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天然气地球科学

• 天然气勘探 • 上一篇    

同步挤压小波变换在储层预测中的应用

李斌1,2，乐友喜3，温明明1,2   

  1. 1.中国地质调查局广州海洋地质调查局，广东 广州 510075；
    2.国土资源部海底矿产资源重点实验室，广东 广州 510075；
    3.中国石油大学（华东）地球科学与技术学院，山东 青岛 266580
  • 收稿日期:2016-10-20 修回日期:2016-12-08 出版日期:2017-02-10 发布日期:2017-02-10
  • 作者简介:李斌（1989-），男，湖北孝感人，助理工程师，硕士，主要从事海洋地质勘查技术方法研究. E-mail：binli0710@163.com.
  • 基金资助:

    国家重点研发计划重点专项项目“近海底高精度水合物探测技术”（编号：2016YFC0303900）资助.

Reservoir predication based on synchrosqueezing wavelet transform

Li Bin1,2，Yue You-xi3，Wen Ming-ming1,2   

  1. 1.Guangzhou Marine Geological Survey,China Geological Survey,Guangzhou 510075,China;
    2.Key Laboratory of Marine Mineral Resources,Ministry of Land and Resources,Guangzhou 510075,China；
    3.School of Geosciences,China University of Petroleum,Qingdao 266580,China
  • Received:2016-10-20 Revised:2016-12-08 Online:2017-02-10 Published:2017-02-10

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摘要：

随着勘探难度的增加，小波变换时频分辨率的精度已经难以达到实际勘探目标的要求，这就需要探索分辨率更高的时频分析方法。同步挤压小波变换（Synchrosqueezing Wavelet Transform-SWT）通过对小波变换的复系数谱在频率方向上进行压缩重组，得到比小波变换更高的时频分辨率，同时还具有可逆性和一定的抗噪性。通过模拟信号的测试结果表明，同步挤压小波变换在刻画信号的时频特征方面精度更高、准确性更好；而在实际地震资料的分析当中，利用同步挤压小波变换对含气薄储层的地震数据进行分频处理，其低频处出现明显异常，而且频率越低异常越明显，有效地预测出储层的存在。

关键词: 同步挤压小波变换, 时频分辨率, 分频处理, 低频异常, 储层预测

Abstract:

With the increasing difficulty of exploration,the accuracy of the time-frequency resolution of wavelet transform has been difficult to meet the requirements of the actual exploration targets,which needs to explore a higher resolution time-frequency analysis method.The synchrosqueezing wavelet transform (SWT) can obtain time-frequency resolution better than the wavelet transform by squeezing and reconstructing complex coefficient spectra in frequency direction.And it also has reversibility and anti-noise property.The simulation results show that the synchrosqueezing wavelet transform has better accuracy in characterizing the time-frequency characteristics of the signal.And in the analysis of the actual seismic data,the frequency division process of the synchrosqueezing wavelet transform is applied to process the thin gas-bearing reservoir seismic data.Where the low frequency appears obvious anomalies,and the lower frequency is,the more obvious anomalies are.So the reservoir is predicted effectively.

Key words: Synchrosqueezing wavelet transform, Time-frequency resolution, Frequency division processing, Low-frequency anomaly, Reservoir prediction

中图分类号: 

  • TE132.1+4

[1]Partyka G,Gridley J.Interpretational applications of spectral decomposition in reservoir characterization[J].The Leading Edge,1999,18(3):353-360.
[2]Gao Jianhu,Yong Xueshan,Liu Hong.Study of reservoir prediction technology in frequency domain[J].Natural Gas Geoscience,2007,18(6):808-812.[高建虎,雍学善,刘洪.频率域储层预测技术研究[J].天然气地球科学,2007,18(6):808-812.]
[3][KG*5/6]Tian Renfei,Yang Chunfeng,Hu Yu,et al.Thin lithologic reservoir identification with spectral decomposition techniques[J].Natural Gas Geoscience,2015,26(2):360-366.[田仁飞,杨春峰,胡宇,等.识别岩性油藏薄储集层的谱分解技术[J].天然气地球科学,2015,26(2):360-366.]
[4]Lu Yi,Wu Xuesong,Shi Qianru,et.al.Applicability of seismic response to thin-interbed and acceptable condition of spectral decomposition[J].Natural Gas Geoscience,2010,21(4):660-665.[卢异,吴雪松,石倩茹,等.薄互层地震响应及分频技术的适用性分析[J].天然气地球科学,2010,21(4):660-665.]
[5]Daubechies I,Lu J,Wu H T.Synchrosqueezed wavelet transform:An empirical mode decomposition like tool[J].Applied and Computational Harmonic Analysis,2011,30(2):243-261.
[6]Meignen S,Oberlin T.A new algorithm for multicomponent signals analysis based on synchrosqueezing:with an application to signal sampling and denoising[J].IEEE Transactions on Signal Processing,2012,60(11):5787-5798.
[7]Herrera R-H,Han Jiajun,Mirko van dar Baan.Applications of the synchrosqueezing transform in seismic time-frequency analysis[J].Geophysics,2013,79(3):55-64.
[8]Shang Shuai,Han Liguo.Seismic data analysis using synchrosqueezing wavelet transform[C]//Expanded Abstracts of 83th SEG Annual International Meeting,2013:4330-4334.
[9]Shang Shuai,Han Liguo,Hu Wei,et al.Applied research of synchrosqueezing wavelet transform in seismic spectraldecomposition method[J].Geophysical Prospecting for Petroleum,2015,54(1):51-55.[尚帅,韩立国,胡玮,等.压缩小波变换地震谱分解方法应用研究[J].石油物探,2015,54(1):51-55.]
[10]Daubechies I,Maes S.A nonlinear squeezing of the continuous wavelet transform based on auditory nerve models[C]//Wavelets in Medicine and Biology.CRC Press,1996:527-546.
[11]Thakur G,Brevdo E,Fuckar N S,et al.The synchrosqueezing algorithm for time-varying spectral analysis:Robustness properties and new paleoclimate applications[J].Signal Processing,2013,93(5):1079-1094.
[12]Sinha S,Routh P S,Anno P D,et al.Spectral decomposition of seismic data with continuous wavelet transform[J].Geophysics,2005,70(6):19-25.
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