Focal deblending using smart subsets of towed streamer 5D data

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    5 Citations (Scopus)


    Blended data acquisition is gaining popularity, requiring - in most cases - a deblending process before further processing and imaging is applied. Recently, focal transform-based de- blending has been proposed. By applying subsurface-based fo- cal operators to both sources and receivers, reflection informa- tion can be sparsely represented and, thereby, separated in the focal domain from blending noise. Although focal deblending can be easily extended to handle 5D data, involving all four spatial axes in the focusing process will be computationally costly. Instead, we propose dividing the data in 'smart' sub- sets that emerge naturally from the acquisition type, and using focal operators designed for those subsets. In this way, each subset can be deblended independently from the rest. We de- fine such subsets for the case of a marine towed multi-streamer acquisition and test the deblending performance on a synthetic dataset.

    Original languageEnglish
    Title of host publicationSEG International Exposition and 86th Annual Meeting, SEG 2016; Dallas; United States; 16 October 2011 through 21 October 2011
    EditorsC. Sicking, J. Ferguson Sicking
    Number of pages6
    Publication statusPublished - 2016
    EventSEG International Exposition and 86th Annual Meeting - Dallas & Kay Bailey Hutchison Convention Center, Dallas, United States
    Duration: 16 Oct 201621 Oct 2016
    Conference number: 86

    Publication series

    NameSEG Technical Program Expanded Abstracts
    PublisherSociety of Exploration Geophysicists
    ISSN (Print)1052-3812


    ConferenceSEG International Exposition and 86th Annual Meeting
    Abbreviated titleSEG 2016
    Country/TerritoryUnited States
    Internet address


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