Research on stratigraphic correlation method based on dynamic time bending distance algorithm

Zhenfei Li
{"title":"Research on stratigraphic correlation method based on dynamic time bending distance algorithm","authors":"Zhenfei Li","doi":"10.54097/ije.v1i1.3427","DOIUrl":null,"url":null,"abstract":"Stratigraphic division and correlation are the basis of oil and gas exploration. With the increasing degree of oilfield encryption, the traditional artificial comparison method is difficult to meet the actual needs of oilfield development, and the comparison method of different people is also subjective and different problems, it is difficult to form a more scientific quantitative method. In this paper, the dynamic time-bending distance algorithm of curve similarity algorithm is used for stratigraphic correlation, and two constraint methods based on beam constraint and parallelogram constraint are used to improve the dynamic time-bending distance algorithm. The application of dynamic time-bending distance algorithm in formation correlation is verified by using the real logging data of Nan8 area of Daqing Oilfield. The experimental results show that the dynamic time-bending distance algorithm improves the efficiency of formation correlation and achieves a good formation correlation effect on the real logging curve.","PeriodicalId":14093,"journal":{"name":"International journal of energy science","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of energy science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.54097/ije.v1i1.3427","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Stratigraphic division and correlation are the basis of oil and gas exploration. With the increasing degree of oilfield encryption, the traditional artificial comparison method is difficult to meet the actual needs of oilfield development, and the comparison method of different people is also subjective and different problems, it is difficult to form a more scientific quantitative method. In this paper, the dynamic time-bending distance algorithm of curve similarity algorithm is used for stratigraphic correlation, and two constraint methods based on beam constraint and parallelogram constraint are used to improve the dynamic time-bending distance algorithm. The application of dynamic time-bending distance algorithm in formation correlation is verified by using the real logging data of Nan8 area of Daqing Oilfield. The experimental results show that the dynamic time-bending distance algorithm improves the efficiency of formation correlation and achieves a good formation correlation effect on the real logging curve.
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
基于动态时间弯曲距离算法的地层对比方法研究
地层划分与对比是油气勘探的基础。随着油田加密程度的不断提高,传统的人工比较法已难以满足油田开发的实际需要,而且不同人的比较法也存在主观和不同的问题,难以形成较为科学的定量方法。本文采用曲线相似算法中的动态时间弯曲距离算法进行地层对比,并采用基于梁约束和平行四边形约束的两种约束方法对动态时间弯曲距离算法进行改进。利用大庆油田南8区实际测井资料,验证了动态时间弯曲距离算法在地层关联中的应用。实验结果表明,动态时间弯曲距离算法提高了地层关联效率,在真实测井曲线上取得了较好的地层关联效果。
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
Research on Optimization Model of Heat Exchange Fin Structure in Energy Storage System Analysis of Influencing Factors of Water Flooding Productivity in Tight Oil Reservoirs Analysis and Method Overview of Photovoltaic Cell MPPT Technology Study on High-resolution Remote Sensing Image Scene Classification Using Transfer Learning Research on Structural Design and Optimization of Battery Thermal Management System
×
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