Trans-dimensional Bayesian inversion of Airborne Electromagnetic data for 2D conductivity profiles

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