用于叠后地震数据 Q 因子补偿的组合去噪方法

IF 2.2 3区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Journal of Applied Geophysics Pub Date : 2024-08-22 DOI:10.1016/j.jappgeo.2024.105500
Peng Zhang , Qinghan Wang , Yang Liu , Changle Chen
{"title":"用于叠后地震数据 Q 因子补偿的组合去噪方法","authors":"Peng Zhang ,&nbsp;Qinghan Wang ,&nbsp;Yang Liu ,&nbsp;Changle Chen","doi":"10.1016/j.jappgeo.2024.105500","DOIUrl":null,"url":null,"abstract":"<div><p>Attenuation is a main factor limiting the resolution of seismic data. Earth works as a low-pass filter, which has strong attenuation of the high-frequency data. The loss of high-frequency energy can be compensated by the inverse Q filtering strategy. However, this method will also increase the energy of random noise which limits its application. The inverse Q filtering algorithm also needs the Q-factor as the input parameter, which is not easy to obtain. In this paper, we proposed a three-stage process to correct the attenuation of poststack data. In the first stage, a robust structure-oriented filtering is applied to remove random noise while protecting the structure information to avoid high-frequency noise burst. In the second stage, the local centroid frequency shift (LCFS) method is used to estimate the Q factor along the seismic trace. This method combined shaping regularization and centroid frequency shift (CFS) method to improve the robustness and accuracy of Q estimation to some extent. The final stage is to apply a stable inverse Q-filtering. Synthetic and field data examples demonstrate that time-varying Q-value can be accurately estimated by using the local centroid frequency shift (LCFS) method, and the proposed workflow can compensate the attenuation without bursting of high-frequency random noise.</p></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"229 ","pages":"Article 105500"},"PeriodicalIF":2.2000,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A combined denoising method for Q-factor compensation of poststack seismic data\",\"authors\":\"Peng Zhang ,&nbsp;Qinghan Wang ,&nbsp;Yang Liu ,&nbsp;Changle Chen\",\"doi\":\"10.1016/j.jappgeo.2024.105500\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Attenuation is a main factor limiting the resolution of seismic data. Earth works as a low-pass filter, which has strong attenuation of the high-frequency data. The loss of high-frequency energy can be compensated by the inverse Q filtering strategy. However, this method will also increase the energy of random noise which limits its application. The inverse Q filtering algorithm also needs the Q-factor as the input parameter, which is not easy to obtain. In this paper, we proposed a three-stage process to correct the attenuation of poststack data. In the first stage, a robust structure-oriented filtering is applied to remove random noise while protecting the structure information to avoid high-frequency noise burst. In the second stage, the local centroid frequency shift (LCFS) method is used to estimate the Q factor along the seismic trace. This method combined shaping regularization and centroid frequency shift (CFS) method to improve the robustness and accuracy of Q estimation to some extent. The final stage is to apply a stable inverse Q-filtering. Synthetic and field data examples demonstrate that time-varying Q-value can be accurately estimated by using the local centroid frequency shift (LCFS) method, and the proposed workflow can compensate the attenuation without bursting of high-frequency random noise.</p></div>\",\"PeriodicalId\":54882,\"journal\":{\"name\":\"Journal of Applied Geophysics\",\"volume\":\"229 \",\"pages\":\"Article 105500\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Geophysics\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0926985124002167\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Geophysics","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926985124002167","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

衰减是限制地震数据分辨率的一个主要因素。地球就像一个低通滤波器,对高频数据有很强的衰减作用。反 Q 滤波策略可以弥补高频能量的损失。不过,这种方法也会增加随机噪声的能量,从而限制了其应用范围。反 Q 滤波算法还需要 Q 因子作为输入参数,而这一参数并不容易获得。在本文中,我们提出了一种分三阶段修正叠后数据衰减的方法。在第一阶段,采用面向结构的稳健滤波来去除随机噪声,同时保护结构信息,避免高频噪声猝发。第二阶段,采用局部中心频率偏移(LCFS)方法估算地震道沿线的 Q 因子。该方法结合了整形正则化和中心频率偏移(CFS)方法,在一定程度上提高了Q值估计的鲁棒性和准确性。最后阶段是应用稳定的反Q滤波。合成和现场数据实例表明,使用局部中心频率偏移(LCFS)方法可以准确估计时变 Q 值,而且所提出的工作流程可以补偿衰减,而不会出现高频随机噪声猝发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A combined denoising method for Q-factor compensation of poststack seismic data

Attenuation is a main factor limiting the resolution of seismic data. Earth works as a low-pass filter, which has strong attenuation of the high-frequency data. The loss of high-frequency energy can be compensated by the inverse Q filtering strategy. However, this method will also increase the energy of random noise which limits its application. The inverse Q filtering algorithm also needs the Q-factor as the input parameter, which is not easy to obtain. In this paper, we proposed a three-stage process to correct the attenuation of poststack data. In the first stage, a robust structure-oriented filtering is applied to remove random noise while protecting the structure information to avoid high-frequency noise burst. In the second stage, the local centroid frequency shift (LCFS) method is used to estimate the Q factor along the seismic trace. This method combined shaping regularization and centroid frequency shift (CFS) method to improve the robustness and accuracy of Q estimation to some extent. The final stage is to apply a stable inverse Q-filtering. Synthetic and field data examples demonstrate that time-varying Q-value can be accurately estimated by using the local centroid frequency shift (LCFS) method, and the proposed workflow can compensate the attenuation without bursting of high-frequency random noise.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Applied Geophysics
Journal of Applied Geophysics 地学-地球科学综合
CiteScore
3.60
自引率
10.00%
发文量
274
审稿时长
4 months
期刊介绍: The Journal of Applied Geophysics with its key objective of responding to pertinent and timely needs, places particular emphasis on methodological developments and innovative applications of geophysical techniques for addressing environmental, engineering, and hydrological problems. Related topical research in exploration geophysics and in soil and rock physics is also covered by the Journal of Applied Geophysics.
期刊最新文献
Magnetic diagnosis model for heavy metal pollution in beach sediments of Qingdao, China An improved goal-oriented adaptive finite-element method for 3-D direct current resistivity anisotropic forward modeling using nested tetrahedra Deep learning-based geophysical joint inversion using partial channel drop method Advanced predictive modelling of electrical resistivity for geotechnical and geo-environmental applications using machine learning techniques Editorial Board
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1