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

Airborne electromagnetic data generated by the AusAEM Survey are shown to map mineral deposit host rocks and regional geological features within the AusAEM Survey area. We have developed new functionality in Geoscience Australia’s sample-by-sample layered earth inversion algorithm, allowing inversion of the magnitude of the combined vector sum of the X- and Z-components of TEMPEST AEM data. This functionality improves the clarity of inverted interpretation products by reducing the degree of along-line incoherency inherent to stitched 1D inversions. The new inversion approach improves the interpretability of sub-horizontal conductors, allowing better mapping of geological features under cover. Examples of geological mapping by the AusAEM survey highlight the utility of wide line spacing, regional AEM surveying to improve geological, mineral systems and groundwater resource understanding in the regions flanking outcropping mineral deposit host rocks in northern Australia. Presented at the 2019 Australasian Exploration Geoscience Conference

This paper presents the application of a novel trans-dimensional sampling approach to a time domain airborne electromagnetic (AEM) inverse problem to solve for plausible conductivities of the subsurface. Geophysical inverse problems, such as time domain AEM, are well known to have a large degree of non-uniqueness. Common least-squares optimization approaches fail to take this into account and provide a single solution with linearized estimates of uncertainty which can result in overly optimistic appraisal of the conductivity of the subsurface. In this new non-linear approach, the spatial complexity of a 2D profile is controlled directly by the data. By examining an ensemble of proposed conductivity profiles it accommodates non-uniqueness and provides more robust estimates of uncertainties. <b>Citation:</b> Hawkins, R., Brodie, R. C., & Sambridge, M. (2018). Trans-dimensional Bayesian inversion of airborne electromagnetic data for 2D conductivity profiles. <i>Exploration Geophysics</i>, 49(2), 134–147. https://doi.org/10.1071/EG16139