Exploring for the Future (EFTF) is an Australian Government program led by Geoscience Australia, in partnership with state and Northern Territory governments. This first phase of the EFTF program (2016–2020) aimed to assist industry investment in resource exploration in frontier regions of northern Australia by providing precompetitive data and information about energy, mineral and groundwater resource potential. As part of this initiative, this record presents whole-rock inorganic geochemistry data including X-ray fluorescence (XRF) and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) analyses and quantitative X-ray diffraction (qXRD) results for 67 drill core and cuttings samples of sedimentary rocks from Barnicarndy 1 drilled in the Barnicarndy Graben of the Canning Basin. The inorganic geochemistry analyses were undertaken by Geoscience Australia and Bureau Veritas (BV). This work complements other components of the EFTF program, including a comprehensive sampling program of the Barnicarndy 1 deep stratigraphic well, the Kidson Sub-basin seismic survey, and the Kidson Sub-basin petroleum systems model to better understand the geological evolution, basin architecture and petroleum prospectivity of the region.

<div>Environmental DNA (eDNA), elemental and mineralogical analyses of soil have been shown to be specific to their source material, prompting consideration of the use of dust for forensic provenancing. Dust is ubiquitous in the environment and is easily transferred to items belonging to a person of interest, making dust analysis an ideal tool in forensic casework. The advent of Next Generation Sequencing technologies means that metabarcoding of eDNA can uncover microbial, fungal, and even plant genetic fingerprints in dust particles. Combining this with elemental and mineralogical compositions offers multiple, complementary lines of evidence for tracing the origin of an unknown dust sample. This is particularly pertinent when recovering dust from a person of interest to ascertain where they may have travelled. Prior to proposing dust as a forensic trace material, however, the optimum sampling protocols and detection limits need to be established to place parameters around its utility in this context. We tested several approaches to collecting dust from different materials and determined the lowest quantity of dust that could be analysed for eDNA, geochemistry and mineralogy, whilst still yielding results capable of distinguishing between sites. We found that fungal eDNA profiles could be obtained from multiple sample types and that tape lifts were the optimum collection method for discriminating between sites. We successfully recovered both fungal and bacterial eDNA profiles down to 3&nbsp;mg of dust (the lowest tested quantity) and recovered elemental and mineralogical compositions for all tested sample quantities. We show that dust can be reliably recovered from different sample types, using different sampling techniques, and that fungal, bacterial, and elemental and mineralogical profiles, can be generated from small sample quantities, highlighting the utility of dust as a forensic provenance material.</div> <b>Citation:</b> Nicole R. Foster, Belinda Martin, Jurian Hoogewerff, Michael G. Aberle, Patrice de Caritat, Paul Roffey, Robert Edwards, Arif Malik, Priscilla Thwaites, Michelle Waycott, Jennifer Young, The utility of dust for forensic intelligence: Exploring collection methods and detection limits for environmental DNA, elemental and mineralogical analyses of dust samples, <i>Forensic Science International </i>, Volume 344, 2023, 111599, ISSN 0379-0738, https://doi.org/10.1016/j.forsciint.2023.111599. ISSN 0379-0738,

<div>Alluvial sediments have long been used in geochemical surveys as their compositions are assumed to be representative of areas upstream. Overbank and floodplain sediments, in particular, are increasingly used for regional to continental-scale geochemical mapping. However, during downstream transport, sediments from heterogeneous source regions are carried away from their source regions and mixed. Consequently, using alluvial sedimentary geochemical data to generate continuous geochemical maps remains challenging. In this study we demonstrate a technique that numerically unmixes alluvial sediments to make a geochemical map of their upstream catchments. The unmixing approach uses a model that predicts the concentration of elements in downstream sediments, given a map of the drainage network and element concentrations in the source region. To unmix sedimentary chemistry, we seek the upstream geochemical map that, when mixed downstream, best fits geochemical observations downstream. To prevent overfitting we penalise the roughness of the geochemical model. To demonstrate our approach we apply it to alluvial samples gathered as part of the Northern Australia Geochemical Survey. This survey gathered samples collected over a ∼ 500,000 km2 area in northern Australia. We first validate our approach for this sample distribution with synthetic tests, which indicate that we can resolve geochemical variability at scales greater than 0.5 – 1◦ in size. We proceed to invert real geochemical data from the total digestion of fine-grained fraction of alluvial sediments. The resulting geochemical maps for two elements of potential economic interest, Cu and Nd, are evaluated in detail. We find that in both cases, our predicted downstream concentrations match well against a held-out, unseen subset of the data, as well as against data from an independent geochemical survey. By performing principal component analysis on maps generated for all 46 available elements we produce a synthesis map showing the significant geochemical domains of this part of northern Australia. This map shows strong spatial similarities to the underlying lithological map of the area. Finally, we compare the results from our approach to a geochemical map produced by kriging. We find that, unlike the method presented here, kriging generates geochemical maps that are both dampened relative to expected magnitude, as well as being spatially distorted. We argue that the unmixing approach is the most appropriate method for generating geochemical maps from regional-scale alluvial surveys.&nbsp;</div> <b>Citation:</b> Alex G. Lipp, Patrice de Caritat, Gareth G. Roberts, Geochemical mapping by unmixing alluvial sediments: An example from northern Australia, <i>Journal of Geochemical Exploration,</i> Volume 248, <b>2023</b>, 107174, ISSN 0375-6742, https://doi.org/10.1016/j.gexplo.2023.107174. (https://www.sciencedirect.com/science/article/pii/S0375674223000213)

Geoscience Australia’s Exploring for the Future program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia’s geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia’s transition to net zero emissions, strong, sustainable resources and agriculture sectors, and economic opportunities and social benefits for Australia’s regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government. This package contains data generated in the field as part of stratigraphic drilling operations in the Delamerian region of the western New South Wales during 2023 funded through the Exploring for the Future program. A range of geological, geophysical and geochemical data are included, as well as associated borehole information such as core photographs. The data can be viewed and downloaded via the Geoscience Australia Portal - https://portal.ga.gov.au/. The data that is available is from several databases which are associated to this record. <i>These data are published with the permission of the CEO, Geoscience Australia. </i>

<div>With a higher demand for lithium (Li), a better understanding of its concentration and spatial distribution is important to delineate potential anomalous areas. This study uses a digital soil mapping framework to combine data from recent geochemical surveys and environmental covariates to predict and map Li content across the 7.6 million km2 area of Australia. Soil samples were collected by the National Geochemical Survey of Australia at a total of 1315 sites, with both top (0–10 cm depth) and bottom (on average 60–80 cm depth) catchment outlet sediments sampled. We developed 50 bootstrap models using a Cubist regression tree algorithm for both depths. The spatial prediction models were validated on an independent Northern Australia Geochemical Survey dataset, showing a good prediction with an RMSE of 3.82 mg kg-1 for the top depth. The model for the bottom depth has yet to be validated. The variables of importance for the models indicated that the first three Landsat bands and gamma radiometric dose have a strong impact on Li prediction. The bootstrapped models were then used to generate digital soil Li prediction maps for both depths, which could select and delineate areas with anomalously high Li concentrations in the regolith. The map shows high Li concentration around existing mines and other potentially anomalous Li areas. The same mapping principles can potentially be applied to other elements.&nbsp;</div> <b>Citation:</b> Ng, W., Minasny, B., McBratney, A., de Caritat, P., and Wilford, J.: Digital soil mapping of lithium in Australia, <i>Earth Syst. Sci. Data</i>, 15, 2465–2482, https://doi.org/10.5194/essd-15-2465-2023, <b>2023</b>.

<div>The ubiquitous nature of dust, along with localised chemical and biological signatures, makes it an ideal medium for provenance determination in a forensic context. Metabarcoding of dust can yield biological communities unique to the site of interest, similarly, geochemical and mineralogical analyses can uncover elements and minerals within dust than can be matched to a geographic location. Combining these analyses presents multiple lines of evidence as to the origin of collected dust samples. In this work, we investigated whether the time an item spent at a site collecting dust influenced the ability to assign provenance. We then integrated dust metabarcoding of bacterial and fungal communities into a framework amenable to forensic casework, (i.e., using calibrated log-likelihood ratios to predict the origin of dust samples) and assessed whether current soil metabarcoding databases could be utilised to predict dust origin. Furthermore, we tested whether both metabarcoding and geochemical/mineralogical analyses could be conducted on a single sample for situations where sampling is limited. We found both analyses could generate results capable of separating sites from a single swabbed sample and that the duration of time to accumulate dust did not impact site separation. We did find significant variation within sites at different sampling time periods, showing that bacterial and fungal community profiles vary over time and space – but not to the extent that they are non-discriminatory. We successfully modelled soil and dust samples for both bacterial and fungal diversity, developing calibrated log-likelihood ratio plots and used these to predict provenance for dust samples. We found that the temporal variation in community composition influenced our ability to predict dust provenance and recommend reference samples be collected as close to the sampling time as possible. Thus, our framework showed soil metabarcoding databases are capable of being used to predict dust provenance but the temporal variation in metabarcoded communities will need to be addressed to improve provenance estimates.&nbsp;</div> <b>Citation:</b> Nicole R. Foster, Duncan Taylor, Jurian Hoogewerff, Michael G. Aberle, Patrice de Caritat, Paul Roffey, Robert Edwards, Arif Malik, Michelle Waycott and Jennifer M. Young, The secret hidden in dust: Uncovering the potential to use biological and chemical properties of the airborne soil fraction to assign provenance and integrating this into forensic casework, <i>Forensic Science International: Genetics,</i> (2023) doi:https://doi.org/10.1016/j.fsigen.2023.102931

<div>Levelling of geochemical data between surveys is a vital step in using datasets together. This code can apply a number of approaches to eliminate inter-laboratory differences from multi-generational and spatially isolated geochemical surveys. This codes allow the use of a variety of levelling methods: re-analysis, single standards, and multiple standards. The methodology and effectiveness of each of these methods are outlined in Main, P.T. and Champion, D.C., 2022. Levelling of multi-generational and spatially isolated geochemical surveys. Journal of Geochemical Exploration.</div>

<div>A novel method of estimating the silica (SiO2) and loss-on-ignition (LOI) concentrations for the North American Soil Geochemical Landscapes (NASGL) project datasets is proposed. Combining the precision of the geochemical determinations with the completeness of the mineralogical NASGL data, we suggest a ‘reverse normative’ or inversion approach to calculate first the minimum SiO2, water (H2O) and carbon dioxide (CO2) concentrations in weight percent (wt%) in these samples. These can be used in a first step to compute minimum and maximum estimates for SiO2. In a recursive step, a ‘consensus’ SiO2 is then established as the average between the two aforementioned estimates, trimmed as necessary to yield a total composition (major oxides converted from reported Al, Ca, Fe, K, Mg, Mn, Na, P, S, and Ti elemental concentrations + ‘consensus’ SiO2 + reported trace element concentrations converted to wt% + ‘normative’ H2O + ‘normative’ CO2) of no more than 100 wt%. Any remaining compositional gap between 100 wt% and this sum is considered ‘other’ LOI and likely includes H2O and CO2 from the reported ‘amorphous’ phase (of unknown geochemical or mineralogical composition) as well as other volatile components present in soil. We validate the technique against a separate dataset from Australia where geochemical (including all major oxides) and mineralogical data exist on the same samples. The correlation between predicted and observed SiO2 is linear, strong (R2 = 0.91) and homoscedastic. We also compare the estimated NASGL SiO2 concentrations with another publicly available continental-scale survey over the conterminous USA, the ‘Shacklette and Boerngen’ dataset. This comparison shows the new data to be a reasonable representation of SiO2 values measured on the ground over the same study area. We recommend the approach of combining geochemical and mineralogical information to estimate missing SiO2 and LOI by the recursive inversion approach in datasets elsewhere, with the caveat to validate results.</div><div><br></div><div>The major oxide concentrations, including those for the estimated SiO2 and LOI, for the NASGL A and C horizons are available for download, as CSV files. A worked example for five selected NASGL C horizon samples is also available for download, as an XLSX file.</div> <b>Citation:</b> P. de Caritat, E. Grunsky, D.B. Smith; Estimating the silica content and loss-on-ignition in the North American Soil Geochemical Landscapes datasets: a recursive inversion approach. <i>Geochemistry: Exploration, Environment, Analysis</i> 2023; 23 (3): 2023-039 doi: https://doi.org/10.1144/geochem2023-039 This article appears in multiple journals (Lyell Collection & GeoScienceWorld)

<div>Soil is a complex and spatially variable material that has a demonstrated potential to be a useful evidence class in forensic casework and intelligence operations. Here, the capability to spatially constrain searches and prioritise resources by triaging areas as low and high interest is advantageous. Conducted between 2017 and 2021, a forensically relevant topsoil survey (0-5 cm depth; 1 sample per 1 km2) has been carried out over Canberra, Australia, with the aims of documenting the distribution of chemical elements in an urban/suburban environment, and of acting as a testbed for investigating various aspects of forensic soil provenancing. Geochemical data from X-Ray Fluorescence (XRF; for total major oxides) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS; for trace elements) following a total digestion (HF + HNO3) were obtained from the survey’s 685 topsoil samples (plus 138 additional quality control samples and six “Blind” simulated evidentiary samples). Using those “Blind” samples, we document a likelihood ratio approach where for each grid cell the analytical similarity between the grid cell and evidentiary sample is attributed from a measure of overlap between both Cauchy distributions, including appropriate uncertainties. Unlike existing methods that base inclusion/exclusion on an arbitrary threshold (e.g., ± three standard deviations), our approach is free from strict binary or Boolean thresholds, providing an unconstrained gradual transition dictated by the analytical similarity. Using this provenancing model, we present and evaluate a new method for upscaling from a fine (25 m x 25 m) interpolated grid to a more appropriate coarser (500 m x 500 m) grid, in addition to an objective method using Random Match Probabilities for ranking individual variables to be used for provenancing prior to receiving evidentiary material. Our results show this collective procedure generates more consistent and robust provenance maps between two different interpolation algorithms (e.g., inverse distance weighting, and natural neighbour), grid placements (e.g., grid shifts to the north or east) and theoretical users (e.g., different computer systems, or forensic geoscientists).</div> <b>Citation:</b> Michael G. Aberle, Patrice de Caritat, James Robertson, Jurian A. Hoogewerff, A robust interpolation-based method for forensic soil provenancing: A Bayesian likelihood ratio approach,<i> Forensic Science International</i>, Volume 353, 2023, 111883, ISSN 0379-0738. https://doi.org/10.1016/j.forsciint.2023.111883.

<div>The Birrindudu Basin is a region of focus for the second phase of the Exploring for the Future program (EFTF; 2020–2024) as it contains strata of similar age to the prospective McArthur Basin, South Nicholson region and Mount Isa Province, but remains comparatively poorly understood.</div><div><br></div><div>In order to provide an improved understanding of the stratigraphy, basin architecture and resource potential of the Birrindudu Basin and surrounding region, Geoscience Australia, in collaboration with the Northern Territory Geological Survey and CSIRO is acquiring a range of datasets as part of phase two of EFTF. </div><div><br></div><div>This data release presents XRD results from 79 bulk core samples from the Birrindudu and McArthur basins. This report and the associated analyses were conducted by CSIRO, under contract to Geoscience Australia.</div>