2021
DOI: 10.1007/s10712-021-09676-y
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Mitigating Velocity Errors in Least-Squares Imaging Using Angle-Dependent Forward and Adjoint Gaussian Beam Operators

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Cited by 6 publications
(2 citation statements)
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“…where Λ true represents the true fractional pseudo-differential operator in the wavenumber domain (8). We used the interior-reflective Newton algorithm [37] to solve this leastsquares inverse problem.…”
Section: Approximating the Pseudo-differential Operator Using A Gener...mentioning
confidence: 99%
See 1 more Smart Citation
“…where Λ true represents the true fractional pseudo-differential operator in the wavenumber domain (8). We used the interior-reflective Newton algorithm [37] to solve this leastsquares inverse problem.…”
Section: Approximating the Pseudo-differential Operator Using A Gener...mentioning
confidence: 99%
“…It is suitable for lateral velocity variation and is not constrained by steeply dipping limitations. Over time, RTM has been expanded from acoustic isotropic media to viscoelastic anisotropic media [4][5][6] and, from adjointbased migration to least-squares migration [7,8]. In exploration regions with significant anisotropy, such as subsalt sediments and shale reservoirs, neglecting the anisotropy not only results in blurring and mispositioning of events, but also degrades and distorts seismic images [9].…”
Section: Introductionmentioning
confidence: 99%