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    Least-squares reverse time migration with radon preconditioning

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    segam2016-13943593.1.pdf
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    Expanded Abstract
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    Type
    Conference Paper
    Authors
    Dutta, Gaurav cc
    Agut, Cyril
    Giboli, Matteo
    Williamson, Paul
    KAUST Department
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2016-09
    Online Publication Date
    2016-09
    Print Publication Date
    2016-09
    Permanent link to this record
    http://hdl.handle.net/10754/625273
    
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    Abstract
    We present a least-squares reverse time migration (LSRTM) method using Radon preconditioning to regularize noisy or severely undersampled data. A high resolution local radon transform is used as a change of basis for the reflectivity and sparseness constraints are applied to the inverted reflectivity in the transform domain. This reflects the prior that for each location of the subsurface the number of geological dips is limited. The forward and the adjoint mapping of the reflectivity to the local Radon domain and back are done through 3D Fourier-based discrete Radon transform operators. The sparseness is enforced by applying weights to the Radon domain components which either vary with the amplitudes of the local dips or are thresholded at given quantiles. Numerical tests on synthetic and field data validate the effectiveness of the proposed approach in producing images with improved SNR and reduced aliasing artifacts when compared with standard RTM or LSRTM.
    Citation
    Dutta G, Agut C, Giboli M, Williamson P (2016) Least-squares reverse time migration with radon preconditioning. SEG Technical Program Expanded Abstracts 2016. Available: http://dx.doi.org/10.1190/segam2016-13943593.1.
    Publisher
    Society of Exploration Geophysicists
    Journal
    SEG Technical Program Expanded Abstracts 2016
    Conference/Event name
    SEG International Exposition and 86th Annual Meeting, SEG 2016
    DOI
    10.1190/segam2016-13943593.1
    Additional Links
    http://library.seg.org/doi/10.1190/segam2016-13943593.1
    ae974a485f413a2113503eed53cd6c53
    10.1190/segam2016-13943593.1
    Scopus Count
    Collections
    Conference Papers; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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