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    Bayes Meets Tikhonov: Understanding Uncertainty Within Gaussian Framework for Seismic Inversion

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    Bayes_meets_Tikhonov__Understanding_Uncertainty_within_Gaussian_Framework_for_Seismic_Inversion.pdf
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    1.027Mb
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    Description:
    Accepted manuscript
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    Type
    Book Chapter
    Authors
    Izzatullah, Muhammad cc
    Peter, Daniel cc
    Kabanikhin, Sergey
    Shishlenin, Maxim
    KAUST Department
    Earth Science and Engineering Program
    Physical Science and Engineering (PSE) Division
    Extreme Computing Research Center
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2020-10-22
    Online Publication Date
    2020-10-22
    Print Publication Date
    2021
    Permanent link to this record
    http://hdl.handle.net/10754/665903
    
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    Abstract
    In this chapter, we demonstrate the sound connection between the Bayesian approach and the Tikhonov regularisation within Gaussian framework. We provide a thorough uncertainty analysis to answer the following two fundamental questions: (1) How well is the estimate determined by a posteriori PDF, i.e. by the combination of observed data and a priori information? (2) What are the respective contributions of observed data and a priori information? To support the proposed methodology, we demonstrate it through numerical applications in seismic inversions.
    Citation
    Izzatullah, M., Peter, D., Kabanikhin, S., & Shishlenin, M. (2020). Bayes Meets Tikhonov: Understanding Uncertainty Within Gaussian Framework for Seismic Inversion. Studies in Systems, Decision and Control, 121–145. doi:10.1007/978-981-15-8606-4_8
    Publisher
    Springer Nature
    ISBN
    9789811586057
    9789811586064
    DOI
    10.1007/978-981-15-8606-4_8
    Additional Links
    http://link.springer.com/10.1007/978-981-15-8606-4_8
    ae974a485f413a2113503eed53cd6c53
    10.1007/978-981-15-8606-4_8
    Scopus Count
    Collections
    Physical Science and Engineering (PSE) Division; Extreme Computing Research Center; Earth Science and Engineering Program; Book Chapters; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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