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Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp018049g7563
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dc.contributor.advisorTromp, Jeroen-
dc.contributor.authorModrak, Ryan-
dc.contributor.otherGeosciences Department-
dc.date.accessioned2017-04-12T20:40:12Z-
dc.date.available2017-04-12T20:40:12Z-
dc.date.issued2017-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/dsp018049g7563-
dc.description.abstractReaching the global minimum of a waveform misfit function requires careful choices about the nonlinear optimization, preconditioning and regularization methods underlying an inversion. Because waveform inversion problems are susceptible to erratic convergence, one or two test cases are not enough to reliably inform such decisions. We identify best practices instead using two global, one regional and four near-surface acoustic test problems. To obtain meaningful quantitative comparisons, we carry out hundreds acoustic inversions, varying one aspect of the implementation at a time. Comparing nonlinear optimization algorithms, we find that L-BFGS provides computational savings over nonlinear conjugate gradient methods in a wide variety of test cases. Comparing preconditioners, we show that a new diagonal scaling derived from the adjoint of the forward operator provides better performance than two conventional preconditioning schemes. Comparing regularization strategies, we find that projection, convolution, Tikhonov regularization, and total variation regularization are effective in different contexts. Besides these issues, reliability and efficiency in waveform inversion depend on close numerical attention and care. Implementation details have a strong effect on computational cost, regardless of the chosen material parameterization or nonlinear optimization algorithm. Building on the acoustic inversion results, we carry out elastic experiments with four test problems, three objective functions, and four material parameterizations. The choice of parameterization for isotropic elastic media is found to be more complicated than previous studies suggests, with ``wavespeed-like'' parameters performing well with phase-based objective functions and Lam\'{e} parameters performing well with amplitude-based objective functions. Reliability and efficiency can be even harder to achieve in transversely isotropic elastic inversions because rotation angle parameters describing fast-axis direction are difficult to recover. Using Voigt or Chen-Tromp parameters avoids the need to include rotation angles explicitly and provides an effective strategy for anisotropic inversion. The need for flexible and portable workflow management tools for seismic inversion also poses a major challenge. In a final chapter, the software used to the carry out the above experiments is described and instructions for reproducing experimental results are given.-
dc.language.isoen-
dc.publisherPrinceton, NJ : Princeton University-
dc.relation.isformatofThe Mudd Manuscript Library retains one bound copy of each dissertation. Search for these copies in the library's main catalog: <a href=http://catalog.princeton.edu> catalog.princeton.edu </a>-
dc.subjectelasticity and anisotropy-
dc.subjectinverse theory-
dc.subjectnear-surface geophysics-
dc.subjectnonlinear optimization-
dc.subjectnumerical wave propagation-
dc.subjectseismology-
dc.subject.classificationGeophysics-
dc.titleAcoustic and Elastic Waveform Inversion Best Practices-
dc.typeAcademic dissertations (Ph.D.)-
pu.projectgrantnumber690-2143-
Appears in Collections:Geosciences

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