Results 21 to 30 of about 672 (170)
A U-Net Based Multi-Scale Deformable Convolution Network for Seismic Random Noise Suppression
Remote Sensing, 2023 Seismic data processing plays a key role in the field of geophysics. The collected seismic data are inevitably contaminated by various types of noise, which makes the effective signals difficult to be accurately discriminated.
Haixia Zhao +3 more
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An Alternative Adaptive Method for Seismic Data Denoising and Interpolation [PDF]
Mathematical Problems in Engineering, 2020 Seismic data denoising and interpolation are generally essential steps for reflection processing and imaging workflow especially for the complex surface geologic conditions and the irregular acquisition field area. The rank-reduction method is a valid way for the attenuation of random noise and data interpolation by selecting the suitable threshold, i ...
Zilin Lu +6 more
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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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Frontiers in Earth Science, 2023 Convolutional Neural Network (CNN) is widely used in seismic data denoising due to its simplicity and effectiveness. However, traditional seismic denoising methods based on CNN ignore multi-scale features of seismic data in the wavelet domain.
Liangsheng He +5 more
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Research on Sparse Denoising of Strong Earthquakes Early Warning Based on MEMS Accelerometers
Micromachines, 2022 In view of the fact that the noise in the same frequency band as the useful signal in the MEMS acceleration sensor observation data cannot be effectively removed by traditional filtering methods, a denoising method for strong earthquake signals based on ...
Jiening Xia +5 more
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Remote Sensing, 2022 The noise attenuation of seismic data is an indispensable part of seismic data processing, directly impacting the following inversion and imaging. This paper focuses on two bottlenecks in the AI-based denoising method of seismic data: the destruction of ...
Wenda Li, Tianqi Wu, Hong Liu
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IEEE Access, 2022 Traditional denoising methods for seismic exploration data design a corresponding mathematical denoising model batch according to the different properties of different random noises, which is a tedious and time-consuming process.
Liang Guo +5 more
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Rank-constrained seismic data interpolation and denoising
Brazilian Journal of Geophysics, 2022 Rank-constrained seismic data interpolation methods have been used to cope with spatial sampling deficiencies, but some fundamental aspects are often neglected. Understanding their underlying features is the first step for developing new solutions to overcome existing limitations.
Quézia Cavalcante, Milton Porsani
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 In seismic data processing, denoising and reconstruction are the two steps for identification of resources in the earth subsurface layers. The seismic data quality is affected by random noise and interference during acquisition.
Lakshmi Kuruguntla +4 more
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Seismic random noise suppression using improved CycleGAN
Frontiers in Earth Science, 2023 Random noise adversely affects the signal-to-noise ratio of complex seismic signals in complex surface conditions and media. The primary challenges related to processing seismic data have always been reducing the random noise and increasing the signal-to-
Shimin Sun +8 more
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