Denoising Seismic Signal via Resampling Local Applicability Functions

Fangyu Li, Kennesaw State University
Fengyuan Sun, Guilin University of Electronic Technology
Naihao Liu, Xi'an Jiaotong University
Rui Xie, University of Central Florida


We propose a novel seismic signal processing approach to efficiently and effectively attenuate seismic random noises. The proposed approach is a generalized seismic noise attenuation solution that can be applied to typical denoising operators. Our work has two main contributions. First, conventional filtering operators 'regularize' the denoised results through the operator design. However, as seismic data have strong nonstationarity, it is inevitable to remove certain signal components. The resampling mechanism alleviates the signal loss. Second, the resampling operation does not require a lot of parameter tuning, which improves the denoising efficiency. Using the proposed approach, compared with existing denoising operators, the intrinsic seismic signal components are better recovered since random noise has been suppressed. Synthetic example and field data applications quantitatively and qualitatively demonstrate excellent performances of the proposed approach.