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• W2063681606 abstract "Tomographic velocity model building has become an industry standard for depth migration. Anisotropy of the Earth challenges tomography because the inverse problem becomes severely ill-posed. Singular value decomposition (SVD) of tomographic operators or, similarly, eigendecomposition of the corresponding normal equations, are well known as a useful framework for analysis of the most significant dependencies between model and data. However, application of this approach in velocity model building has been limited, primarily because of the perception that it is computationally prohibitively expensive, especially for the anisotropic case. In this paper, we extend our prior work (Osypov et al., 2008) to VTI tomography, modify the process of regularization optimization, and propose an updated way for uncertainty and resolution quantification using the apparatus of eigendecomposition. We demonstrate the simultaneous tomographic estimation of VTI parameters on a real dataset. Our approach provides extra capabilities for regularization optimization and uncertainty analysis in anisotropic model parameter space which can be further translated into the structural uncertainty within the image." @default.
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• W2063681606 date "2008-01-01" @default.
• W2063681606 modified "2023-09-30" @default.
• W2063681606 title "Uncertainty and resolution analysis for anisotropic tomography using iterative eigendecomposition" @default.
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• W2063681606 doi "https://doi.org/10.1190/1.3064019" @default.
• W2063681606 hasPublicationYear "2008" @default.
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