地球物理学进展 ›› 2020, Vol. 35 ›› Issue (2): 714-720.doi: 10.6038/pg2020DD0072

• 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

两种抗噪反Q滤波方法对比及应用

赵岩1,2, 毛宁波1,2   

  1. 1. 油气资源与勘探技术教育部重点实验室(长江大学),武汉 430100
    2. 长江大学地球物理与石油资源学院,武汉 430100
  • 收稿日期:2019-05-16 修回日期:2019-12-19 出版日期:2020-04-20 发布日期:2020-04-30
  • 作者简介:赵岩,男,1986年生,河南驻马店人,中国石油大学(北京)地球物理与信息工程学院博士毕业,讲师,现就职于长江大学地球物理与石油资源学院,主要从事地震资料处理方法研究. E-mail: changda.zhaoyan@126.com
  • 基金资助:
    油气资源与勘探技术教育部重点实验室(长江大学)开放基金资助项目(K2018-13);国家自然科学基金项目(41604094)

Comparison and application of two anti-noise inverse Q filtering methods

ZHAO Yan1,2, MAO Ning-bo1,2   

  1. 1. Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Ministry of Education, Wuhan 430100, China
    2. School of Geophysics and Oil Resources, Yangtze University, Wuhan 430100, China
  • Received:2019-05-16 Revised:2019-12-19 Online:2020-04-20 Published:2020-04-30

摘要:

本文就两种抗噪反Q滤波方法进行了讨论,其中对比了考虑时频域信噪比的反Q滤波方法和基于变稳定因子的反Q滤波方法.与稳定的反Q滤波方法相比,这两种方法可以抑制噪声,提高反Q滤波后地震数据的分辨率和信噪比.然而,它们基于不同的方法原理,并且在处理效果上存在一定的差异.为了探究反Q滤波方法抑制噪声的关键问题,回顾了方法的原理,对比和讨论这两种方法的差异,并通过理论模型数据和实际地震数据进行了比较.测试结果表明,反Q滤波方法抑制噪声的关键在于有效控制振幅补偿的频带范围.就算法而言,考虑时频域信噪比的反Q滤波方法可根据地震数据的信噪比水平选择不同的频带补偿范围,具有较强的灵活性,但需要先计算出地震数据的时频域信噪比;而基于变稳定因子的反Q滤波方法具有更加简单的算法,其振幅补偿规律本身即具有一定的噪声压制能力,避免了计算时频域信噪比.当选取合适的参数,二者的振幅补偿频带范围接近时,这两种抗噪反Q滤波方法可以得到相似的处理效果.

关键词: Q滤波, 抗噪声, 分辨率, 时频域信噪比, 变稳定因子

Abstract:

In this paper, the two anti-noise inverse Q filtering methods are discussed. The inverse Q filtering method considering Time-Frequency Domain Signal-to-Noise Ratio (TFSNR) and the inverse Q filtering method based on varying stabilization factor are compared. Compared with the stable inverse Q filtering method, these two methods can suppress noise and improve the resolution and Signal-to-Noise Ratio (SNR) of seismic data after inverse Q filtering. However, they are based on different methodological principles and there are some differences in the processing effect. In order to explore the key problems of inverse Q filtering method to suppress noise, the principle of the method is reviewed, and the differences between the two methods are compared and discussed, and compared by the theoretical model data and real seismic data. The test results show that the key to suppressing noise by the inverse Q filtering method is to effectively control the frequency band range of amplitude compensation. In terms of algorithms, the inverse Q filtering method considering TFSNR can select different frequency band compensation ranges according to the SNR level of the seismic data, and has strong flexibility, but the TFSNR of the seismic data needs to be calculated first. However, the inverse Q filtering method based on varying stabilization factor has a simpler algorithm and the amplitude compensation law has a certain noise suppression capability, also avoids calculating the TFSNR. When the appropriate parameters are selected and the amplitude compensation band ranges of the two are close, the two anti-noise inverse Q filtering methods can obtain similar processing effects.

Key words: Inverse Q filtering, Anti-noise, Resolution, Time-Frequency Domain Signal-to-Noise Ratio (TFSNR), Varying stabilization factor

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