A Robust Adaptive Rank-Reduction Method for 3D Diffraction Separation and Imaging.

Diffractions with good illumination carry valuable subwavelength information below the Rayleigh limit and can be used for high-resolution imaging of small-scale discontinuous features. As diffractions are characterized by weak energy, diffracted wavefield separation is a key step before imaging of discontinuities. The traditional multichannel singular-spectrum analysis (MSSA) for diffraction separation considers the constant rank strategy. It is challenging to estimate the appropriate rank for various data. In this study, we propose a robust adaptive rank-reduction method for 3D diffraction separation and imaging. It utilizes the low-rank characteristics of reflections in the common-offset or poststack domain based on the MSSA algorithm. The method considers the kinematic and dynamic differences of reflections and diffractions, and combines the energy intensity and smoothed curvature to accurately estimate the rank thresholds as well as the ranks of the reflections and diffractions. Three-dimensional multilayer and complex synthetic examples are used to demonstrate the feasibility of the proposed method in removing reflections and separating diffractions and achieving high-resolution imaging with diffractions, which is helpful for seismic data interpretation. [ABSTRACT FROM AUTHOR]