Abstract

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2005Structural inversion of gravity data using linear programming: a case studyAuthors: Tim van ZonKabir Roy ChowdhuryTim van ZonUtrecht UniversitySearch for more papers by this author and Kabir Roy ChowdhuryUtrecht UniversitySearch for more papers by this authorhttps://doi.org/10.1190/1.2144426 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract We investigate the applicability of the Linear Programming (LP) based inversion to a regional scale gravity data‐set. The data is inverted, assuming a bi‐modal lithology, and a 2.5‐D geometry, for the basement topography using a rectangular gridded parameterization. Linear Programming is used to minimize the L1‐norm of the data‐fit. Several aspects of the ”history” of the data‐set pertaining to the pre‐processing and the geological setting were unknown. We show that some of these effects can be bundled together and inverted for. Given a density contrast between the lithotypes, an inversion with Linear Programming has the intrinsic advantage that a structural model is retrieved instead of smooth one. The model we recover is almost bi‐modal and its general features seem to be robust with respect to the parameterization scenarios investigated. An offset and a linear trend in the data were also retrieved simultaneously. Our results are comparable to those obtained based on forward modeling using many narrow near‐vertical prisms.Permalink: https://doi.org/10.1190/1.2144426FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2005ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2005 Pages: 2668 publication data© 2005 Copyright © 2005 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 07 Dec 2005 CITATION INFORMATION Tim van Zon and Kabir Roy Chowdhury, (2005), "Structural inversion of gravity data using linear programming: a case study," SEG Technical Program Expanded Abstracts : 720-723. https://doi.org/10.1190/1.2144426 Plain-Language Summary PDF DownloadLoading ...

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