Controlled-source Electromagnetic Inversion Using Truncated Wavelet Representations

We present 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 resistivity distribution is represented in terms of a basis such as Fourier, cosine, or wavelet. By applying a proper 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. Furthermore, since the controlled-source electromagnetic measurements have low-resolution, we will show that for inversion it is sufficient to only keep the low-spatial frequency part of the image. This model compression scheme accelerates the computational time as well as reduces the memory usage of the Gauss-Newton method. For demonstration purposes, we show both synthetic and field data inversions. The results show that we are able to significantly reduce the algorithm computational complexity without compromising the quality of the inverted models.