Abstract:Time-frequency analysis is one of the important methods for thin layer identification with seismic data. Conventional time-frequency analysis methods are affected by fixed time window, window function and other factors. To this end, continuous wavelet transform(CWT), based on tunable factor Gabor wavelet(TFGW), TFGW-CWT for short, is used to process seismic data. In the TFGW-CWT method, TFGW transform is performed, and then the minimum absolute value projection method is employed to combine the continuous wavelet coefficients of each tunable factor to reduce the cross interference of adjacent frequencies and improve the local time-frequency resolution. Furthermore, non-negative matrix factorization(NMF) is conducted to reduce the dimensionality of the time-frequency data body to obtain a low-rank characteristic data structure relation volume. This reduces the data redundancy of high-dimensional space, highlights the high-frequency information, and achieves the purpose of improving the resolution of seismic data. The results of simulation record and actual data processing confirm the validity of the proposed method, which can provide a new technique for thin layer detection.
赵邦六,董世泰,曾忠,等.中国石油"十三·五"物探技术进展及"十四·五"发展方向思考[J].中国石油勘探,2021,26(1):108-120.ZHAO Bangliu,DONG Shitai,ZENG Zhong,et al.Geophysical prospecting technology progress of PetroChina in the 13th Five-Year Plan period and development direction consideration in the 14th Five-Year Plan period[J].China Petroleum Exploration,2021,26(1):108-120.
[2]
张军华,王庆峰,张晓辉,等.薄层和薄互层叠后地震解释关键技术综述[J].石油物探,2017,56(4):459-471.ZHANG Junhua,WANG Qingfeng,ZHANG Xiaohui,et al.Poststack interpretation key techniques for thin layer and thin interbed reservoirs[J].Geophysical Prospecting for Petroleum,2017,56(4):459-471.
[3]
武迪,宋维琪,刘军,等.变分模态分解与包络导数算子结合的时频分析方法及溶洞储层预测[J].石油地球物理勘探,2021,56(2):346-355.WU Di,SONG Weiqi,LIU Jun,et al.Seismic time-frequency analysis based on VMD and envelope derivative operator for fractured-vuggy reservoir prediction[J].Oil Geophysical Prospecting,2021,56(2):346-355.
[4]
李思源,徐天吉.基于Wigner-Ville分布与Chrip-Z变换的高分辨时频分析方法[J].石油地球物理勘探,2022,57(1):168-175,211.LI Siyuan,XU Tianji.A new high-resolution time-frequency analysis method based on Wigner-Ville distribution and Chrip-Z transform[J].Oil Geophysical Prospecting,2022,57(1):168-175,211.
[5]
尚平萍,李鹏,杨安琪,等.基于CEEMDAN的地震信号高分辨率时频分析方法[J].石油物探,2019,58(4):547-554.SHANG Pingping,LI Peng,YANG Anqi,et al.Seismic high-resolution time-frequency analysis based on CEEMDAN[J].Geophysical Prospecting for Petro-leum,2019,58(4):547-554.
[6]
郭爱华,路鹏飞,余波,等.利用Shearlet变换提高叠后地震资料分辨率[J].石油地球物理勘探,2021,56(5):992-1000.GUO Aihua,LU Pengfei,YU Bo,et al.Improving post-stack seismic data resolution based on Shearlet transform[J].Oil Geophysical Prospecting,2021,56(5):992-1000.
[7]
江雨濛,曹思远,陈思远,等.基于二阶自适应同步挤压S变换的时变子波提取方法[J].石油物探,2021,60(5):721-731.JIANG Yumeng,CAO Siyuan,CHEN Siyuan,et al.Time-varying wavelet estimation method based on second-order adaptive synchro-squeezing S transform[J].Geophysical Prospecting for Petroleum,2021,60(5):721-731.
[8]
杨子鹏,宋维琪,刘军,等.联合广义S变换和压缩感知提高地震资料分辨率[J].地球物理学进展,2021,36(5):2119-2127.YANG Zipeng,SONG Weiqi,LIU Jun,et al.Combine generalized S transform with compressed sensing to improve the resolution of seismic data[J].Progress in Geophysics,2021,36(5):2119-2127.
[9]
纪永祯,张渝悦,朱立华,等.基于SBL-WVD的地震高分辨率时频分析[J].石油物探,2020,59(1):80-86.JI Yongzhen,ZHANG Yuyue,ZHU Lihua,et al.High-resolution seismic time-frequency analysis based on sparse Bayesian learning combined with Wigner-Ville distribution[J].Geophysical Prospecting for Petroleum,2020,59(1):80-86.
[10]
黄昱丞,郑晓东,栾奕,等.地震信号线性与非线性时频分析方法对比[J].石油地球物理勘探,2018,53(5):975-989.HUANG Yucheng,ZHENG Xiaodong,LUAN Yi,et al.Comparison of linear and nonlinear time-frequency analysis on seismic signals[J].Oil Geophysical Prospecting,2018,53(5):975-989.
[11]
HONG J C,KIM Y Y,LEE H C,et al.Damage detection using the Lipschitz exponent estimated by the wavelet transform:applications to vibration modes of a beam[J].International Journal of Solids and Structures,2002,39(7):1803-1816.
HE C,ZHENG Y F,AHALT S C.Object tracking using the Gabor wavelet transform and the golden section algorithm[J].IEEE Transactions on Multimedia,2002,4(4):528-538.
[14]
马志霞,孙赞东.Gabor-Morlet小波变换分频技术及其在碳酸盐岩储层预测中的应用[J].石油物探,2010,49(1):42-45.MA Zhixia,SUN Zandong.Spectral decomposition technique based on Gabor-Morlet wavelet transform and its application to carbonate reservoir prediction[J].Geophy-sical Prospecting for Petroleum,2010,49(1):42-45.
[15]
ZHANG X,LIU Z W,WANG J X,et al.Time-frequency analysis for bearing fault diagnosis using multiple Q-factor Gabor wavelets[J].ISA Transactions,2019,87:225-234.
[16]
FARGE M.Wavelet transforms and their applications to turbulence[J].Annual Review of Fluid Mechanics,1992,24(1):395-457.
[17]
DAUBECHIES I.Ten Lectures on Wavelets[M].Society for Industrial and Applied Mathematics,Philadelphia,1992.
[18]
MENA-CHALCO J P,CARRER H,ZANA Y,et al.Identification of protein coding regions using the mo-dified Gabor-wavelet transform[J].IEEE/ACM Tran-sactions on Computational Biology and Bioinforma-tics,2008,5(2):198-207.
[19]
NOH H Y,ASCE S M,NAIR K K,et al.Use of wavelet-based damage-sensitive features for structural damage diagnosis using strong motion data[J].Journal of Structural Engineering,2011,137(10):1215-1228.
[20]
成谷,张宝金.Morlet小波匹配追踪方法的时频原子参数分析[J].地球物理学进展,2019,34(6):2247-2255.CHENG Gu,ZHANG Baojin.Analysis on parameters of time-frequency atoms in matching pursuit based on Morlet wavelet[J].Progress in Geophysics,2019,34(6):2247-2255.
[21]
SELESNICK I W.Wavelet transform with tunable Q-factor[J].IEEE Transactions on Signal Processing,2011,59(8):3560-3575.
[22]
REMY-JARDIN M,REMY J,GOSSELIN B,et al.Sliding thin slab,minimum intensity projection technique in the diagnosis of emphysema:histopathologic-CT correlation[J].Radiology,1996,200(3):665-671.
[23]
熊松龄,曾庆宁,龙超,等.NMF的有监督算法在瞬变电磁信号降噪中的应用[J].石油物探,2021,60(3):421-429.XIONG Songling,ZENG Qingning,LONG Chao,et al.Application of supervised algorithm of NMF in noise reduction of transient electromagnetic signal[J].Geophysical Prospecting for Petroleum,2021,60(3):421-429.
[24]
LEE D D,SEUNG H S.Algorithms for non-negative matrix factorization[J]. Advances in Neural Information Processing Systems,2000,13(6):556-562.