3D Land CSEM Inversion with a Single Transmiter Position

Anthropogenic noise, cost and logistical constrains generaly limit to the use of land CSEM to a few transmiter positions for the deep imaging of the electrical conductivity. The 3D inversion of CSEM data in the near field using a single transmiter position suffers from critical sensitivity singularities. We proposed a robust inversion framework adapted to this ill-conditioned inversion problem. The framework relies specificaly on a robust Gauss-Newton solver, model parameter transformations to compensate the heterogeneous sensitivies, and on the reformulation of the CSEM data under the form of a pseudo-MT tensor. We describe the approach used for modeling and inversion implemented in our code POLYEM3D and the new pseudo-MT formulation. We illustrate its application on a pathologic synthetic case inspired from grayver et al (2013) and then show the application of the process to a real CSEM dataset acquired in the context of thermal water prospection.