Desert Seismic Low-Frequency Noise Attenuation Based on Approximate-Message-Passing-Based Complex Diffusion

• Published in: IEEE geoscience and remote sensing letters Vol. 17; no. 3; pp. 524 - 528
• Main Authors: Ma, Haitao, Wang, Yuzhuo, Li, Yue
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximate message passing; Approximation algorithms; Attenuation; complex diffusion; desert seismic noise attenuation; Deserts; Diffusion; Directivity; Exploration; Frequency dependence; Geological surveys; Geology; Information processing; LF noise; low-frequency noise; Mathematical model; Message passing; Noise; Noise measurement; Noise reduction; Seismic activity; Seismic data; Seismic exploration; Seismological data; Signal processing; Signal to noise ratio; Surface water waves; Surface waves
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2019.2924248

High-quality seismic exploration data are the basis of geological exploration. However, due to the increasingly complex environment in the exploration area, the signal-to-noise ratio (SNR) of seismic data is getting lower and lower. Eliminating noise is the most direct mean to improve the SNR and quality of seismic data. The Tarim Basin with a desert surface in China is rich in energy, but due to the variability of surface conditions, the desert noise has nonstationary, nonlinear, spatial directivity, low frequency, and other characteristics, which make noise attenuation very difficult. Aiming at this problem, we develop an extension of complex diffusion filter, namely approximate-message-passing-based complex diffusion, which is used to eliminate noise in desert seismic exploration data and enhance effective signals. Compared with the traditional complex diffusion, this letter adds a noise estimate in its diffusion processing, which improves the algorithm's ability to eliminate desert noise. The experimental results of synthetic and field seismic data show that the proposed method is more effective than other methods. Not only it can remove the noise and surface wave in the desert seismic record but also can preserve the effective signal. Therefore, we believe that the proposed method can provide a new idea for desert seismic signal processing.