Abstract
SUMMARY 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.
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