&nbsp;This work encourages exploration investment, can reduce exploration risks and costs, helps expand search area whilst aiding target identification, and allows users to make well-informed decisions. Presented herein are some key findings from interpretations in potentially prospective, yet in some cases, underexplored regions from around Australia.&nbsp;</div> This abstract was submitted & presented to the 8th International Airborne Electromagnetics Workshop (AEM2023) (https://www.aseg.org.au/news/aem-2023)

<div> The High Quality Geophysical Analysis (HiQGA) package is a framework for geophysical forward modelling, Bayesian inference, and deterministic imaging. A primary focus of the code is production inversion of airborne electromagnetic (AEM) data from a variety of acquisition systems. Adding custom AEM systems is simple using a modern computational idea known as multiple dispatch. For probabilistic spatial inference from geophysical data, only a misfit function needs to be supplied to the inference engine. For deterministic inversion, a linearisation of the forward operator (i.e., Jacobian) is also required. For fixed wing geometry nuisances, probabilistic inversion is carried out using Hierarchical Bayesian inference, and deterministic inversion for these nuisances is done using BFGS optimisation. The code is natively parallel, and inversions from a full day of production AEM acquisition can be inverted on thousands of CPUs within a few hours. This allows for quick assessment of the quality of the acquisition, and provides geological interpreters preliminary subsurface images together with associated uncertainties. These images are then used to create subsurface models for a range of applications from natural resource exploration to its management and conservation.</div><div> </div> This abstract was submitted to/presented at the 8th International Airborne Electromagnetics Workshop (AEM 2023) (https://www.aseg.org.au/news/aem-2023).