新疆石油地质 ›› 2002, Vol. 23 ›› Issue (6): 513-515.

• 油气勘探 • 上一篇    下一篇

小波包变换叠前地震信号研究

王振国, 周熙襄, 钟本善   

  1. 成都理工大学信息工程学院,四川 成都 610059
  • 收稿日期:2002-01-08 出版日期:2002-12-01 发布日期:2020-08-12
  • 作者简介:王振国(1965-),男,江苏武进人,在读博士生,地球物理勘探。联系电话:0312-3683440

Study on Pre-Stacking Seismic Signals for Wavelet Packet

WANG Zhen-guo, ZHOU Xi-xiang, ZHONG Ben-shan   

  • Received:2002-01-08 Online:2002-12-01 Published:2020-08-12
  • About author:WANG Zhen-guo (1965-), Male, Doctor Candidate, Geophysical Prospecting, Information Engineering Institute, Chengdu Scientific University, Chengdu, Sichuan 610059, China

摘要: 叠前地震资料是多种波的复合体,为了提取有效波,必需消除主要的干扰波,如面波、高频随机干扰波。一般的去噪方法有:一维滤波、滤波、变换、f-x预测等,但它们都侧重于考虑某一方面的单 -特性或某种条件假设,这些方法具有一定的局限性。小波包变换是一种时频分析的方法,它对地震资料进行时频精细划分优于小波变换,与传统的Fourier变换相比,它能刻画出具有相同频率的有效波与干扰波在时间-空间域的分布。经过小波包对叠前资料分解,可分离出面波、高频随机干扰等,然后再经过小波包重构,可有效地剔除干扰,且对有效波的伤害较少。经实际资料验证,小波包变换,确实是一个十分有效的去噪方法。

关键词: 小波包, 变换, 地震信号, 叠前分析

Abstract: There are usually different noises in seismic data before stacking. In order to pick-up effectual wave, we must remove noise waves such as surface wave and random noise with high frequency. The normal methods include: 1D filter, f-x filter, t-p transform, f-x prediction, etc. However, these methods have limitations that they only particular emphasis on a single characteristic of surface wave or are based on some hypothesis. Wavelet packet is a time-frequency analytical method, and can be better of dividing the seismic data in detail than wavelet transform. It can describe the distribution of effectual wave and noise wave in time-space field at same frequency,comparing with traditional Fourier transform. By decomposing seismic data before stacking with wavelet packet, separate surface-wave and random noise of high frequency from seismic data. After processing wavelet packet reconstruction, we can eliminate noise-wave and allow fewer damage of effectual wave. Through validating real data, wavelet packet is good for removing noise.

Key words: wavelet packet, transformation, seismic signal, prestack analysis

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