Accelerated Signal-and-Noise Orthogonalization
文献类型：期刊论文
| 作者 | Huang, Guangtan4; Zhang, Dong3; Chen, Wei2; Chen, Yangkang1 |
| 刊名 | IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
 |
| 出版日期 | 2022 |
| 卷号 | 60页码:9 |
| 关键词 | Noise reduction Acceleration Imaging Inverse problems Smoothing methods Oils Mathematical model Denoising local orthogonalization seismic data processing |
| ISSN号 | 0196-2892 |
| DOI | 10.1109/TGRS.2021.3054839 |
| 英文摘要 | The local signal-to-noise orthogonalization algorithm has been widely used in the community of seismic processing and imaging. It helps orthogonalize the signal-and-noise components in an elegant way so that the noise does not contain the signal leakage in seismic denoising. The traditional local signal-to-noise orthogonalization is based on solving a highly underdetermined, ill-posed inverse problem with local smoothness constraint. Due to the inversion nature, the local orthogonalization method requires a large number of iterations and thus is computationally demanding in large-scale applications. Here, we proposed a much accelerated signal-and-noise orthogonalization method, where we design an efficient way for calculating the orthogonalization weight. When new samples are involved in the calculation, we calculate the orthogonalization weight of the new samples by connecting them with the calculated weights of the previous samples. The orthogonalization weight needs to be smoothed and scaled after all samples have been processed to make the resulted orthogonalization weight smooth across the seismic data and match the amplitude level of the initially suppressed noise. In this way, we avoid iterations when calculating the orthogonalization weight. We apply the proposed method to several synthetic and field data examples, have a benchmark comparison with state-of-the-art algorithms, and demonstrate its much accelerated efficiency compared with the traditional local signal-and-noise orthogonalization. |
| 资助项目 | Zhejiang University ; National Natural Science Foundation of China[41804140] ; Open Fund of Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education[PI2018-02] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000728266600100 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/30956]  |
| 专题 | 中科院武汉岩土力学所 |
| 通讯作者 | Chen, Wei |
| 作者单位 | 1.Zhejiang Univ, Sch Earth Sci, Key Lab Geosci Big Data & Deep Resource Zhejiang, Hangzhou 310027, Peoples R China 2.Yangtze Univ, Key Lab Explorat Technol Oil & Gas Resources, Minist Educ, Wuhan 430100, Peoples R China 3.Delft Univ Technol, Dept Imaging Phys, NL-2628 CJ Delft, Netherlands 4.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Guangtan,Zhang, Dong,Chen, Wei,et al. Accelerated Signal-and-Noise Orthogonalization[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2022,60:9. |
| APA | Huang, Guangtan,Zhang, Dong,Chen, Wei,&Chen, Yangkang.(2022).Accelerated Signal-and-Noise Orthogonalization.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,60,9. |
| MLA | Huang, Guangtan,et al."Accelerated Signal-and-Noise Orthogonalization".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 60(2022):9. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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