3D inversion of time domain electromagnetic data

Abstract

Airborne time-domain electromagnetic (EM) surveys are effective tools for mineral exploration, geologic mapping and environmental applications. These surveys can be an economical way to explore large prospective regions. Traditionally, the data from such surveys have been interpreted using time constant analysis, conductivity to depth imaging (CDI) or possibly 1D inversions. These methods assist in a simple interpretation of the data, however because they do not fully model the physics in 3D, they can fail to accurately represent environments such as real world structures and geological targets. Airborne EM datasets are characterized by large volumes of data, as each EM sounding implies a new transmitter location. As a result, inverting this data in 3D is a computationally difficult problem that until recently has not been possible for the exploration community. In this abstract we demonstrate a methodology for inverting large airborne EM surveys in 3D using multiple meshes, each spanning the full model domain. By using an adaptive meshing procedure during the forward modeling, each mesh is optimally designed for computational efficiency on the local domains defined by a subset of transmitters. This procedure allows the computational cost of each mesh to be dependent on the number of subset transmitters considered, rather than the total survey size. Since the forward modeling operation is the bottleneck for any inversion, this results in a highly parallel algorithm that can handle arbitrarily large datasets. In this abstract we outline our airborne electromagnetic inversion methodology and demonstrate it using synthetic and field data examples.