Imaging point diffractors using a low-rank approximation method

Abstract

Diffraction separation plays a critical role in obtaining high-resolution images of subsurface diffractors by eliminating the diffractions’ contribution from reflections. It is usually based on the difference in spatial coherency between seismic reflection and diffraction energy in the time domain. Methods based on local slope differences, e.g., plane-wave destruction (PWD) method, tend to separate point and line diffractors simultaneously. This paper applies a rank-based diffraction separation method, known as the localized rank-reduction (LRR) method, to distinguish point diffractors in poststack data sets from line diffractors, thereby obtaining a higher resolution when characterizing point discontinuities such as karst caves. To make the LRR method more adaptive, a novel rank determination method based on a newly defined accumulated singular value ratio sequence is developed. The effectiveness of the proposed method is proved via a variety of 2D/3D synthetic and real data examples and a detailed discussion of its practical potential. Despite a larger computational cost compared to the PWD method, the proposed method helps interpretation by enabling us to distinguish between line and point diffractors.