A Robust Random Noise Suppression Method for Seismic Data Using Sparse Low-Rank Estimation in the Time-Frequency Domain

Abstract

The noise separation from seismic data is of significant importance in geophysics. In most cases, the random noise always overlaps the seismic reflections over time, which makes it challenging to suppress. To enhance seismic signal, we propose a robust noise suppression method based on high-order synchrosqueezing transform (FSSTH) and robust principal component analysis (RPCA). Firstly, the noisy seismic data is transformed into a sparse time-frequency matrix (TFM) using the FSSTH. Then, the RPCA algorithm is employed to decompose the sparse TFM into a low-rank matrix and a sparse matrix that can be used to depict the useful signal and noise, respectively. Finally, the denoised signal can be obtained by back-transforming the low-rank matrix to the time domain via the inverse FSSTH. We utilize a synthetic data and two field datasets to demonstrate the robustness and superiority of our method, and compare with the conventional denoising algorithms such as f − x denconvolution and f − x singular spectrum analysis (SSA). The obtained results indicate that the proposed method is capable of achieving an excellent tradeoff between random noise suppression and seismic signal preservation.INDEX TERMS High-order synchrosqueezing transform, robust principal component analysis, low rank matrix, noise suppression.

Seismic data denoising through dual attention residual network

“…Some classical filter denoising methods have achieved good results in the noise suppression of seismic data (Liu et al, 2009;Li et al, 2019). Seismic records are time series data, which can be converted to other domains for noise suppression processing (Bing et al, 2020;Chen et al, 2014;Wu et al, 2021). In addition, wavelet transform (Langston et al, 2016), Fourier transform (Ma and Cao, 2019;Yu et al, 2017), seislet transform (Dalai et al, 2019) and the curvelet transform (Zhang et al, 2019) are also widely used for noise suppression of seismic data.…”