Seismic Data Interpolation Based on Spectrally Normalized Generative Adversarial Network
Author:
Affiliation:
1. College of Geophysics, Chengdu University of Technology, Chengdu, China
2. Key Laboratory of Earth Exploration and Information Technology, Ministry of Education, Chengdu University of Technology, Chengdu, China
Funder
Guangdong Provincial Key Laboratory of Geophysical High-Resolution Imaging Technology
Natural Science Foundation Project of Sichuan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Earth and Planetary Sciences,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/36/10006360/10201923.pdf?arnumber=10201923
Reference33 articles.
1. The Curvelet Transform
2. An anti-aliasing POCS interpolation method for regularly undersampled seismic data using curvelet transform
3. Interpolation and denoising of high-dimensional seismic data by learning a tight frame
4. Curvelet reconstruction of non‐uniformly sampled seismic data using the linearized Bregman method
5. Seismic Data Interpolation Using Dual-Domain Conditional Generative Adversarial Networks
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. GNP-WGAN: Generative Nonlocal A Priori Augmented Wasserstein Generative Adversarial Networks for Seismic Data Reconstruction;IEEE Transactions on Geoscience and Remote Sensing;2024
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