A convolutional neural network approach for ghost removal-Reference-Cited by-同舟云学术

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A convolutional neural network approach for ghost removal

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

Almuteri Khalid¹,Sava Paul¹

Affiliation:

1. Center for Wave Phenomena, Colorado School of Mines

Publisher

Society of Exploration Geophysicists

Link

https://library.seg.org/doi/pdf/10.1190/segam2021-3584059.1

Reference24 articles.

1. Wavenumber‐based filtering of marine point‐source data

2. Broadband seismic over/under sources and their designature-deghosting

3. Low-frequency seismic deghosting

4. The footsteps of the receiver ghost in the f-k domain

5. Wave equation receiver deghosting: A provocative example

Cited by 5 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. Attenuating free‐surface multiples and ghost reflection from seismic data using a trace‐by‐trace convolutional neural network approach;Geophysical Prospecting;2023-11-29

2. Deghosting dual‐component streamer data using demigration‐based supervised learning;Geophysical Prospecting;2023-08-10

3. Seismic deghosting using convolutional neural networks;GEOPHYSICS;2023-03-29

4. Source and receiver deghosting by demigration‐based supervised learning;Geophysical Prospecting;2022-08-24

5. Marchenko focusing using convolutional neural networks;Second International Meeting for Applied Geoscience & Energy;2022-08-15

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