Deep learning based gather automated processing of migrated gathers for velocity model building-Reference-Cited by-同舟云学术

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Deep learning based gather automated processing of migrated gathers for velocity model building

Published:2021-09-01 Issue: Volume: Page:
ISSN:
Container-title:First International Meeting for Applied Geoscience & Energy Expanded Abstracts
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Author:

Vamaraju Janaki¹,Han Boran¹,Sutton Christian²,Liu Zaifeng²,Rynja Harry³,Vila Jeremy³

Affiliation:

1. Shell Global Solutions US Inc

2. Shell Exploration & Production Company

3. Shell International Exploration and Production Inc.

Publisher

Society of Exploration Geophysicists

Link

https://library.seg.org/doi/pdf/10.1190/segam2021-3583872.1

Reference31 articles.

1. Nonlinear 3D tomographic least-squares inversion of residual moveout in Kirchhoff prestack-depth-migration common-image gathers

2. Towards a Perceptual Loss

3. Random and coherent noise attenuation by empirical mode decomposition

4. Angle‐domain common‐image gathers for migration velocity analysis by wavefield‐continuation imaging

5. Signal enhancement-a composite property mapping algorithm

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. Machine learning-based residual moveout picking;Second International Meeting for Applied Geoscience & Energy;2022-08-15

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