Assessing Quantitatively Interpretable Zones From 1D Forward Modelling Aem Inversion Models

The inversion of time-domain AEM data with full 3D inversion requires specialists’ expertise and a huge amount of computational resources, not readily available to everyone. Consequently, quasi-2D/3D inversion methods are prevailing, using a much faster but approximate (1D) forward model. The question remains whether the obtained inversion results are reliable and can be interpreted quantitatively. We propose an appraisal tool for quasi-2D/3D methods that indicate zones in the inversion model that are not in agreement with the multidimensional (2D/3D) forward model and therefore, should not be interpreted in a quantitative fashion. The image appraisal step only requires one full 2.5D or 3D forward and one multidimensional Jacobian computation on a coarse mesh to compute a so-called normalized gradient. Large values in that gradient indicate model parameters that do not fit the true multidimensionality of the observed data well and should not be interpreted quantitatively. We demonstrate our method on a real AEM survey in a salinization context, revealing problematic zones in the fresh-saltwater interface. Interestingly, the problematic zones are not necessarily at larger depths, but where the interface is changing. The advantage of our approach is that all computations are feasible on a single laptop.