Seismic Data Denoising Based on Sparse and Low-Rank Regularization [PDF]
Energies, 2020 Seismic denoising is a core task of seismic data processing. The quality of a denoising result directly affects data analysis, inversion, imaging and other applications.
Shu Li +4 more
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A Denoising Method for Seismic Data Based on SVD and Deep Learning [PDF]
Applied Sciences, 2022 When reconstructing seismic data, the traditional singular value decomposition (SVD) denoising method has the challenge of difficult rank selection. Therefore, we propose a seismic data denoising method that combines SVD and deep learning. In this method,
Guoli Ji, Chao Wang
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Curvelet Denoising of 4D Seismic [PDF]
66th EAGE Conference & Exhibition, 2004 With burgeoning world demand and a limited rate of discovery of new reserves, there is increasing impetus upon the industry to optimize recovery from already existing fields. 4D, or time-lapse, seismic imaging is an emerging technology that holds great promise to better monitor and optimise reservoir production. The basic idea behind 4D seismic is that
Bayreuther, Moritz +2 more
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Joint denoising method of seismic velocity signal and acceleration signals based on independent component analysis [PDF]
Frontiers in Earth Science, 2023 The signal-to-noise ratio (SNR) of seismic data is the key to seismic data processing, and it also directly affects interpretation of seismic data results.
Guangde Zhang +7 more
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Denoising Method for Seismic Co-Band Noise Based on a U-Net Network Combined with a Residual Dense Block [PDF]
Applied Sciences, 2023 To address the problem of waveform distortion in the existing seismic signal denoising method when removing co-band noise, further improving the signal-to-noise ratio (SNR) of seismic signals and enhancing their quality, this paper designs a seismic co ...
Jianxian Cai +5 more
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Application of 2D Variational Mode Decomposition Method in Seismic Signal Denoising [PDF]
Elektronika ir ElektrotechnikaSeismic data are typical nonlinear and nonstationary data. In the acquisition and processing of seismic data, many factors interfere with it. Seismic data contain both effective waves and random noises, seriously affecting the quality of seismic data and
Chao Liu +4 more
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Imaging Domain Seismic Denoising Based on Conditional Generative Adversarial Networks (CGANs) [PDF]
Energies, 2022 A high-resolution seismic image is the key factor for helping geophysicists and geologists to recognize the geological structures below the subsurface.
Hao Zhang, Wenlei Wang
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Seismic denoising using curvelet analysis [PDF]
Physica A: Statistical Mechanics and its Applications, 2012 AbstractA curvelet is a new and effective spectral transform, that allows sparse representations of complex data. It has many applications in several fields, including denoising, wave propagation in disordered media and pattern recognition. This spectral technique is based on directional basis functions that represent objects having discontinuities ...
Oliveira, M.S. +4 more
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Research on Seismic Signal Denoising Model Based on DnCNN Network [PDF]
Applied SciencesAddressing the noise in seismic signals, a prevalent challenge within seismic signal processing, has been the focus of extensive research. Conventional algorithms for seismic signal denoising often fall short due to their reliance on manually determined ...
Li Duan, Jianxian Cai, Li Wang, Yan Shi
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An EEMD-Based Denoising Method for Seismic Signal of High Arch Dam Combining Wavelet with Singular Spectrum Analysis [PDF]
Shock and Vibration, 2019 Due to complicated noise interference, seismic signals of high arch dam are of nonstationarity and a low signal-to-noise ratio (SNR) during acquisition process.
Bo Li +3 more
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