Conductivity-depth estimates generated using the 1D Geoscience Australia layered earth inversion algorithm (GA-LEI) have been released to the public domain. The GA-LEI has been shown to provide useful mapping of subsurface conductivity features in the Paterson; for example paleovalleys, unconformities and faults. GA-LEI interpretations have been supported by independent borehole conductivity logs, and lithological drill-hole information. The Geoscience Australia Record 2010/12; Geological and energy implications of the Paterson Province airborne electromagnetic (AEM) survey, Western Australia, summarises the AEM processing, inversion, interpretation and implications for mineral exploration using the 1D GA-LEI. There is an inherent assumption in the GA-LEI algorithm that the earth can be represented by a set of 1D layers, which extend to infinite distance in the horizontal plane. This layered earth assumption has some limitations, and has been demonstrated to create artefacts when applied to heterogeneous 3D geological features. 3D inversion methods can potentially overcome some of the limitations of 1D inversion methods, reducing the artefacts of a 1D earth assumption. 3D inversions require much greater computational resources than 1D methods because they have to solve many large systems of equations. In addition, a large sensitivity matrix is computed, which increases memory requirements, and the process must be repeated for multiple iterations. This computational expense has generally limited the application of 3D inversions to AEM datasets, and restricted its practicality as a general mapping tool. The EMVision® inversion generated by TechnoImaging presents a method of running a 3D inversion, with a runtime comparable to 1D inversion methods. The EMVision® algorithm uses a moving footprint to limit the number of data points needed as input to the inversion at any one location. A background conductivity model is chosen to represent the far-field response of the earth, and the data points within the AEM footprint are treated as anomalies with respect to the background. In 2010, Geoscience Australia decided that a comparison of the GA-LEI with the EMVision® inversion would be useful both for geological interpretation and for assessing the benefits of 3D inversion of AEM. A subset of the regional Paterson AEM dataset around the Kintyre uranium deposit was provided to TechnoImaging to create a 3D inversion using EMVision® software. The data subset was a combination of GA data and data owned by Cameco Corporation and the cost of inversion by TechnoImaging was shared by both parties. Under the terms of the agreement between Cameco Corporation and Geoscience Australia there was a moratorium on the data release until 2012.

No abstract available

Sander Geophysics Limited (SGL) conducted a fixed-wing high-resolution gravimetric survey between 23 February and 14 March 2012 over the Kauring airborne gravity test site, Western Australia, for the Victoria State Department of Primary Industries (DPI) as part of the CarbonNet Project. The survey was flown using SGL's airborne gravity system, AIRGrav (Airborne Inertially Referenced Gravimeter). This data package contains located airborne geophysical data (ASCII columns) and gridded airborne geophysical data in ER Mapper grid format (.ers) and Geosoft grid (.gxf) format, a technical report file (PDF) and a licence agreement and explanatory notes file (PDF). The survey was conducted using SGL's Cessna Grand Caravan 208B, registration C-GSGA. Production flights commenced on February 23, 2012 and were completed on March 14, 2012. A total of 16 flights were performed during the survey to complete the planned 3064 line kilometres. The survey operations were conducted from Perth Jandakot airport (YPJT). <b>Copyright retained by 3rd party. Data available for download via a licence agreement.</b>

These data are one of a set of 13 that captures a consistent horizon and fault interpretation of approximately 35 000 km of regional, mostly deep, seismic reflection data recorded by AGSO along the north and northwestern continental margins of Australia between 1990 and 1994.

PSMA Australia combines spatial data from Australia's governments to create national spatial information datasets that include features such as roads, street addresses, and cadastral and administrative boundaries. Geoscience Australia has entered into an agreement with PSMA Distribution Pty Ltd in June 2013 which provides GA access to key PSMA data products. The conditions of use are stipulated in the End User Agreement (EUA) and simplified form of Terms and Conditions (see below) will be made available soon to GA staff. The EUA has been extended in December 2013 to include the Land Tenure and Postcode Boundaries datasets, effectively providing GA access to the whole suite of PSMA products. These are: -Administrative Boundaries -Features of Interest -CadLite -Geocoded National Address File (G-NAF) -Land Tenure -Postcode Boundaries -Transport & Topography For more details about these products - including content and maintenance cycle - please refer to PSMA website (http://www.psma.com.au/list-products/).

This series of cross sections and data show the suitablility of the Sydney Basin for storage of carbon dioxide.Cartography file number 07-1825-1.

The Yilgarn OZCHEM database subset is comprised of 4886 wholerock analyses derived from AGSO field work and the literature. AGSO's complete OZCHEM database contains approximately 50000 analyses, mainly from Australia but some are also from Papua New Guinea, Antarctica, Solomon Islands and New Zealand. Approximately 32000 analyses of Australian rocks of all ages and some New Zealand Tertiary volcanics are available for sale. The location is stored with each analysis along with geological descriptions, including the host stratigraphic unit and lithology. Most samples have been collected by AGSO field parties.OZCHEM is stored in an ORACLE relational database and is available in Oracle export, comma-delimited relational ASCII, and Microsoft Access formats.

These data are one of a set of 13 that captures a consistent horizon and fault interpretation of approximately 35 000 km of regional, mostly deep, seismic reflection data recorded by AGSO along the north and northwestern continental margins of Australia between 1990 and 1994.

This dataset contains four-class hardness (i.e., hard-1, hard-soft-2, soft-3 and soft-hard-4) prediction data from seabed mapping surveys on the Van Diemen Rise in the eastern Joseph Bonaparte Gulf of the Timor Sea. This dataset was generated based on hard90 seabed hardness classification scheme using random forest methods based on the point data of seabed hardness classification using video images and multibeam data. Refer to Selecting optimal random forest predictive models: a case study on predicting the spatial distribution of seabed hardness for further information on processing techniques applied [1]. [1] Li, J., Tran, M., Siwabessy, J., 2016. Selecting optimal random forest predictive models: a case study on predicting the spatial distribution of seabed hardness PLOS ONE 11(2) e0149089.

No abstract available