Airborne electromagnetic (AEM) surveys are widely used for hydrogeological applications. The areas targeted for AEM campaigns may present a great deal of ancillary information (e.g. resistivity logs, lithology, etc.) and integrating it with AEM data is fundamental. Yet, using this information either as a-priori or a-posteriori may bring out conflict between different datasets, preventing reconciliation everywhere. For instance, some borehole drillings may have been logged inaccurately, AEM data may present bias, or data may have been acquired at different times, with variations occurring in between . In this study we present a way to integrate AEM data and other types of resistivity data (boreholes electrical logging and vertical electrical soundings, in this case), through an inversion scheme that identify automatically conflicting data without preventing the general convergence of the process. To do so, we make use of a generalization of the minimum support norm, the asymmetric generalized minimum support (AGMS) norm, for defining the data misfit in the objective function of an iterative reweighted least squared (IRLS) gauss-newton inversion. The AGMS norm in the data misfit puts a cap on the weight of non- fitting data points, allowing for the inversion to focus on the data points that can be fitted. Outliers are identified after the AGMS inversion and excluded, in order to complete the inversion process with a classic L2 misfit. We present an application of this method in the Netherlands, on a SkyTEM survey complemented with a vast and open-source database of ashore resistivity logs, as well as vertical electrical soundings (VES).

Open-Access Online Publication: November 3, 2023