地球物理学进展 ›› 2020, Vol. 35 ›› Issue (1): 166-173.doi: 10.6038/pg2020CC0462

• 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

基于VMD算法在地震数据时频分析中的应用

龙丹1, 牛聪3, 周怀来1,2, 黄饶3, 周慰1   

  1. 1. 成都理工大学地球物理学院,成都 610059;
    2. “油气藏地质及开发工程”国家重点实验室,成都 610059;;
    3. 中海油研究总院,北京 100028
  • 收稿日期:2019-05-09 修回日期:2019-12-18 出版日期:2020-02-20 发布日期:2020-03-18
  • 作者简介:龙丹,女,1993年生,在读硕士研究生,主要研究方向为油气地球物理探勘探.E-mail:dd508dd@163.com
  • 基金资助:
    十三五国家重大专项子题(2016ZX05026-001-005)资助.

Application of VMD algorithm in time-frequency analysis of seismic data

LONG Dan1, NIU Cong3, ZHOU Huai-lai1,2, HUANG Rao3, ZHOU Wei1   

  1. 1. College of Geophysics, Chengdu University of Technology, Chengdu 610059, China;
    2. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu Sichuan University of Technology, Chengdu 610059, China;
    3. CNOOC Research Institute, Beijing 100028, China
  • Received:2019-05-09 Revised:2019-12-18 Online:2020-02-20 Published:2020-03-18

摘要: 受新开发的变分模态分解(VMD)的启发,本文引入一种基于VMD的时频分析方法来分析地震数据.VMD的原理是将信号分解成具有一定中心频率的模态分量,通过这些分量来重构原始信号.这种分解方式可以降低各个模态中的残余噪声,同时进一步减少冗余的模态,很好的克服了模态混叠问题.此外,VMD是一种自适应信号分解技术,它可以非递归地将多分量信号分解为几个准正交固有模态函数,与EMD及其推广(如EEMD,CEEMD)相比,有坚实的数学基础.将VMD方法与CEEMD方法进行比较,对合成数据进行测试显示了基于VMD的时频分析方法具有更好的时频聚焦性,同时对实际数据处理也表明该方法具有突出地质特征和地层信息的潜力.

关键词: 变分模态分解(VMD), 时频分析, 中心频率, 模态混叠

Abstract: Inspired by the newly developed Variational Mode Decomposition (VMD), this paper introduces a time-frequency analysis method based on VMD to analyze seismic data. The principle of VMD is to decompose the signal into modal components with a certain center frequency, through modal components we can reconstruct the original signal. The decomposition method can reduce the residual noise in each mode, and it can further decrease the redundant mode, which overcomes the mode-mixing problem well. Moreover, VMD is an adaptive signal decomposition technique, which can nonrecursively decompose a multicomponent signal into several quasi-orthogonal intrinsic mode functions. This new tool, in contrast to Empirical Mode Decomposition (EMD) and its variations, such as EEMD, CEEMD, is based on a solid mathematical foundation. Comparing the VMD with the CEEMD and testing the synthesized data shows that the time-frequency analysis method based on VMD has better time-frequency focusing. Simultaneously, application on seismic data processing also shows the potential of the proposed approach in highlighting geologic characteristics and stratigraphic information effectively.

Key words: Variational Mode Decomposition (VMD), Time-frequency, Analysis center frequency, The mode-mixing

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