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Conjugate Gradient Least-Squares Algorithm for Three-Dimensional Magnetotelluric Inversion  

Kim, Hee-Joon (Dept. of Environmental Exploration Eng., Pukyong National University)
Han, Nu-Ree (Dept. of Civil, Urban and Geosystem Eng., Seoul National University)
Choi, Ji-Hyang (Dept. of Civil, Urban and Geosystem Eng., Seoul National University)
Nam, Myung-Jin (Dept. of Petroleum and Geosystem Eng., The University of Texas at Austin)
Song, Yoon-Ho (Korea Institute of Geoscience & Mineral Resources)
Suh, Jung-Hee (Dept. of Civil, Urban and Geosystem Eng., Seoul National University)
Publication Information
Geophysics and Geophysical Exploration / v.10, no.2, 2007 , pp. 147-153 More about this Journal
Abstract
The conjugate gradient (CG) method is one of the most efficient algorithms for solving a linear system of equations. In addition to being used as a linear equation solver, it can be applied to a least-squares problem. When the CG method is applied to large-scale three-dimensional inversion of magnetotelluric data, two approaches have been pursued; one is the linear CG inversion in which each step of the Gauss-Newton iteration is incompletely solved using a truncated CG technique, and the other is referred to as the nonlinear CG inversion in which CG is directly applied to the minimization of objective functional for a nonlinear inverse problem. In each procedure we only need to compute the effect of the sensitivity matrix or its transpose multiplying an arbitrary vector, significantly reducing the computational requirements needed to do large-scale inversion.
Keywords
conjugate gradient(CG); least-squares; magnetotelluric; inversion; sensitivity;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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