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The AusAEM airborne electromagnetic (AEM) survey is one of the main components of the Exploring for the Future program. This Australian Government initiative is aimed at enhancing the geoscientific information available, to support resource exploration and to showcase Australia as a destination for investment opportunities. Regional geophysical mapping programs are the basis for informed mineral exploration and have enabled the building of a continental-scale inventory of Australia's potential resource endowment. They also provide elements of the scientific backing for decision-making and answering a range of different geoscientific questions. The latest of these airborne initiatives AusAEM is composed of a series of wide line-spaced studies targeting acquisition of data for regional mapping in area of new frontiers; it is gathering data and unveiling information on extents never previously attempted by AEM surveys. [ABSTRACT FROM AUTHOR]

We have applied a Bayesian inference algorithm and released open-source code for the 1D inversion of audio-frequency magnetotelluric data. The algorithm uses a trans-dimensional Markov chain Monte Carlo technique to solve for a probabilistic resistivity-depth model. The inversion employs multiple Markov chains to generate an ensemble of millions of resistivity models that adequately fit the data given the assigned noise levels. The trans-dimensional aspect of the inversion means that the number of layers in the resistivity model is solved for rather than being predetermined. The inversion scheme favours a parsimonious solution and the acceptance criterion ratio is theoretically derived such that the Markov chain will eventually converge to an ensemble that is a good approximation of the posterior probability density (PPD). Once the ensemble of models is generated, its statistics are analysed to assess the PPD and to quantify model uncertainties. This approach gives a thorough exploration of model space and a more robust estimation of uncertainty than deterministic methods allow. We demonstrate the application of the method to cover thickness estimation for a number of regional drilling programs. Comparison with borehole results demonstrates that the method is capable of identifying major stratigraphic units with resistivity contrasts. Our results have assisted with drill site targeting and have helped to reduce the uncertainty and risk associated with intersecting targeted stratigraphic units in covered terrains. Interpretation of the audio-frequency magnetotelluric data has improved our understanding of the distribution and geometries of sedimentary basins. From an exploration perspective, mapping sedimentary basins and covered near-surface geological features supports the effective search for mineral deposits in greenfield areas. • Bayesian inference algorithm via trans-dimensional Markov chain Monte Carlo technique. • Probabilistic inversion of audio magnetotelluric data to characterise cover. • Cover thickness estimation helps drill site targeting by reducing uncertainty. • Regional drilling programs provide ground-truth data to validate the models. • Mapping sedimentary basins promotes mineral exploration in covered terrains. [ABSTRACT FROM AUTHOR]