Seismic signal enhancement based on the low‐rank methods

Abstract

Based on the fact that the Hankel matrix constructed by noise-free seismic data is low-rank, low-rank approximation (or rank-reduction) methods have been widely used for removing noise from seismic data. Due to the linear-event assumption of the traditional low-rank approximation method, it is difficult to define a rank that optimally separates the data subspace into signal and noise subspaces. For preserving the most useful signal energy, a relatively large rank threshold is often chosen, which inevitably leaves residual noise. To reduce the energy of residual noise, we propose an optimally damped rank-reduction method. The optimal damping is applied via two steps. In the first step, a set of optimal damping weights is derived. In the second step, we derive an optimal singular value damping operator. We review several traditional low-rank methods and compare their performance with the new one. We also compare these low-rank methods with two sparsity-promoting transform methods. Examples demonstrate that the proposed optimally damped rank-reduction method could get significantly cleaner denoised images compared with the state-of-the-art methods.

Seismic sedimentological interpretation method under coal seam interference: a case study of Shan2 in the southeast Ordos Basin

“…There are two problems in the seismic exploration of Shan2 in the southeast Ordos Basin: one is the poor quality of seismic data, and the other is the significant interference of coal seams to seismic waves. As a result, the accuracy of using conventional seismic methods to study the distribution of sedimentary facies is low, such as seismic stratigraphy [1,[13][14] , seismic attribute extraction [15][16] and seismic sedimentology [17][18][19] .…”