Generative adversarial networks review in earthquake-related engineering fields
Within seismology, geology, civil and structural engineering, deep learning (DL), especially
via generative adversarial networks (GANs), represents an innovative, engaging, and …
via generative adversarial networks (GANs), represents an innovative, engaging, and …
Enhanced seismic attenuation compensation: integrating attention mechanisms with residual learning in neural networks
N Wang, Y Shi, J Ni, J Fang, B Yu - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The natural damping effect of the Earth typically results in significant distortion of seismic
waveforms, which greatly diminishes the precise of subsequent processes such as …
waveforms, which greatly diminishes the precise of subsequent processes such as …
A projection-onto-convex-sets network for 3D seismic data interpolation
Seismic data interpolation is an essential procedure in seismic data processing. However,
conventional interpolation methods may generate inaccurate results due to the simplicity of …
conventional interpolation methods may generate inaccurate results due to the simplicity of …
Seismic data compression: an overview
D Sebai, M Zouaoui, F Ghorbel - Multimedia Systems, 2024 - Springer
Seismic Data (SD) have been for several decades used as one of the main inspection and
exploration tools in various fields, particularly petroleum industry and geoscience. However …
exploration tools in various fields, particularly petroleum industry and geoscience. However …
Deep learning route to quantum materials: A domain agnostic analytic continuation mapping
In recent years, numerous techniques have been developed to improve our understanding
of the physical principles governing quantum materials. Such systems exhibit highly unusual …
of the physical principles governing quantum materials. Such systems exhibit highly unusual …
Reviving Legacy Seismic Data via Machine learning Technique Part 1: Expanding 3D Seismic Survey Coverage with Gated Convolution GAN
JW Lee, MJ Lee, DJ Min, Y Cho - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
We propose a novel machine learning-based seismic volume reconstruction method that
gradually extrapolates a seed volume by referring to line data external to the seed volume …
gradually extrapolates a seed volume by referring to line data external to the seed volume …
面向海域水合物精细刻画的地震勘探技术——耙缆式地震勘探
文鹏飞， 刘斌， 徐云霞， 薛花， 杨振， 李延， 孟大江… - 地球物理学进展, 2021 - dzkx.org
随着海域天然气水合物试采取得成功, 水合物产业化开发的计划也提上了日程.
水合物的开发需要更为精细的储层刻画及评价结果, 这就要求更高分辨率的地震数据 …
水合物的开发需要更为精细的储层刻画及评价结果, 这就要求更高分辨率的地震数据 …
Seismic data interpolation by Shannon entropy-based shaping
W Huang - IEEE Transactions on Geoscience and Remote …, 2022 - ieeexplore.ieee.org
The undersampled seismic data may suffer from the degraded quality and pose negative
impacts on subsequent processing procedures. Seismic data interpolation is a cost-saving …
impacts on subsequent processing procedures. Seismic data interpolation is a cost-saving …
Deep attributes: innovative LSTM-based seismic attributes
Seismic attributes are derived measures from seismic data that help characterize subsurface
geological features and enhance the interpretation of subsurface structures: we propose to …
geological features and enhance the interpretation of subsurface structures: we propose to …
Deep learning realm for geophysics: Seismic acquisition, processing, interpretation, and inversion
P Lu - arXiv preprint arXiv:1909.06486, 2019 - arxiv.org
Applying deep-learning models to geophysical applications has attracted special attentions
during the past a couple of years. There are several papers published in this domain …
during the past a couple of years. There are several papers published in this domain …