3-D Crosswell electromagnetic inversion based on IRLS norm sparse optimization algorithms

Abstract

Due to the complexity of underground reservoir distribution and the non-uniqueness of geophysical inverse problems, there is still a lack of practical and effective cross-well electromagnetic inversion methods. Our goal is to develop an efficient method to reduce the non-uniqueness of the physical property model recovered in the inversion. Based on a defined framework, we propose a 3-D crosswell electromagnetic sparse inversion based on iterative reweighted least squares (IRLS) method. We perform the inversion using a hybrid norm formulation, where the lp-norm (0 ≤ p ≤ 1) sparse optimization problem can be transformed into a series of weighted l2-norm optimization problems. Compared with the traditional norm inversion method, the sparse inversion method can make more effective use of the known physical information and obtain more accurate abnormal body position and shape. Finally, the effectiveness of sparse inversion method is verified by model test and inversion of measured data in mining area.