Seismic feature extraction using steiner tree methods

Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Ligang Lu, Xingang Chi, Detlef Hohl

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    Identifying 'interesting' features, such as faults, unconformities, and other events in subsurface images is a challenging task in seismic data processing. Existing state-of-the-art methods usually involve manual intervention in the form of a visual inspection by an expert, but this is time-consuming, expensive, and error-prone. In this paper, we propose an efficient, automatic approach for seismic feature extraction. The core idea of our approach involves interpreting a given 2D seismic image as a function defined over the vertices of a specially chosen underlying graph. This enables us to formulate the feature extraction task as an instance of the Prize-Collecting Steiner Tree problem encountered in combinatorial optimization. We develop an efficient algorithm to solve this problem, and demonstrate the utility of our method on a number of synthetic and real examples.

    Original languageEnglish (US)
    Title of host publication2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1647-1651
    Number of pages5
    ISBN (Electronic)9781467369978
    DOIs
    StatePublished - Aug 4 2015
    Event40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Brisbane, Australia
    Duration: Apr 19 2014Apr 24 2014

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume2015-August
    ISSN (Print)1520-6149

    Other

    Other40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015
    CountryAustralia
    CityBrisbane
    Period4/19/144/24/14

    Keywords

    • Prize Collecting Steiner Tree problem
    • Seismic signal processing
    • combinatorial optimization

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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  • Cite this

    Schmidt, L., Hegde, C., Indyk, P., Lu, L., Chi, X., & Hohl, D. (2015). Seismic feature extraction using steiner tree methods. In 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015 - Proceedings (pp. 1647-1651). [7178250] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings; Vol. 2015-August). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2015.7178250