Cover-thickness Mapping

Approximately 80 per cent of the Australian landmass is blanketed post-mineralisation sedimentary cover and regolith. The cover presents a challenge to successful exploration. The thickness, nature and variability of these cover materials are not well known, particularly in less explored 'green field' regions across Australia.

To facilitate more effective exploration in these buried landscapes Geoscience Australia is developing databases, methodologies and predictive models to better understand the nature of the cover. We aim to generate 3-dimensional surfaces of the depths to major chronostratigraphic interfaces including the bases of Cenozoic, Mesozoic, Palaeozoic and Proterozoic packages.

Drilling provides the most reliable source of depth information. Geophysical depth estimates derived from, for example, depth to magnetic basement techniques and seismic reflection profiles also provide important constraints on cover depth. These point depth measurements are stored in a new national database, the Estimates of Geological and Geophysical Surfaces or EGGS. Depth information centrally stored in EGGS will be used to underpin the generation of chronostratigraphic depth surfaces using point interpolation methods such as kriging or machine learning that establishes predictive relationships between the depth estimates and other geological or geophysical information (e.g. distance from outcrop, gravity).


  • Information from hundreds of boreholes from stratigraphic, petroleum and exploration company drill holes has been interpreted within the Tennant Creek — Mt Isa focus area and surrounding regions.  Chronostratigraphic unit thicknesses from these drill holes have been recorded in the EGGS database.
  • Thousands of depth to magnetic top estimates have been calculated and are being attributed with the inferred stratigraphic interface they reflect.


  • Chronostratigraphic unit thicknesses from boreholes and magnetic datasets will be accessible through the EGGS database in mid-2018.
  • Chronostratigraphic cover thickness models over the Tennant Creek — Mt Isa focus area will be available towards the end of 2018. These cover predictions with also show the uncertainties of the predictions.
  • The machine learning UncoverML codes used to generate cover-thickness models are available through the Geoscience Australia GitHub repository. The use of these codes will be explained and demonstrated to stakeholders at appropriate conferences/workshops.


The machine learning code used to generate cover depth predictions has been developed in collaboration with Data61 at CSIRO.

The key external collaborators of this project includes the Northern Territory Geological Survey (NTGS) and the Geological Survey of Queensland (GSQ). This specifically involves sharing drill hole information and stored exploration company reports.