Results 11 to 20 of about 4,442 (191)
Residual Learning of Cycle-GAN for Seismic Data Denoising
Random noise attenuation has always been an indispensable step in the seismic exploration workflow. The quality of the results directly affects the results of subsequent inversion and migration imaging. This paper proposes a cycle-GAN denoising framework
Wenda Li, Jian Wang
doaj +4 more sources
Seismic Data Denoising Based on Sparse and Low-Rank Regularization
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
doaj +3 more sources
A Denoising Method for Seismic Data Based on SVD and Deep Learning
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
doaj +3 more sources
Multi-scale dual-path attention network for seismic background noise attenuation [PDF]
The background noise in seismic records severely interferes with the extraction of effective reflection events, particularly in complex exploration environments such as deserts.
Li Han, Dongyan Wang, Feng Li
doaj +2 more sources
Diffusion Model for DAS-VSP Data Denoising [PDF]
Distributed acoustic sensing (DAS) has emerged as a transformational technology for seismic data acquisition. However, noise remains a major impediment, necessitating advanced denoising techniques. This study pioneers the application of diffusion models,
Donglin Zhu +3 more
doaj +2 more sources
Seismic data denoising based on attention dual dilated CNN [PDF]
Seismic data denoising is essential for accurate seismic-exploration data processing and interpretation. Traditional noise suppression methods often result in the loss of critical signals, affecting subsurface structure characterization.
Haixia Hu +6 more
doaj +2 more sources
Curvelet Denoising of 4D Seismic [PDF]
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
openaire +1 more source
A U-Net Based Multi-Scale Deformable Convolution Network for Seismic Random Noise Suppression
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source

