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Three-Dimensional Seismic Data Reconstruction Based on Fully Connected Tensor Network Decomposition

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成果类型:
期刊论文
作者:
Xu, Yuejiao;Fu, Lihua;Niu, Xiao;Chen, Xingrong;Zhang, Meng
通讯作者:
Fu, LH
作者机构:
[Fu, Lihua; Chen, Xingrong; Xu, Yuejiao; Niu, Xiao] China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China.
[Zhang, Meng] Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China.
通讯机构:
[Fu, LH ] C
China Univ Geosci, Sch Math & Phys, Wuhan 430074, Peoples R China.
语种:
英文
关键词:
Tensors;Three-dimensional displays;Matrix decomposition;Correlation;Singular value decomposition;Frequency-domain analysis;Spectral analysis;3-D seismic data reconstruction;fully connected tensor network (FCTN);Hankel tensor;low rank
期刊:
IEEE Transactions on Geoscience and Remote Sensing
ISSN:
0196-2892
年:
2023
卷:
61
页码:
1-11
基金类别:
10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 42274172)
机构署名:
本校为其他机构
院系归属:
计算机学院
摘要:
Rank-reduction approaches assume that seismic data in the frequency–space domain is of low-rank after a specific pretransformation. The presence of noise or missing traces will increase the rank; therefore, seismic data can be denoised and recovered via rank-reduction techniques. The iterative weighted projection onto convex sets (POCS) framework can be used for noise attenuation and data reconstruction simultaneously. Multichannel singular spectrum analysis (MSSA) is a classic 3-D seismic data reconstruction algorithm that rearranges the temp...

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