The GEOPHYS_SURV database describes geophysical surveys (air, land, and marine), the datasets derived from those surveys, and the methods used for delivery of those datasets. The database includes metadata for all surveys conducted or managed by Geoscience Australia and its predecessor agencies, as well as data and surveys from State and Territory geological survey agencies.

Geoscience Australia first sought feedback on a metadata standard for magnetotelluric (MT) time-series data in 2018 with the publication of a Preview article (Kirkby, 2019) outlining suggestions for metadata fields that should be collected when running an MT survey. This was the first step in standardising the MT formats used by the Australian MT community to ensure a cohesive community approach moving forward. Intrepid Geophysics was subsequently contracted by Geoscience Australia to investigate the current community sentiment around a metadata standard and report on the community’s requirements for a standardised data format. Intrepid Geophysics was chosen as an independent party that had no significant stake in the magnetotellurics discussion. This report is the third made to Geoscience Australia in a series investigating the needs of the Australian magnetotelluric community, with a focus on the definition of the metadata that should be collected along with the raw data of an MT survey. The findings were collated from interviews conducted in the preliminary stage of the project as well as an online questionnaire that was sent to those who had agreed to be contacted. Feedback was constructive, centring on standardisation of parameter naming schemes, adding parameters that were missing and could add value, and misclassification of parameters. Future work should focus on a more widespread community engagement program that involves system manufacturers as well as building the metadata structure around the chosen data format.

Gravity data measures small changes in gravity due to changes in the density of rocks beneath the Earth's surface. The data collected are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. These line dataset from the GA302 Capel and Faust Basins MSS survey were acquired in 2006 for Geoscience Australia. This survey acquired a range of pre-competitive geological and geophysical data that included seismic reflection, gravity, magnetic and swath bathymetry measurements, as well as seafloor dredge samples.

Total magnetic intensity (TMI) data measures variations in the intensity of the Earth's magnetic field caused by the contrasting content of rock-forming minerals in the Earth crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. The data are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. These line dataset from the GA302 Capel and Faust Basins MSS survey were acquired in 2006 for Geoscience Australia. This survey acquired a range of pre-competitive geological and geophysical data that included seismic reflection, gravity, magnetic and swath bathymetry measurements, as well as seafloor dredge samples.

Gravity data measures small changes in gravity due to changes in the density of rocks beneath the Earth's surface. The data collected are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. These line dataset from the GA310 South West Margin 2D MSS survey were acquired for Geoscience Australia in 2008/2009 as part of the Australian Government's Offshore Energy Security Program. This survey acquired a range of pre-competitive geological and geophysical data that included seismic reflection, gravity, magnetic and swath bathymetry measurements, as well as seafloor dredge samples. A total of 26,000 line-kilometres of magnetic and gravity data were acquired during this survey.

Total magnetic intensity (TMI) data measures variations in the intensity of the Earth's magnetic field caused by the contrasting content of rock-forming minerals in the Earth crust. Magnetic anomalies can be either positive (field stronger than normal) or negative (field weaker) depending on the susceptibility of the rock. The data are processed via standard methods to ensure the response recorded is that due only to the rocks in the ground. The results produce datasets that can be interpreted to reveal the geological structure of the sub-surface. The processed data is checked for quality by GA geophysicists to ensure that the final data released by GA are fit-for-purpose. These line dataset from the GA310 South West Margin 2D MSS were acquired for Geoscience Australia in 2008/2009 as part of the Australian Government's Offshore Energy Security Program. This survey acquired a range of pre-competitive geological and geophysical data that included seismic reflection, gravity, magnetic and swath bathymetry measurements, as well as seafloor dredge samples. A total of 26,000 line-kilometres of magnetic and gravity data were acquired during this survey.

The Neoproterozoic–Paleozoic Officer Basin, located in South Australia and Western Australia, remains a frontier basin for energy exploration with significant uncertainty due to a paucity of data. As part of Geoscience Australia’s Exploring for the Future (EFTF) program, the objective of this study is to derive the petrophysical properties and characterise potential reservoirs in the Neoproterozoic–Cambrian sedimentary succession in the Officer Basin through laboratory testing, and well log interpretation using both conventional and neural network methods. Laboratory measurements of forty-one legacy core samples provide the relationships between gas permeability, Klinkenberg corrected permeability, and nano-scale permeability, as well as grain density, effective and total porosity for various rock types. Conventional log interpretation generates the volume fraction of shale, effective and total porosity from gamma ray and lithology logs. Self-organising map (SOM) was used to cluster the well log data to generate petrophysical group/class index and probability profiles for different classes. Neural network technology was employed to approximate porosity and permeability from logs, conventional interpretation results and class index from SOM modelling. The Neoproterozoic-Cambrian successions have the potential to host both conventional and tight hydrocarbon reservoirs. Neoproterozoic successions are demonstrated to host mainly tight reservoirs with the range in average porosity and geometric mean permeability of 4.77%-6.39% and 0.00087-0.01307 mD, respectively, in the different sequences. The range in average porosity and geometric mean permeability of the potential Cambrian conventional reservoirs is 14.54%-26.38% and 0.341-103.68 mD, respectively. The Neoproterozoic shales have favourable sealing capacities. This work updates the knowledge of rock properties to further the evaluation of the resource potential of the Officer Basin. Published in The APPEA Journal 2022 <b>Citation:</b> Wang Liuqi, Bailey Adam H. E., Carr Lidena K., Edwards Dianne S., Khider Kamal, Anderson Jade, Boreham Christopher J., Southby Chris, Dewhurst David N., Esteban Lionel, Munday Stuart, Henson Paul A. (2022) Petrophysical characterisation of the Neoproterozoic and Cambrian successions in the Officer Basin. <i>The APPEA Journal</i><b> 62</b>, 381-399. https://doi.org/10.1071/AJ21076

Barnicarndy 1 is a stratigraphic well drilled in the southern part of the Canning Basin’s Barnicarndy Graben under Geoscience Australia’s Exploring for the Future program in collaboration with the Geological Survey of Western Australia to provide stratigraphic data for this poorly understood tectonic component. The well intersects a thin Cenozoic section, Permian–Carboniferous fluvial clastics and glacial diamictites and a thick pre-Carboniferous succession (855–2585 mRT) unconformably overlying Neoproterozoic metasedimentary rocks. Three informal siliciclastic intervals were defined based on core lithology, well logs, chemical and mineral compositions: the Upper Sandstone (855–1348.1 mRT), Middle Interval (1348.1–2443.4 mRT) and Lower Sandstone (2443.4–2585 mRT). The Middle Interval was further divided into six internal zones. Both conventional methods and artificial neural network technology were applied to well logs to interpret petrophysical and elastic properties, total organic carbon (TOC) content, pyrolysis products from the cracking of organic matter (S2) and mineral compositions. Average sandstone porosity and reservoir permeability are 17.9% and 464.5 mD in the Upper Sandstone and 6.75% and 10 mD in the Lower Sandstone. The Middle Interval claystone has an average porosity and permeability of 4.17% and 0.006 mD, and average TOC content and S2 value of 0.17 wt% and 0.047 mg HC/g rock, with maximum values of 0.66 wt% and 0.46 mg HC/g rock, respectively. Correlations of mineral compositions and petrophysical, geomechanical and organic geochemical properties of the Middle Interval have been conducted and demonstrate that these sediments are organically lean and lie within the oil and gas window. Published in The APPEA Journal 2021 <b>Citation:</b> Wang Liuqi, Edwards Dianne S., Bailey Adam, Carr Lidena K., Boreham Chris J., Grosjean Emmanuelle, Normore Leon, Anderson Jade, Jarrett Amber J. M., MacFarlane Susannah, Southby Chris, Carson Chris, Khider Kamal, Henson Paul, Haines Peter, Walker Mike (2021) Petrophysical and geochemical interpretations of well logs from the pre-Carboniferous succession in Barnicarndy 1, Canning Basin, Western Australia. <i>The APPEA Journal</i><b> 61</b>, 253-270. https://doi.org/10.1071/AJ20038

For the AusAEM Year 1 survey an inertial measurement unit (IMU) was installed for the first time on the TEMPEST receiver bird to measure its orientation and to augment GPS derived positioning of the receiver. This has given us the opportunity to develop better quality control and calibration procedures, which would otherwise not be possible. Theoretical modelling of the primary field on high altitude zero-lines, using the full position/orientation information, revealed discrepancies between observed and modelled data. It alerted us to time-lag parallaxes between EM and bird position/orientation data, some spurious IMU data on many pre-flight zero-lines, and a coordinate system sign convention inconsistency. The modelling also revealed systematic differences that we could attribute to the calibration of the receiver pitch and EM data scaling. We developed an inversion algorithm to solve for a receiver pitch offset and an EM scaling calibration parameter, for each zero-line, which minimised the systematic discrepancies. It eventuated that the calibration parameters fell into five distinct populations explicable by significant equipment changes. This gave us the confidence to use the medians of these populations as parameters to calibrate the data. The work shows the value of the new receiver bird orientation data and the importance of accurate IMU calibration after any modification. It shows the practical utility of quantitative modelling in the quality control workflow. It also demonstrates how modelling and inversion procedure can be used to successfully diagnose calibration issues in fixed-wing AEM data. Presented at the 2019 Australasian Exploration Geoscience Conference

<p>The accompanying data package, was released on 30 April 2020 by the Geological Survey of New South Wales (GSNSW) and Geoscience Australia (GA). <p>The package contains processed data from the “MinEx CRC Cobar Airborne Electromagnetic Survey” that was flown over the Cobar–Lake Cargelligo area of Central West New South Wales . The regional survey was flown at 2.5 and 5 km nominal line spacings and entails approximately 5,900 line kilometres of new geophysical data. The survey was flown in 2019 by New Resolution Geophysics Pty. Ltd. (NRG) using the XCITE® airborne electromagnetic system. NRG also processed the data. <p>The survey also included a further 800 line kilometres of infill flying that was funded by private exploration companies, in certain blocks within the survey area. The data from these infill blocks are not part of this data release due to confidentiality agreements but will be released to the public after a 12 month moratorium. <p>GSNSW commissioned the survey as part of the MinEx Cooperative Research Centre’s (MinEx CRC), the world’s largest mineral exploration collaboration. It brings together industry, government, research organisations and universities to further our understanding of geology, mineral deposits and groundwater resources in areas where rocks aren’t exposed at Earth’s surface. GSNSW is a major participant in the NDI program, committing $16 million to the program over 10 years. In NSW, the program focuses on five areas in the state’s central and far west, where metallic minerals potentially exist under a layer of younger barren geology. These areas are North Cobar, South Cobar, Broken Hill (Mundi), Forbes and Dubbo. <p>GA managed the survey data acquisition and processing contract and the quality control of the survey on behalf of GSNSW. GA also contributed by generating one of the two inversion products included in the data package. <p>The data release package comntains <p>1. A data release package summary PDF document. <p>2. The survey logistics and processing report and XCITE® system specification files <p>3. ESRI shape files for the flight lines and boundary <p>4. KML (Google Earth) files of the flight lines <p>5. Final processed point located line data in ASEG-GDF2 format -final processed dB/dt electromagnetic, magnetic and elevation data -final processed BField electromagnetic, magnetic and elevation data <p>6. Conductivity estimates generated by NRG’s inversion -point located line data output from the inversion in ASEG-GDF2 format -graphical (PDF) multiplot conductivity sections and profiles for each flight line -graphical (JPEG) conductivity sections for each line -georeferenced (PNG) conductivity sections (suitable for pseudo-3D display in a 2D GIS) -GoCAD™ S-Grid 3D objects (suitable for various 3D packages) -Curtain image conductivity sections (suitable 3D display in GA’s EarthSci) -Grids generated from the NRG inversion in ER Mapper® format (layer conductivities, depth slices, elevation slices) -Images generated from the grids above (layer conductivities, depth slices, elevation slices) <p>7. Conductivity estimates generated by Geoscience Australia's inversion -point located line data output from the inversion in ASEG-GDF2 format -graphical (JPEG) conductivity sections for each line -georeferenced (PNG) conductivity sections (suitable for pseudo-3D display in a 2D GIS) -GoCAD™ S-Grid 3D objects (suitable for various 3D packages) -Curtain image conductivity sections (suitable 3D display in GA’s EarthSci) -Grids generated from Geoscience Australia's inversion in ER Mapper® format (layer conductivities, depth slices, elevation slices) -Images generated from the grids above (layer conductivities, depth slices, elevation slices) <p>Directory structure <p>├── report <p>│   ├── line_data <p>│   ├── shapefiles <p>│   ├── kml <p>│   ├── contractor_inversion <p>│   │   ├── line_data <p>│   │   ├── multiplots <p>│   │   ├── sections <p>│   │   ├── georeferenced_sections <p>│   │   ├── gocad_sgrids <p>│   │   ├── earthsci <p>│   │   │   └── MinExCRC_Cobar_AEM_Contractor_Regional <p>│   │   ├── images <p>│   │   │   ├── layers <p>│   │   │   ├── depth_slice <p>│   │   │   └── elevation_slice <p>│   │   └── grids <p>│   │   ├── layers <p>│   │   ├── depth_slice <p>│   │   └── elevation_slice <p>│   └── ga_inversion <p>│   ├── line_data <p>│   ├── sections <p>│   ├── georeferenced_sections <p>│   ├── gocad_sgrids <p>│   ├── earthsci <p>│   │   └── MinExCRC_Cobar_AEM_GA-Inversion_Regional <p>│   ├── images <p>│   │   ├── layers <p>│   │   ├── depth_slice <p>│   │   └── elevation_slice <p>│   └── grids <p>│   ├── layers <p>│   ├── depth_slice <p>│   └── elevation_slice