Noise types and their attenuation in towed marine seismic: A tutorial

V Hlebnikov, T Elboth, V Vinje, LJ Gelius - Geophysics, 2021 - library.seg.org
The presence of noise in towed marine seismic data is a long-standing problem. The various
types of noise present in marine seismic records are never truly random. Instead, seismic …

Trace-wise coherent noise suppression via a self-supervised blind-trace deep-learning scheme

S Liu, C Birnie, T Alkhalifah - Geophysics, 2023 - library.seg.org
Seismic data denoising via supervised deep learning is effective and popular but requires
noise-free labels, which are rarely available. Blind-spot networks circumvent this …

Unsupervised deep learning with higher-order total-variation regularization for multidimensional seismic data reconstruction

TA Larsen Greiner, JE Lie, O Kolbjørnsen… - Geophysics, 2022 - library.seg.org
In 3D marine seismic acquisition, the seismic wavefield is not sampled uniformly in the
spatial directions. This leads to a seismic wavefield consisting of irregularly and sparsely …

Unsupervised erratic seismic noise attenuation with robust deep convolutional autoencoders

F Qian, W Guo, Z Liu, H Yu, G Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Erratic seismic noise, following a (known or unknown) non-Gaussian distribution, poses a
formidable challenge to conventional methods of random noise attenuation. Many erratic …

Ground truth-free 3-D seismic random noise attenuation via deep tensor convolutional neural networks in the time-frequency domain

F Qian, Z Liu, Y Wang, Y Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The inherent challenge of 3-D seismic noise attenuation is determining how to uncover high-
dimensional concise structures that only exist in true signals to eliminate random noise. The …

Unsupervised seismic facies classification using deep convolutional autoencoder

V Puzyrev, C Elders - Geophysics, 2022 - library.seg.org
With the increased size and complexity of seismic surveys, manual labeling of seismic facies
has become a significant challenge. Application of automatic methods for seismic facies …

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 …

Unsupervised intense VSP coupling noise suppression with iterative robust deep learning

F Qian, H Hua, Y Wen, J Zong… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Due to the poorly coupled geophones present in boreholes, vertical seismic profiling (VSP)
data are known to suffer from intense coupling noise, which causes severe VSP image …

Seismic data reconstruction based on a multicascade self-guided network

X Dong, C Wei, T Zhong, M Cheng, S Dong, F Li - Geophysics, 2024 - library.seg.org
Due to inherent limitations in data acquisition, seismic data reconstruction is an important
procedure to recover missing data or improve observation density. Many conventional …

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 …