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Widely linear denoising of multicomponent seismic data
Geophysical Prospecting, 2019ABSTRACTSeismic data processing is a challenging task, especially when dealing with vector‐valued datasets. These data are characterized by correlated components, where different levels of uncorrelated random noise corrupt each one of the components.
Breno Bahia, Mauricio D. Sacchi
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Mask-Guided Model for Seismic Data Denoising
IEEE Geoscience and Remote Sensing Letters, 2022Ziyi Fang, Hongbo Lin, Xinyu Xu
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NS2NS: Self-Learning for Seismic Image Denoising
IEEE Transactions on Geoscience and Remote Sensing, 2022Naihao Liu +6 more
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Nonlocal Total Variation Denoising of Seismic Data
Proceedings, 2013Seismic denoising can be considered to be a total variation minimization problem. Nonlocal total variation (NLTV) denoising is one of the best denoising models and is widely used in image processing. Combined with Split-Bregman algorithm, the computational efficiency of NLTV regularization can be improved, making it able to handle large data set.
S. Shang, L.G. Han
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Application of Wavelet Analysis in Denoising Seismic Data
Applied Mechanics and Materials, 2014The random noise is the kind of noise with wide frequency band in seismic data detected by the optical acceleration sensors. The noises influence and destroy the useful signal of the seismic information. There are a lot of methods to remove noise and one of the standard methods to remove the noise of the signal was the fast Fourier transform (FFT ...
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Denoising and Storage in Seismic Reverse Time Migration
Chinese Journal of Geophysics, 2010AbstractPre‐stack reverse time migration (RTM) is a very useful tool for seismic imaging. It has, however, some problems such as highly intensive computation cost, low‐frequency imaging noise and massy memory demand. The problem of time consuming for calculation can be solved by GPU/CPU collaborative computation. This paper focuses on suppressing noise
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Similarity-Informed Self-Learning and Its Application on Seismic Image Denoising
IEEE Transactions on Geoscience and Remote Sensing, 2022Naihao Liu, Jinghuai Gao, Shaojie Chang
exaly
Multiscale Spatial Attention Network for Seismic Data Denoising
IEEE Transactions on Geoscience and Remote Sensing, 2022Xintong Dong +4 more
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SAPD: Self-Attention Progressive Seismic Data Denoising
2023 International Conference on Machine Learning and Cybernetics (ICMLC), 2023Ke Wang 0049 +3 more
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Robust reduced-rank seismic denoising
SEG Technical Program Expanded Abstracts 2013, 2013Ke Chen, Mauricio D. Sacchi
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