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2D Sparse Magnetization Vector Inversion Based On L1-Minimization
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, 79th EAGE Conference and Exhibition 2017, Jun 2017, Volume 2017, p.1 - 5
Abstract
Remanence effect makes the standard magnetic inversion method ineffective. To deal with this problem, we present a 2D sparse magnetization vector inversion method using the interior-point algorithm. This method consists of three steps. First, we transform the total-field data into magnetic amplitude data, which is independent on the total magnetization direction. Second, we use a bound-constrained l1-regularized method to invert the amplitude data for the magnetization amplitude model. Third, we use a bound-constrained l2-regularized method to invert the total-field for the magnetization inclination model based on the amplitude model calculated from the previous step. Our method yields results characterized by sharp boundaries. Tests on synthetic examples demonstrate the utility of the proposed method.