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Stacking angle‐domain common‐image gathers for normalization of illumination
Author(s) -
Liu Guochang,
Fomel Sergey,
Chen Xiaohong
Publication year - 2011
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/j.1365-2478.2010.00916.x
Subject(s) - stacking , geology , reflection (computer programming) , normalization (sociology) , seismic migration , thresholding , artificial intelligence , computer vision , amplitude , image quality , computer science , optics , image (mathematics) , physics , seismology , nuclear magnetic resonance , sociology , anthropology , programming language
Unequal illumination of the subsurface highly impacts the quality of seismic imaging. Different image points receive different folds of reflection‐angle illumination, which can be caused by irregular acquisition or by wave propagation in complex media. Illumination problems can deteriorate amplitudes in migrated images. To address this problem, we present a method of stacking angle‐domain common‐image gathers, in which we use local similarity with soft thresholding to determine the folds of local illumination. Normalization by local similarity regularizes local illumination of reflection angles for each image point of the subsurface model. This approach compensates for irregular illumination by selective stacking in the image space, regardless of the cause of acquisition or propagation irregularities. Additional migration is not required because the methodology is implemented in the reflection angle domain after migration. We use two synthetic examples to demonstrate that our method can normalize migration amplitudes and effectively suppress migration artefacts.