<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).

<div>The groundwater and surface water systems associated with the Upper Darling River Floodplain (UDF) in arid northwest New South Wales form part of the Murray-Darling Basin drainage system, which hosts 40% of Australia’s agricultural production. Increasing water use demands and a changing regional climate are affecting hydrological systems, and consequently impacting the quality and quantity of water availability to communities, industries and the environment.</div><div>As part of the Australian Government’s Exploring for the Future program, the UDF project is working in collaboration with State partners to collect and integrate new data and information with existing hydrogeological knowledge. The goal is to provide analyses and products that assist water managers to increase water security in the region, with a focus on groundwater resources. </div><div>As part of this project we are assessing the occurrence of, and geological controls on, potable water resources within the Darling Alluvium (DA), which comprises unconsolidated sediments (<140 m thick) associated with the modern and paleo-Darling River. The DA’s relationship to the underlying Eromanga, Surat (Great Artesian Basin) and Murray basins is also important, particularly in the context of potential groundwater sources or sinks, and connection between low and high quality groundwater resources. At least one major fault system is known to influence groundwater flow paths and control groundwater-surface water interaction.</div><div>Data collection across the project area has commenced, with an airborne electromagnetic (AEM) survey already complete, and new geophysical, hydrochemical and hydrodynamic data being acquired. Preliminary interpretation of the new AEM data in conjunction with existing geological and hydrogeological information has already revealed the major paths and geometries of the paleo-Darling River, given important insights into fault controls on groundwater flow paths, and shown variation in the thickness, distribution and character of the DA, which has direct implications for groundwater–surface water connectivity.</div><div><br></div>

<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 groundwater and surface water systems associated with the Upper Darling River Floodplain (UDF) in arid northwest New South Wales form part of the Murray-Darling Basin drainage system, which hosts 40% of Australia’s agricultural production. Increasing water use demands and a changing regional climate are affecting hydrological systems, and consequently impacting the quality and quantity of water availability to communities, industries and the environment.</div><div>As part of the Australian Government’s Exploring for the Future program, the UDF project is working in collaboration with State partners to collect and integrate new data and information with existing hydrogeological knowledge. The goal is to provide analyses and products that assist water managers to increase water security in the region, with a focus on groundwater resources. </div><div>As part of this project we are assessing the occurrence of, and geological controls on, potable water resources within the Darling Alluvium (DA), which comprises unconsolidated sediments (<140 m thick) associated with the modern and paleo-Darling River. The DA’s relationship to the underlying Eromanga, Surat (Great Artesian Basin) and Murray basins is also important, particularly in the context of potential groundwater sources or sinks, and connection between low and high quality groundwater resources. At least one major fault system is known to influence groundwater flow paths and control groundwater-surface water interaction.</div><div>Data collection across the project area has commenced, with an airborne electromagnetic (AEM) survey already complete, and new geophysical, hydrochemical and hydrodynamic data being acquired. Preliminary interpretation of the new AEM data in conjunction with existing geological and hydrogeological information has already revealed the major paths and geometries of the paleo-Darling River, given important insights into potential fault controls on groundwater flow paths, and shown variation in the thickness, distribution and character of the DA, which has direct implications for groundwater–surface water connectivity.</div><div><br></div>

<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>

<div>This package contains Airborne Electromagnetic (AEM) data from the regional survey flown over the Upper Darling Floodplain in New South Wales (NSW), Australia between March-July 2022. Approximately 25,000 line km of transient EM and magnetic data were acquired. Geoscience Australia (GA) commissioned the survey in collaboration with the New South Wales Department of Planning and Environment (NSW DPE) as part of the Australian Government’s Exploring for the Future (EFTF) program (https://www.ga.gov.au/eftf). The NSW DPE were funding contributors to the AEM data collection. GA managed all aspects of the acquisition, quality control and processing of the AEM data.</div>

<div>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 GA Record is a technical report detailing the science undertaken as part of the Musgrave Palaeovalley groundwater project. The project aimed to improve understanding of the region's palaeovalley architecture, groundwater quality, and overall hydrogeology to support responsible water resource management. The most significant work undertaken included three-dimensional modelling of palaeovalley architecture, groundwater characterisation using hydrochemistry, groundwater model conceptualisation and a detailed review of local groundwater around remote communities in the region. This work will underpin responsible groundwater management into the future.</div>

<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)

Long-range, active-source airborne electromagnetic (AEM) systems for near-surface imaging fall into two categories: helicopter borne or fixed-wing aircraft borne. A multitude of factors such as flying height, transmitter loop area and current, source waveforms, aerodynamic stability and data stacking times contribute to the geological resolvability of the subsurface. A comprehensive comparison of the relative merits of each system considering all such factors is difficult, but test flights over known subsurface geology with downhole induction logs are extremely useful for resolution studies. Further, given the non-linear nature of the electromagnetic inverse problem, handling transmitter-receiver geometries in fixed-wing aircraft is especially challenging. As a consequence of this nonlinearity, inspecting the closeness of downhole conductivities to deterministic inversion results is not sufficient for studying resolvability. A more comprehensive picture is provided by examining the width of the depth-wise Bayesian posterior conductivity distributions for each kind of system. For this purpose, probabilistic inversions of data must be carried out -- with acquisition over the same geology, survey noise levels must be measured, and the same prior probabilities on conductivity must be used. With both synthetic models as well as real data from over the Menindee calibration range in New South Wales, Australia, we shed new light on the matter of AEM inverse model resolution. Specifically, we use a novel Bayesian inversion scheme which handles fixed-wing geometry attributes as generic nuisance parameters during Markov chain sampling. Our findings have useful implications in AEM system selection, as well as in the design of better deterministic AEM inversion algorithms. <b>Citation:</b> Anandaroop Ray, Yusen Ley-Cooper, Ross C Brodie, Richard Taylor, Neil Symington, Negin F Moghaddam, An information theoretic Bayesian uncertainty analysis of AEM systems over Menindee Lake, Australia, Geophysical Journal International, Volume 235, Issue 2, November 2023, Pages 1888–1911, <a href="https://doi.org/10.1093/gji/ggad337">https://doi.org/10.1093/gji/ggad337</a>

<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.