地球物理学进展 ›› 2018, Vol. 33 ›› Issue (6): 2498-2506.doi: 10.6038/pg2018BB0374

• 应用地球物理学Ⅰ(油气及金属矿产地球物理勘探) • 上一篇    下一篇

同步挤压小波变换在储层预测中的应用研究

乐友喜1,2,蔡俊雄1,2,*(),李斌3,曾勉1,2   

  1. 1. 中国石油大学(华东)地球科学与技术学院,山东青岛 266580
    2. 海洋国家实验室海洋矿产资源评价与探测技术功能实验室,山东青岛 266071
    3. 中国地质调查局广州海洋地质调查局,广州 510075
  • 收稿日期:2018-03-15 修回日期:2018-09-26 出版日期:2018-12-20 发布日期:2019-03-03
  • 通讯作者: 蔡俊雄 E-mail:992743065@qq.com
  • 作者简介:乐友喜,男,1966年生,博士,教授,硕士生导师,主要研究方向为地震信号分析和储层预测.(E-mail: yueyouxi@upc.edu.cn)

Application research of synchrosqueezing wavelet transform in the reservoir prediction

YUE You-xi1,2,CAI Jun-xiong1,2,*(),LI Bin3,ZENG Mian1,2   

  1. 1. School of Geosciences, China University of Petroleum (Huadong), Shandong Qingdao 266580, China
    2. Laboratory for Marine Mineral Resources, Qingdao National Laboratory for Marine Science and Technology, Shandong Qingdao 266071, China
    3. Guangzhou Marine Geological Survey, China Geological Survey, Guangzhou 510075, China;
  • Received:2018-03-15 Revised:2018-09-26 Online:2018-12-20 Published:2019-03-03
  • Contact: Jun-xiong CAI E-mail:992743065@qq.com

摘要:

地震信号是非平稳的,谱分解方法是研究非平稳信号性质的重要方法,由于常规谱分解方法无法同时获得高时间分辨率和高频率分辨率,已经无法满足现阶段高精度地震数据解释的要求,一种高时频分辨率的谱分解方法的提出迫在眉睫.由于同步挤压小波变换(SSWT)只在频率方向对小波变换后的系数进行压缩和重排,不仅提高了时频分辨率,还可以重构出原始信号.本文从SSWT基本原理出发,研究本方法的抗噪性和可逆性等基本性质,采用频率修正同步挤压小波变换(FMSSWT)算法有效减轻了瞬时频率变化率不为零的信号所存在的时频谱模糊现象.通过对模拟信号和实际地震资料分别采用连续小波变换(CWT)、三参数小波变换(TP)、S变换(ST)和同步挤压小波变换进行谱分解研究,验证了该方法的有效性和优越性.

关键词: 同步挤压小波变换, 谱分解, 谱重排, 时频分析, 时频分辨率

Abstract:

Seismic signals are non-stational, and spectral decomposition is an important method for studying the properties of non-stationary signals. Conventional spectrum decomposition methods can not simultaneously have high time-frequency resolution, which can not satisfy the requirement of high-precision seismic data interpretation at present. Therefore, a spectral decomposition method with high resolution in time and frequency domain is imminent. Since the wavelet coefficients of the wavelet transform are compressed and rearranged only in the frequency axis of the SSWT, it can improve the time-frequency resolution and can also reconstruct the signal. Based on the basic principle of the SSWT, the frequency modified synchrosqueezing wavelet transform algorithm was used to effectively reduce the time-frequency spectrum ambiguity when the variation rate of instantaneous frequency of the signal not equals to zero. The relevant properties such as anti-noise ability and invertibility were analyzed. Through the spectral decomposition of the analog signals and the actual seismic data by using Continuous Wavelet Transform(CWT), three parameter Wavelet Transform(TP), S Transform (ST)and the SSWT, the effectiveness and superiority of the SSWT with higher time-frequency resolution was verified.

Key words: synchrosqueezing wavelet transform, spectral decomposition, spectral rearrangement, time-frequency analysis, time-frequency resolution

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