INVERSION OF 3-D DC RESISTIVITY DATA USING AN APPROXIMATE INVERSE MAPPING

We present an iterative algorithm for inverting 3-D pole-pole DC resistivity data. The algorithm utilizes an AIM (approximate inverse mapping) formalism and iterative inversions are carried out by performing updates in both model space (AIM-MS) and data space (AIM-DS) by using an approximate inverse mapping with-an exact forward mapping. In the approximate inverse mapping, the potential anomaly is expressed as a depth integral of the logarithmic conductivity perturbation convolved horizontally with a known kernel. Fourier transforming the data equation decouples wavenumber components and the Fourier transform of the conductivity anomaly is recovered by performing 1-D linear inversions at each wavenumber. Inverse Fourier transforming the 1-D inversion results produces the sought conductivity. The AIM methodology avoids the generation and inversion of a full 3-D sensitivity matrix and is consequently fast and efficient. Only one forward modelling is performed at each iteration. The algorithm is tested with synthetic data and a field data set from an epithermal region.