Unsupervised 3-D random noise attenuation using deep skip autoencoder
Effective random noise attenuation is critical for subsequent processing of seismic data,
such as velocity analysis, migration, and inversion. Thus, the removal of seismic random …
such as velocity analysis, migration, and inversion. Thus, the removal of seismic random …
Deep learning seismic random noise attenuation via improved residual convolutional neural network
Because a high signal-to-noise ratio (SNR) is beneficial to the subsequent processing
procedures, the noise attenuation is important. We propose an adaptive random noise …
procedures, the noise attenuation is important. We propose an adaptive random noise …
Denoising of distributed acoustic sensing data using supervised deep learning
Distributed acoustic sensing (DAS) is an emerging technology for acquiring seismic data
due to its high-density and low-cost advantages. Because of the harsh acquisition …
due to its high-density and low-cost advantages. Because of the harsh acquisition …
Unsupervised deep learning for ground roll and scattered noise attenuation
The attenuation of coherent noise in land seismic data, specifically ground roll and near-
surface scattered energy, remains a longstanding challenge. Although recent advances in …
surface scattered energy, remains a longstanding challenge. Although recent advances in …
Intelligent deblending of seismic data based on U-Net and transfer learning
B Wang, J Li, J Luo, Y Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The blended acquisition allows multiple sources to be simulated simultaneously in a narrow
time interval, which can improve the acquisition efficiency and reduce the acquisition cost …
time interval, which can improve the acquisition efficiency and reduce the acquisition cost …
Self-supervised Multistep Seismic Data Deblending
X Chen, B Wang - Surveys in Geophysics, 2024 - Springer
The potential of blended seismic acquisition to improve acquisition efficiency and cut
acquisition costs is still open, particularly with efficient deblending algorithms to provide …
acquisition costs is still open, particularly with efficient deblending algorithms to provide …
Deblending and recovery of incomplete blended data via MultiResUnet
B Wang, J Li, D Han, J Song - Surveys in Geophysics, 2022 - Springer
Blended acquisition is still open to improve the efficiency of seismic data acquisition.
Deblending is an essential procedure to provide separated gathers for subsequent …
Deblending is an essential procedure to provide separated gathers for subsequent …
Deep nonlocal regularizer: A self-supervised learning method for 3d seismic denoising
Noise suppression for seismic data can meliorate the quality of many subsequent
geophysical tasks. In this work, we propose a novel self-supervised learning method, the …
geophysical tasks. In this work, we propose a novel self-supervised learning method, the …
Seismic random noise attenuation based on M-ResUNet
J Gao, Z Li, M Zhang - IEEE Transactions on Geoscience and …, 2023 - ieeexplore.ieee.org
Suppressing random noise and improving the signal-to-noise ratio of seismic data are of
great significance for subsequent high-precision processing. As one of the most popular …
great significance for subsequent high-precision processing. As one of the most popular …
Deblending of seismic data based on neural network trained in the CSG
K Wang, T Hu - IEEE Transactions on Geoscience and Remote …, 2021 - ieeexplore.ieee.org
The simultaneous source acquisition method, which excites multiple sources in a narrow
time interval, can greatly improve the efficiency of seismic data acquisition and provide good …
time interval, can greatly improve the efficiency of seismic data acquisition and provide good …