Wavefield Solutions from Machine Learned Functions that Approximately Satisfy the Wave Equation-Reference-Cited by-同舟云学术

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Wavefield Solutions from Machine Learned Functions that Approximately Satisfy the Wave Equation

Published:2020 Issue: Volume: Page:
ISSN:
Container-title:EAGE 2020 Annual Conference & Exhibition Online
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Author:

Alkhalifah T.,Song C.,Waheed U. Bin,Hao Q.

Publisher

European Association of Geoscientists & Engineers

Cited by 10 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. On cost-efficient parallel iterative solvers for 3D frequency-domain seismic multisource viscoelastic anisotropic wave modeling;GEOPHYSICS;2024-05-02

2. Fully Convolutional Network-Enhanced DeepONet-Based Surrogate of Predicting the Travel-Time Fields;IEEE Transactions on Geoscience and Remote Sensing;2024

3. Physics‐Informed Neural Networks for Elliptical‐Anisotropy Eikonal Tomography: Application to Data From the Northeastern Tibetan Plateau;Journal of Geophysical Research: Solid Earth;2023-12

4. Graphical neural networks based on physical information constraints for solving the eikonal equation;Journal of Geophysics and Engineering;2023-08-25

5. Ground-penetrating radar wavefield simulation via physics-informed neural network solver;GEOPHYSICS;2023-02-20

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