Automatic fault localization using the generalized Earth Mover's distance

Ludwig Schmidt, Chinmay Hegde, Piotr Indyk, Jonathan Kane, Ligang Lu, Detlef Hohl

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

    Abstract

    Localizing fault lines and surfaces in seismic subsurface images is a daunting challenge. Existing state-of-the-art approaches usually involve visual interpretation by an expert, but this is time-consuming, expensive and error-prone. In this paper, we propose some initial steps towards a new algorithmic framework for automatic fault localization. The core of our approach is a deterministic model for 2D images that we call the Constrained Generalized Earth Mover's Distance (CGEMD) model. We propose an algorithm that returns the best approximation in the model for any given input 2D image X; the output of this algorithm is then post-processed to reveal the locations of the faults in the image. We demonstrate the validity of this approach on a number of synthetic and real-world examples.

    Original languageEnglish (US)
    Title of host publication2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages8134-8138
    Number of pages5
    ISBN (Print)9781479928927
    DOIs
    StatePublished - 2014
    Event2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 - Florence, Italy
    Duration: May 4 2014May 9 2014

    Publication series

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

    Other

    Other2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
    Country/TerritoryItaly
    CityFlorence
    Period5/4/145/9/14

    Keywords

    • Earth Mover's Distance
    • Sparse recovery
    • min-cost flows
    • seismic signal processing

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Electrical and Electronic Engineering

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