Guochang Liu
, China University of Petroleum-Beijing and
The University of Texas at Austin; Sergey Fomel,
The University of Texas at Austin; Xiaohong Chen,
China University of Petroleum-Beijing
Unequal illumination of the subsurface highly impacts the quality of seismic imaging.
Different image points of the media have different folds of reflection-angle illumination,
which can be caused by irregular acquisition or by wave propagation in complex media.
To address this problem, we present a method of stacking angle-domain common-image gathers (ADCIGs),
in which we use local similarity with soft thresholding to decide 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 can restore good fidelity of amplitude
by selective stacking in the image space, whatever the cause of acquisition or propagation irregularities.
We use two synthetic examples to demonstrate that our method can normalize migration amplitudes and
effectively suppress migration artifacts.
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