A new denoising strategy and the X-shaped supplement denoising operator targeting time-reversed mirror imaging technique
Author(s) -
Lingli Zhang,
Yuxiao Ren,
Lei Chen,
Kai Wang,
Xinji Xu,
Xiaobin Xu,
Chao Fu
Publication year - 2021
Publication title -
journal of geophysics and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.623
H-Index - 38
eISSN - 1742-2140
pISSN - 1742-2132
DOI - 10.1093/jge/gxab030
Subject(s) - noise reduction , operator (biology) , noise (video) , artificial intelligence , wavelet , computer vision , laplace operator , computer science , image (mathematics) , image denoising , algorithm , mathematics , mathematical analysis , biochemistry , chemistry , repressor , transcription factor , gene
Imaging of vertical structures is a challenge in the seismic imaging field. The conventional imaging methods for vertical structures are highly dependent on the reference model or boreholes. Time-reversed mirror imaging can effectively image the vertical structures based on the multiples and a smoothed velocity model without the need of accurate seismic wavelet estimation. Although the Laplacian operator is applied in time-reversed mirror imaging, there still exists severe residual noise. In this study, we developed a new imaging denoising strategy and an X-shaped supplement denoising operator for time-reversed mirror imaging based on the geometric features of the image and the causes of imaging noise. Synthetic results for the single- and double-staircase model prove the powerful denoising capacity of the X-shaped supplement denoising operator. In addition, the results of a Marmousi model prove that the X-shaped denoising operator can also effectively suppress the noise when applying time-reversed mirror imaging method to image complex inclined structures. However, the X-shaped denoising operator still contains some limitations, such as non-amplitude-preserving.
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