Band limited ridge regression deconvolution of vibroseis data

Toshifumi Matsuoka , Tad J Ulrych , Armando Lopes Farias
{"title":"Band limited ridge regression deconvolution of vibroseis data","authors":"Toshifumi Matsuoka ,&nbsp;Tad J Ulrych ,&nbsp;Armando Lopes Farias","doi":"10.1016/0016-7142(90)90002-A","DOIUrl":null,"url":null,"abstract":"<div><p>Owing to the band limited nature of seismic data, ridge regression plays an important role in the processing and particularly in the deconvolution of seismic sections. To improve the condition number of the autocovariance matrix a ride regression parameter (RRP) is added which is a small fraction of the zero-lag autocovariance value. As pointed out by Berkhout, the size of the RRP is important since it affects the phase of the residual wavelet. In a previous work, Matsuoka and Ulrych explored this property of the RRP by considering the effect of very large values of this parameter on the deconvolution of Vibroseis data. In this paper we briefly summarise our previous findings and extend the method by considering the effect of band limited ridge regression on the deconvolution of Vibroseis data. We call this approach BLRR deconvolution and we develop a theoretical justification for its use. We show that the use of BLRR is effective in the removal of not only short- and long-period multiples, but also in the deconvolution of phase shifted and attenuated wavelets. The latter result is of particular importance, since, as shown by Gibson and Larner, the conventional phase corrected deconvolution is not effective in low-<em>Q</em> environments. The determination of the value of the BLRR parameter in this work is accomplished by monitoring a modified form of the Varimax of the deconvolved trace. The use of the Varimax norm was suggested by Levy and Oldenburg as a measure of phase distortion, and we have found it to be of particular value in deconvolution studies.</p></div>","PeriodicalId":100579,"journal":{"name":"Geoexploration","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1990-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/0016-7142(90)90002-A","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoexploration","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/001671429090002A","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Owing to the band limited nature of seismic data, ridge regression plays an important role in the processing and particularly in the deconvolution of seismic sections. To improve the condition number of the autocovariance matrix a ride regression parameter (RRP) is added which is a small fraction of the zero-lag autocovariance value. As pointed out by Berkhout, the size of the RRP is important since it affects the phase of the residual wavelet. In a previous work, Matsuoka and Ulrych explored this property of the RRP by considering the effect of very large values of this parameter on the deconvolution of Vibroseis data. In this paper we briefly summarise our previous findings and extend the method by considering the effect of band limited ridge regression on the deconvolution of Vibroseis data. We call this approach BLRR deconvolution and we develop a theoretical justification for its use. We show that the use of BLRR is effective in the removal of not only short- and long-period multiples, but also in the deconvolution of phase shifted and attenuated wavelets. The latter result is of particular importance, since, as shown by Gibson and Larner, the conventional phase corrected deconvolution is not effective in low-Q environments. The determination of the value of the BLRR parameter in this work is accomplished by monitoring a modified form of the Varimax of the deconvolved trace. The use of the Varimax norm was suggested by Levy and Oldenburg as a measure of phase distortion, and we have found it to be of particular value in deconvolution studies.

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
可控震源数据的带限脊回归反褶积
由于地震资料的带限性质,脊回归在地震剖面的反褶积处理中起着重要的作用。为了改善自协方差矩阵的条件数,在自协方差矩阵中加入了一个相对于零滞后自协方差的小比例的平顺回归参数(RRP)。正如Berkhout所指出的,RRP的大小很重要,因为它影响残差小波的相位。在之前的工作中,Matsuoka和Ulrych通过考虑该参数非常大的值对可控震源数据反褶积的影响,探索了RRP的这一特性。在本文中,我们简要总结了我们以前的研究成果,并通过考虑带限脊回归对可控震源数据反褶积的影响来扩展该方法。我们称这种方法为BLRR反卷积,并为其使用提供了理论依据。我们表明,使用BLRR不仅可以有效地去除短周期和长周期的倍数,而且可以有效地去除相移和衰减小波的反褶积。后一个结果特别重要,因为正如Gibson和Larner所示,传统的相位校正反褶积在低q环境中是无效的。在这项工作中,BLRR参数值的确定是通过监测反卷积迹线的变差的修改形式来完成的。Levy和Oldenburg建议使用Varimax范数作为相位失真的度量,我们发现它在反褶积研究中具有特殊的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Introduction Numerical modeling of surface-to-borehole electromagnetic surveys for monitoring thermal enhanced oil recovery Algorithms for EOR imaging using crosshole seismic data: an experiment with scale model data Cross-borehole TEM for enhanced oil recovery: a model study Application of the cross-borehole direct-current resistivity technique for EOR process monitoring—a feasibility study
×
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