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• W2065795854 abstract "We extend the cross-gradient methodology for joint inversion to three-dimensional environments and introduce a solution procedure based on a statistical formulation and equality constraints for structural similarity resemblance. We apply the proposed solution to the joint 3D inversion of gravity and magnetic data and gauge the advantages of this new formulation on test and field-data experiments. Combining singular-value decomposition (SVD) and other conventional regularizing constraints, we determine 3D distributions of the density and magnetization with enhanced structural similarity. The algorithm reduces some misleading features of the models, which are introduced commonly by conventional separate inversions of gravity and magnetic data, and facilitates an integrated interpretation of the models." @default.
• W2065795854 created "2016-06-24" @default.
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• W2065795854 date "2009-07-01" @default.
• W2065795854 modified "2023-10-14" @default.
• W2065795854 title "Cross-gradients joint 3D inversion with applications to gravity and magnetic data" @default.
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• W2065795854 doi "https://doi.org/10.1190/1.3119263" @default.
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