Compression scheme for geophysical electromagnetic inversions

Abstract:

We have developed a model-compression scheme for improving the efficiency of the regularized Gauss-Newton inversion algorithm for geophysical 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 geophysical 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.