Abstract
We have developed a model-compression scheme for improving the efficiency of the regularized Gauss-Newton inversion algorithm for marine controlled-source electromagnetic applications. In this scheme, the unknown model parameters (the conductivity/resistivity distribution) are represented in terms of a basis such as Fourier and wavelet (Haar and Daubechies). By applying a truncation criterion, the model may then be approximated by a reduced number of basis functions, which is usually much less than the number of the model parameters. Further, because the controlled-source electromagnetic measurements have low resolution, it is sufficient for inversion to only keep the low-spatial-frequency part of the image. This model-compression scheme accelerates the computational time and also reduces the memory usage of the Gauss-Newton method. We are able to significantly reduce the algorithm computational complexity without compromising the quality of the inverted models.
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