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本文提出了一种基于自适应核时频表示的最佳滤波方法。通过理论模型验证了该方法的灵活性和在时频谱上的聚焦能力，用于实际叠前与叠后地震资料的处理也取得了极好的去噪效果。结果表明该方法可以同时提高地震资料的信噪比与分辨率，对地层岩性变化具有更高的识别精度，为后续高精度解释工作奠定了坚实基础。
Abstract：The existing common seismic data denoising methods based on time-frequency analysis generally have the disadvantages of cross term interference in time-frequency spectrum and unsatisfactory denoising method, because of influence by the window function. Therefore, an optimal filtering method based on adaptive kernel time-frequency representation is proposed to effectively overcome the above defects in order to improve the results of signal time-frequency analysis. This method improves the computational efficiency of adaptive time-frequency analysis and the resolution of signal time-frequency analysis. The flexibility and focusing ability of this method in time-frequency spectrum are verified by theoretical model. Through the results of the actual pre-stack and post-stack data processing, it is proved that this method can improve the signal-to-noise ratio and resolution of seismic data at the same time, realize the real amplitude preserving processing. Therefore, applying adaptive kernel time-frequency representation can lay a solid foundation for the follow-up high-precision interpretation.
[1] Liu N H,Gao J H,Zhang B,et al.Time-frequency analysis of seismic data using a three parameters S transform[J].IEEE Geoscience and Remote Sensing Letters,2018,15(1):142-146.
[2] Kodera K,Villedary C D,Gendrin R.A new method for the numerical analysis of non-stationary signals[J].Physics of the Earth & Planetary Interiors,1976,12(2-3):142-150.
[3] Morlet J,Arens G,Fourgeau E,et al.Wave propagation and sampling theory-Part Ⅰ:Complex signal and scattering in multilayered media[J].Geophysics,1982,47(2):203-221.
[4] Stockwell R G,Mansinha L,Lowe R P.Localization of the complex spectrum:The S transform[J].IEEE Transactions on Signal Processing,1996,44(4):998-1001.
[5] Pinnegar C R,Mansinha L.The S-transform with windows of arbitrary and varying shape[J].Geophysics,2003,68(1):381-385.
[6] Radad M,Gholami A,Siahkoohi H R.S-transform with maximum energy concentration:Application to non-stationary seismic deconvolution[J].Journal of Applied Geophysics,2015,118:155-166.
[7] Daubechies I,Lu J F,Wu H T.Synchrosqueezed wavelet transforms:An empirical mode decomposition-like tool[J].Applied & Computational Harmonic Analysis,2011,30(2):243-261.
[8] 黄忠来，张建中.同步挤压S变换[J].中国科学：信息科学，2016,46(5):643-650.Huang Z L,Zhang J Z.Synchrosqueezing S-transform[J].Scientia Sinica Informationis,2016,46(5):643-650.
[9] 张建中，刘晗，黄忠来，等.基于同步挤压变换的水合物储层地震信号时频分析[J].海洋地质前沿，2015,31(6):23-29.Zhang J Z,Liu H,Huang Z L,et al.A synchrosqueezing transform based time-frequency analysis on seismic signals of hydrate reservoirs[J].Marine Geology Frontiers,2015,31(6):23-29.
[10] 高静怀，陈文超，李幼铭，等.广义S变换与薄互层地震响应分析[J].地球物理学报，2003,46(4):526-532.Gao J H,Chen W C,Li Y M,et al.Generalized S transform and seismic response analysis of thin interbeds[J].Chinese Journal of Geophysics,2003,46(4):526-532.
[11] 李斌.同步挤压小波变换及其在薄互层中的应用[D].青岛：中国石油大学(华东),2021.Li B.Synchrosqueezing Wavelet Transform and Its Application on Thin Interben[D].Qingdao:China University of Petroleum (East China),2021.
[12] Wigner E P.On the Quantum Correction for Thermodynamic Equilibrium[J].Physical Review,1931,40(40):749-759.
[13] 韩利.高分辨率全谱分解方法研究[D].长春：吉林大学，2013.Han L.Research on the Methods of High-resolution Full Spectrum Decomposition[D].Changchun:Jilin University,2013.
[14] Cohen L.Time frequency analysis:theory and application[J].Englewood Cliffs:Prentice-Hall,1995,778:299.
[15] Baraniuk R G,Jones D L.Signal-dependent time-frequency analysis using a radially Gaussian kernel[J].Signal Processing,1993,32(3):263-284.
[16] Jones D L,Baraniuk R G.An adaptive optimal-kernel time-frequency representation[J].IEEE Transaction on Signal Processing,1995,43(10):2361-2371.
[17] 岳龙，刘怀山，徐秀刚.自适应核时频分析方法的改进及应用[J].物探化探计算技术，2017,39(1):44-51.Yue L,Liu H S,Xu X G.Improvement of adaptive kernel time-frequency analysis and its application[J].Computing Techniques for Geophysical and Geochemical Exploration,2017,39(1):44-51.
[18] 韩鹤威.时频分析技术在薄层反演中的应用[D].北京：中国地质大学，2021.Han H W.Application of Time-Frequency Analysis Technology in Thin Layer Inversion[D].Beijing,China University of Geosciences,2021.
[19] 马成英.时频属性提取方法及应用[D].青岛：中国海洋大学，2012.Ma C Y.Time-frequency Attributes Extraction Methods and Application[D].Qingdao:Ocean University of China,2012.
基本信息:
DOI：10.16441/j.cnki.hdxb.20220162
中图分类号:P631.44
引用信息:
[1]张洪茂,邢磊,刘怀山,等.基于自适应核时频分析的地震数据处理方法[J],2023,53(05):126-135.DOI:10.16441/j.cnki.hdxb.20220162.
基金信息:
国家自然科学基金项目(42276055,91958206);; 海底科学与探测技术教育部重点实验室开放基金项目(SGPT-20210-06);; 中央高校基础研究基金项目(202262008,202161013)资助~~