Title: Waveform Inversion via Nonlinear Differential Semblance Optimization
Abstract: PreviousNext No AccessSEG Technical Program Expanded Abstracts 2012Waveform Inversion via Nonlinear Differential Semblance OptimizationAuthors: Dong SunWilliam W SymesDong SunRice UniversitySearch for more papers by this author and William W SymesRice UniversitySearch for more papers by this authorhttps://doi.org/10.1190/segam2012-1190.1 SectionsSupplemental MaterialAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract This paper describes a nonlinear differential semblance approach to waveform inversion. Nonlinear differential semblance optimization combines the ability of full waveform inversion to account for nonlinear physical effects, such as multiple reflections, with the tendency of differential semblance migration velocity analysis to avoid local minima. It borrows the gather-flattening concept from migration velocity analysis, and updates the velocity by flattening primaries-only gathers obtained via nonlinear inversion. We describe the components of this algorithm, including the gradient calculation, and an implementation based on 2D plane wave modeling. We present a simple layered 2D example for which standard full waveform inversion fails, whereas nonlinear differential semblance succeeds in constructing a kinematically correct model and fitting the data rather precisely. 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Publication Year: 2012
Publication Date: 2012-09-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 30
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