Seismic Traffic Noise Attenuation Using $l_{p}$ -Norm Robust PCA
Bangyu Wu, Jiaxu Yu, Haoran Ren, Yihuai Lou, Naihao Liu
Abstract
Traffic noise is often coupled with seismic signals when seismic data are acquired close to the road. The traffic noise usually exhibits high amplitudes in the recorded seismic profile, and it is a challenging task to remove it. In this article, we propose a workflow to attenuate seismic traffic noise using the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${l}_{p}$ </tex-math></inline-formula> -norm robust principal component analysis (RPCA). This method is implemented in the frequency domain, where the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${l}_{p}$ </tex-math></inline-formula> -norm RPCA is applied to each frequency slice and results in a low-rank approximation of seismic reflections. The alternating direction method of multipliers (ADMM) algorithm is included in the implementation for efficiency. The proposed workflow is demonstrated on a 3-D field shot gather contaminated by complex traffic noise. The performance indicates that our method can remove strong traffic noise effectively and, in turn, accentuate the seismic reflections with balanced amplitudes.