Gravity-magnetic cross-gradient joint inversion by the cyclic gradient method. (2nd September 2020)

• Record Type: Journal Article
• Authors: Sun, Cong; Wang, Yanfei
• Is Part Of: Optimization methods and software. Volume 35:Number 5(2020)
• Page Start: 982
• Page End: 1001
• Publication Date: 2020-09-02
• Subjects: Joint inversion -- l1 regularization -- cyclic gradient method -- linear convergence rate; 92C55 -- 15A29 -- 65K10 -- 68U10; Mathematical optimization -- Periodicals; Algorithms -- Periodicals; 519.7
• DOI: 10.1080/10556788.2020.1786565
• Languages: English
• ISSNs: 1055-6788

Abstract

Abstract : In this paper, we consider a joint-inversion problem using different types of geophysical data: gravity and magnetism. We first formulate two kinds of inverse problems in the famework of the first kind Fredholm integral equations, and then build up a sparse inversion model combining the two inverse problems as well as the cross-gradient term. The cyclic gradient method for quadratic function minimization is extended for solving the corresponding optimization problem. We update the stepsizes in a cyclic way, by combining the approximated Cauchy steps and the fixed steplengths. Theoretical analysis shows that the algorithm converges R-linearly. Experimental tests show that the proposed joint inversion sparse model as well as the proposed cyclic gradient method improve the numerical performances effectively, compared to the state of the art.