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| Global Geology 2020 23 (4): 241-246 ISSN: 1673-9736 CN: 22-1371/P |
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| Seismic data denoising based on data-driven tight frame dictionary learning method |
| ZHENG Jialiang, WANG Deli, ZHANG Liang |
| College of Geo-Exploration Science and Technology, Jilin University, Changchun 130026, China |
| 收稿日期 2020-02-19 修回日期 2020-03-29 网络版发布日期 null |
参考文献 Aharon M, Elad M, Bruckstein A. 2006. K-SVD:an algorithm for designing overcomplete dictionaries for sparse representation. IEEE Transactions on Signal Processing, 54(11):4311.
Cai J F, Ji H, Shen Z, et al. 2014. Data-driven tight frame construction and image denoising. Applied and Computational Harmonic Analysis, 37(1):89-105.
Cao J, Shao A. 2017. Adaptive seismic random noise attenuation using curvelet transform//79th EAGE Conference and Exhibition 2017.
Cheng S J, Han L G, Yu J L, et al. 2018.Seismic data denoising based on improved K-SVD dictionary learning method. Global Geology, 37(2):627-635. (in Chinese with English abstract)
Chen Y K, Ma J W, Fomel S. 2016. Double-sparsity dictionary for seismic noise attenuation. Geophysics, 81(2):103-116.
Elad M, Aharon M. 2006. Image denoising via sparse and redundant representations over learned dictionaries. IEEE Transactions on Signal Processing, 15(12):3736-3745.
Herrmann F J, Hennenfent G. 2008. Non-parametric seismic data recovery with curvelet frames. Geophysical Journal International, 173(1):233-248.
Jiang Y D, Yang Q Y, He K, et al. 2012. Study on denoising method of surface micro seismic data based on curved wave transformation. Geophysical Prospecting for Petroleum, 51(6):620-624, 537. (in Chinese)
Nazari Siahsar M A, Gholtashi S, Kahoo A R, et al. 2017.Data-driven multitask sparse dictionary learning for noise attenuation of 3D seismic data. Geophysics, 82(6):V385-V396.
Schönemann P. 1966. A generalized solution of the orthogonal procrustes problem. Psychometrika, 31(1):1-10.
Shao J, Sun C Y, Tang J, et al. 2016. Wavelet domain sparse representation based on dictionary training for microseismic denoising. Oil Geophysical Prospecting, 51(2):254-260, 204-205. (in Chinese with English abstract)
Tang G, Ma J W, Yang H Z. 2012. Seismic data denoising based on learning-type overcomplete dictionaries. Applied Geophysics, 9(1):27-32, 114-115.
Yu S, Ma J, Zhang X, et al. 2015. Interpolation and denoising of high-dimensional seismic data by learning a tight frame. Geophysics, 80(5):V119-V132.
Yuan Y H, Wang Y B, Liu Y K, et al. 2013. Non quadratic curvelet transform and its application in seismic noise suppression. Chinese Journal of Geophysics, 56(3):1023-1032. (in Chinese with English abstract)
Zhang L. 2018. The research of seismic data interprolation and denoising via sparse representation:master's degree thesis. Changchun:Jilin University. (in Chinese with English abstract)
Zhang J H, Lu N, Tian L Y, et al. 2005. A comprehensive review of seismic data denoising methods. Oil Geophysical Prospecting, 40(Suppl. 1):121-127. (in Chinese with English abstract)
Zhu L, Liu E, McClellan J H. 2015.Seismic data denoising through multiscale and sparsity-promoting dictionary learning. Geophysics, 80(6):45-57.
Zou H, Hastie T, Tibshirani R. 2006. Sparse principal component analysis. Journal of Computational and Graphical Statistics, 15(2):265-286. |
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| 通讯作者: WANG Deli |
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