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Wang, Kunxi, Hu, Tianyue, Zhao, Bangliu, Wang, Shangxu (2023) Surface-related multiple attenuation based on a self-supervised deep neural network with local wavefield characteristics. GEOPHYSICS, 88 (5) Society of Exploration Geophysicists. doi:10.1190/geo2022-0599.1

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Reference TypeJournal (article/letter/editorial)
TitleSurface-related multiple attenuation based on a self-supervised deep neural network with local wavefield characteristics
JournalGEOPHYSICS
AuthorsWang, KunxiAuthor
Hu, TianyueAuthor
Zhao, BangliuAuthor
Wang, ShangxuAuthor
Year2023 (September 1)Volume88
Issue5
PublisherSociety of Exploration Geophysicists
DOIdoi:10.1190/geo2022-0599.1Search in ResearchGate
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Mindat Ref. ID16612863Long-form Identifiermindat:1:5:16612863:5
GUID0
Full ReferenceWang, Kunxi, Hu, Tianyue, Zhao, Bangliu, Wang, Shangxu (2023) Surface-related multiple attenuation based on a self-supervised deep neural network with local wavefield characteristics. GEOPHYSICS, 88 (5) Society of Exploration Geophysicists. doi:10.1190/geo2022-0599.1
Plain TextWang, Kunxi, Hu, Tianyue, Zhao, Bangliu, Wang, Shangxu (2023) Surface-related multiple attenuation based on a self-supervised deep neural network with local wavefield characteristics. GEOPHYSICS, 88 (5) Society of Exploration Geophysicists. doi:10.1190/geo2022-0599.1
In(2023, September) Geophysics Vol. 88 (5) Society of Exploration Geophysicists

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Wang, Kunxi, Hu, Tianyue, Wang, Shangxu (2023) Iterative deblending using unsupervised learning with double-deep neural networks. GEOPHYSICS, 88 (3) doi:10.1190/geo2022-0299.1
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Wang, Kunxi, Hu, Tianyue, Zhao, Bangliu, Wang, Shangxu (2023) Random Noise Attenuation Using an Unsupervised Deep Neural Network Method Based on Local Orthogonalization and Ensemble Learning. IEEE Transactions on Geoscience and Remote Sensing, 61. Institute of Electrical and Electronics Engineers (IEEE) 1-11 doi:10.1109/tgrs.2023.3295355
Wang, Kunxi, Hu, Tianyue, Zhao, Bangliu (2023) Seismic Internal Multiple Attenuation Based on Unsupervised Deep Learning With a Local Orthogonalization Constraint. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-9 doi:10.1109/tgrs.2023.3307750
Wang, Kunxi, Hu, Tianyue, Zhao, Bangliu, Wang, Shangxu (2023) An Unsupervised Learning Method to Suppress Seismic Internal Multiples Based on Adaptive Virtual Events and Joint Constraints of Multiple Deep Neural Networks. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-18 doi:10.1109/tgrs.2023.3243106
Wang, Kunxi, Hu, Tianyue, Zhao, Bangliu (2022) An Unsupervised Deep Neural Network Approach Based on Ensemble Learning to Suppress Seismic Surface-Related Multiples. IEEE Transactions on Geoscience and Remote Sensing, 60. 1-14 doi:10.1109/tgrs.2022.3225809
Wang, Kunxi, Hu, Tianyue, Zhao, Bangliu, Wang, Shangxu (2023) An Unsupervised Deep Learning Method for Direct Seismic Deblending in Shot Domain. IEEE Transactions on Geoscience and Remote Sensing, 61. 1-12 doi:10.1109/tgrs.2023.3298054
Li, Jingshuang, Yang, Dinghui, Wang, Zhenrong, Liu, Landong (2023) Attenuation-compensated reverse time migration based on the stereo-modeling operator. GEOPHYSICS, 88 (5) Society of Exploration Geophysicists. doi:10.1190/geo2022-0433.1
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Zheng, Yikang, Wang, Yibo (2023) Ground-penetrating radar wavefield simulation via physics-informed neural network solver. GEOPHYSICS, 88 (2) doi:10.1190/geo2022-0293.1
 
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