Seismic Velocity Inversion Based on Physically Constrained Neural Networks-Reference-Cited by-同舟云学术

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Seismic Velocity Inversion Based on Physically Constrained Neural Networks

Published:2024 Issue: Volume:62 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Zhang Yan¹^ORCID,Meng Decong¹,Zhou Yifan¹,Song Liwei²^ORCID,Dong Hongli³^ORCID

Affiliation:

1. School of Computer and Information Technology, Northeast Petroleum University, Daqing, China

2. School of Physics and Electronic Engineering, Northeast Petroleum University, Daqing, China

3. Institute of Artificial Intelligence Energy Research, Northeast Petroleum University, Daqing, China

Funder

Natural Science Foundation of Heilongjiang Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10354519/10345591.pdf?arnumber=10345591

Reference52 articles.

1. Enhancing low-wavenumber components of full-waveform inversion using an improved wavefield decomposition method in the time-space domain

2. A robust source-independent misfit function for time domain waveform inversion based on normalized convolved wavefield

3. Two-step velocity inversion using trans-dimensional tomography and elastic FWI

4. From tomography to full-waveform inversion with a single objective function

5. Inversion on Reflected Seismic Wave

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. STUGAN: An Integrated Swin Transformer-Based Generative Adversarial Networks for Seismic Data Reconstruction and Denoising;IEEE Transactions on Geoscience and Remote Sensing;2024

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