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- Title
Two-dimensional inversion of magnetotelluric data with consecutive use of conjugate gradient and least-squares solution with singular value decomposition algorithms.
- Authors
Candansayar, M. Emin
- Abstract
I investigated the two-dimensional magnetotelluric data inversion algorithms in studying two significant aspects within a linearized inversion approach. The first one is the method of minimization and second one is the type of stabilizing functional used in parametric functionals. The results of two well-known inversion algorithms, namely conjugate gradient and the least-squares solution with singular value decomposition, were compared in terms of accuracy and CPU time. In addition, magnetotelluric data inversion with various stabilizers, such as L2-norm, smoothing, minimum support, minimum gradient support and first-order minimum entropy, were examined. A new inversion algorithm named least-squares solution with singular value decomposition and conjugate gradient is suggested in seeing the outcomes of the comparisons carried out on least-squares solutions with singular value decomposition and conjugate gradient algorithms subject to a variety of stabilizers. Inversion results of synthetic data showed that the newly suggested algorithm yields better results than those of the individual implementations of conjugate gradient and least-squares solution with singular value decomposition algorithms. The suggested algorithm and the above-mentioned algorithms inversion results for the field data collected along a line crossing the North Anatolian Fault zone were also compared each other and results are discussed.
- Subjects
MAGNETOTELLURIC prospecting; ALGORITHMS; GEOMETRY; ENTROPY; GEOLOGY
- Publication
Geophysical Prospecting, 2008, Vol 56, Issue 1, p141
- ISSN
0016-8025
- Publication type
Article
- DOI
10.1111/j.1365-2478.2007.00668.x