Geophysical Inversion Enhancement Based on Blind Deconvolution

Abstract

Geophysical systematic errors inevitably occur during acquisition and processing of data because of noise and discretization as well as incorrect geophysical forward modeling. In this paper, a new technology is proposed to enhance the geophysical inversion model without introducing any additional information. The relationship between the inversion model resolution matrix and the enhancing model is described. We suggest that more information could be extracted from inversion results by using the blind deconvolution method. Then, a mix-norm TV regularization enhancement algorithm is proposed. Finally, we use the 1D and 2D magnetotelluric inversion models to prove the correctness and the effectiveness of the proposed methods. The results show that the proposed algorithm can increase geophysical model precision by 88.57%.