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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]

The characterisation of the thickness and geology of cover sequences significantly improves targeting for mineral exploration in buried terrains. Audio-frequency Magnetotelluric (AMT) data is applicable to characterise cover sequences, where their conductivity (inverse resistivity) can be differentiated. We present a regional study from the under-cover East Tennant region in the Northern Territory (Australia) where we have applied deterministic and probabilistic inversion methods to derive 2D and 1D resistivity models. We integrated these models with information of co-located basement penetrating boreholes (lithological and geophysical logs) to ground-truth and validate the models and to improve geophysical interpretations. In the East Tennant region, borehole lithology and wireline logging demonstrate that the modelled AMT response is largely controlled by the mineralogy of the cover and basement rocks. The bulk conductivity is due primarily to bulk mineralogy and the success of using the AMT models to predict cover thickness is shown to be dependent on whether the bulk mineralogy of cover and basement rocks are sufficiently different to provide a detectable conductivity contrast. Our investigation of a range of geological scenarios that differ in thickness, complexity and geology of the cover and basement rocks suggests that in areas where there is sufficient difference in bulk mineralogy and where the stratigraphy is relatively simple, AMT models predict the cover thickness with high certainty. In more complex scenarios interpretation of AMT models may be more ambiguous and requires integration with other data (e.g. drilling, wireline logging, potential field modelling). Overall, we conclude that the application of the method has been validated and the results compare favourably with borehole stratigraphy logs once geological (i.e. bulk mineralogical) complexity is understood. This demonstrates that the method is capable of identifying major litho-stratigraphic units with resistivity contrasts. Our results have assisted with the planning of regional drilling programs and have helped to reduce the uncertainty and risk associated with intersecting targeted stratigraphic units in covered terrains. [ABSTRACT FROM AUTHOR]