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Regularized Low-Rank Approximation Method for Diffraction Enhancement
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DOI：10.1109/LGRS.2023.3289951.png)
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Abstract
En 中文
The significance of seismic diffractions for the high-resolution imaging of subsurface discontinuities has been emphasized in recent years. Separating diffractions from strong specular reflected wavefields is a crucial process owing to the weak amplitude of diffractions. The low-rank (LR) characteristics of seismic data have been successfully implemented for diffracted wavefield isolation using rank-reduction methods. Traditional LR-based diffraction separation uses the optimal LR approximation of the Hankel matrix formulated from seismic data for predicting linear reflection events. However, without the Hankel structure in traditional LR approximation, the Hankel matrix of estimated reflections does not exhibit the expected LR properties, which may affect the predicted reflection accuracy. In this study, a regularized LR (RLR) approximation method that exploits the LR properties of reflection events and the corresponding Hankel structure was developed to enhance diffractions and eliminate reflections. The RLR approximation algorithm considered the LR constraint of the Hankel matrix for estimated reflections, leading to improved LR approximation. Synthetic and field examples were used to demonstrate the effectiveness of the proposed algorithm in separating diffractions and imaging small subsurface geological structures.
Keywords:
Diffraction separation
discontinuous structures
Hankel structure
low rank
seismic imaging
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16.4
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