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    Novel Misfit Functions for Full-waveform Inversion

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    PhD_Dissertation_FuqiangChen.pdf
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    Description:
    PhD Dissertation
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    Type
    Dissertation
    Authors
    Chen, Fuqiang cc
    Advisors
    Peter, Daniel cc
    Committee members
    Keyes, David E. cc
    Ravasi, Matteo cc
    Fomel, Sergey
    Program
    Earth Science and Engineering
    KAUST Department
    Physical Science and Engineering (PSE) Division
    Date
    2022-04
    Permanent link to this record
    http://hdl.handle.net/10754/677938
    
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    Abstract
    The main objective of this thesis is to develop novel misfit functions for full-waveform inversion such that (a) the estimation of the long-wavelength model will less likely stagnate in spurious local minima and (b) the inversion is immune to wavelet inaccuracy. First, I investigate the pros and cons of misfit functions based on optimal transport theory to indicate the traveltime discrepancy for seismic data. Even though the mathematically well-defined optimal transport theory is robust to highlight the traveltime difference between two probability distributions, it becomes restricted as applied to seismic data mainly because the seismic data are not probability distribution functions. We then develop a misfit function combining the local cross-correlation and dynamic time warping. This combination enables the proposed misfit automatically identify arrivals associated with a phase shift. Numerical and field data examples demonstrate its robustness for early arrivals and limitations for later arrivals.%, which means that a proper pre-processing step is still required. Next, we introduce differentiable dynamic time warping distance as the misfit function highlighting the traveltime discrepancy without non-trivial human intervention. Compared to the conventional warping distance, the differentiable version retains the property of representing the traveltime difference; moreover, it can eliminate abrupt changes in the adjoint source, which helps full-waveform inversion converge to geologically relevant estimates. Finally, we develop a misfit function entitled the deconvolutional double-difference measurement. The new misfit measures the first difference by deconvolution rather than cross-correlation. We also present the derivation of the adjoint source with the new misfit function. Numerical examples and mathematical proof demonstrate that this modification makes full-waveform inversion with the deconvolutional double-difference measurement immune to wavelet inaccuracy.
    Citation
    Chen, F. (2022). Novel Misfit Functions for Full-waveform Inversion. KAUST Research Repository. https://doi.org/10.25781/KAUST-N88Q0
    DOI
    10.25781/KAUST-N88Q0
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-N88Q0
    Scopus Count
    Collections
    PhD Dissertations; Physical Science and Engineering (PSE) Division; Earth Science and Engineering Program

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