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    Multi-Dimensional Deconvolution with Stochastic Gradient Descent

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    Name:
    EAGE_2022_StochMDD.pdf
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    1.229Mb
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    PDF
    Description:
    Accepted Manuscript
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    Type
    Conference Paper
    Authors
    Ravasi, Matteo cc
    Pandurangan, T. Selvan
    Luiken, Nicolaas
    KAUST Department
    Earth Science and Engineering Program
    King Abdullah University of Science and Technology
    Physical Science and Engineering (PSE) Division
    Date
    2022
    Permanent link to this record
    http://hdl.handle.net/10754/678304
    
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    Abstract
    Multi-Dimensional Deconvolution (MDD) is a versatile technique used in seismic processing and imaging to create ideal datasets deprived of overburden effects. Whilst, the forward problem is well defined for a single source, stable inversion of the MDD equations relies on the availability of a large number of sources, this being independent on the domain where the problem is solved, frequency or time. In this work, we reinterpret the cost function of time-domain MDD as a finite-sum functional, and solve the associated problem by means of stochastic gradient descent algorithms, where gradients at each step are computed using a small subset of randomly selected sources. Through synthetic and field data examples, we show that the proposed method converges more stably than the conventional approach based on full gradients. Therefore, it represents a novel, efficient, and robust approach to deconvolve seismic wavefields in a multi-dimensional fashion.
    Citation
    Ravasi, M., Pandurangan, T. S., & Luiken, N. (2022). Multi-Dimensional Deconvolution with Stochastic Gradient Descent. 83rd EAGE Annual Conference & Exhibition. https://doi.org/10.3997/2214-4609.202210234
    Sponsors
    The authors thank KAUST for supporting this research. We are also grateful to Equinor and partners for releasing the Volve dataset.
    Publisher
    European Association of Geoscientists & Engineers
    Conference/Event name
    83rd EAGE Annual Conference & Exhibition
    DOI
    10.3997/2214-4609.202210234
    Additional Links
    https://www.earthdoc.org/content/papers/10.3997/2214-4609.202210234
    ae974a485f413a2113503eed53cd6c53
    10.3997/2214-4609.202210234
    Scopus Count
    Collections
    Conference Papers; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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