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Least-squares diffraction imaging using shaping regularization by anisotropic smoothing
Geophysics ( IF 3.0 ) Pub Date : 2020-09-11 , DOI: 10.1190/geo2019-0741.1
Dmitrii Merzlikin 1 , Sergey Fomel 2 , Xinming Wu 3
Affiliation  

We have used least-squares migration to emphasize edge diffractions. The inverted forward-modeling operator is the chain of three operators: Kirchhoff modeling, azimuthal plane-wave destruction, and the path-summation integral filter. Azimuthal plane-wave destruction removes reflected energy without damaging edge-diffraction signatures. The path-summation integral guides the inversion toward probable diffraction locations. We combine sparsity constraints and anisotropic smoothing in the form of shaping regularization to highlight edge diffractions. Anisotropic smoothing enforces continuity along edges. Sparsity constraints emphasize diffractions perpendicular to edges and have a denoising effect. Synthetic and field data examples illustrate the effectiveness of the proposed approach in denoising and highlighting edge diffractions, such as channel edges and faults.

中文翻译:

通过各向异性平滑使用整形规则化的最小二乘衍射成像

我们使用最小二乘迁移法来强调边缘衍射。反向正演算子是三个算子的链:基尔霍夫模型,方位平面波破坏和路径求和积分滤波器。方位角平面波破坏可以消除反射能量,而不会损坏边缘衍射特征。路径总和积分将反演导向可能的衍射位置。我们将稀疏性约束和各向异性平滑以形状规则化的形式结合起来,以突出显示边缘衍射。各向异性平滑强制沿边缘连续。稀疏性约束强调垂直于边缘的衍射并具有去噪效果。合成和现场数据示例说明了该方法在消噪和突出边缘衍射方面的有效性,
更新日期:2020-09-16
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