推进砂岩储层可压缩性预测:相关性驱动方法

Q1 Earth and Planetary Sciences Petroleum Research Pub Date : 2024-06-01 DOI:10.1016/j.ptlrs.2024.01.006
Tarek Ganat , Meftah Hrairi , Amr Badawy , Vahid Khosravi , Mohammed Abdalla
{"title":"推进砂岩储层可压缩性预测:相关性驱动方法","authors":"Tarek Ganat ,&nbsp;Meftah Hrairi ,&nbsp;Amr Badawy ,&nbsp;Vahid Khosravi ,&nbsp;Mohammed Abdalla","doi":"10.1016/j.ptlrs.2024.01.006","DOIUrl":null,"url":null,"abstract":"<div><p>This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir rocks. The study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility, with the most optimal fit of results based on a cubic polynomial model. The accuracy of the calculations was validated through comparison with actual data using root mean square method, and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone reservoirs. In this study, the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore oilfields. Accordingly, variations in compressibility with net overburden pressure over the course of the field's lifespan have been examined. The results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent variables. The proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures, with an average error of 2.5% compared to 5–10% for laboratory measurements. The approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.</p></div>","PeriodicalId":19756,"journal":{"name":"Petroleum Research","volume":"9 2","pages":"Pages 273-279"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2096249524000061/pdfft?md5=b2aa0024892ab824ed2d7e109c077872&pid=1-s2.0-S2096249524000061-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Advancing sandstone reservoir compressibility prediction: A correlation-driven methodology\",\"authors\":\"Tarek Ganat ,&nbsp;Meftah Hrairi ,&nbsp;Amr Badawy ,&nbsp;Vahid Khosravi ,&nbsp;Mohammed Abdalla\",\"doi\":\"10.1016/j.ptlrs.2024.01.006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir rocks. The study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility, with the most optimal fit of results based on a cubic polynomial model. The accuracy of the calculations was validated through comparison with actual data using root mean square method, and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone reservoirs. In this study, the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore oilfields. Accordingly, variations in compressibility with net overburden pressure over the course of the field's lifespan have been examined. The results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent variables. The proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures, with an average error of 2.5% compared to 5–10% for laboratory measurements. The approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.</p></div>\",\"PeriodicalId\":19756,\"journal\":{\"name\":\"Petroleum Research\",\"volume\":\"9 2\",\"pages\":\"Pages 273-279\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2096249524000061/pdfft?md5=b2aa0024892ab824ed2d7e109c077872&pid=1-s2.0-S2096249524000061-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Petroleum Research\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2096249524000061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Petroleum Research","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2096249524000061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 0

摘要

本研究提出了一种基于相关性的方法来预测砂岩储层岩石的可压缩性。研究提出了一个新的经验方程矩阵,可显著提高孔隙体积可压缩性的测量精度,其最佳拟合结果基于三次多项式模型。利用均方根法与实际数据进行比较,验证了计算的准确性,所建议的相关性显著提高了砂岩储层岩石压缩性的精确预测。本研究收集的数据来源于东亚海上油田的固结和非固结砂岩。因此,研究了油田生命周期内可压缩性随覆盖层净压力的变化情况。结果表明,回归分析可用于建立自变量和因变量之间的联系网络。与传统的实验室方法相比,针对固结和非固结砂岩提出的相关方法在精确计算岩石可压缩性方面有显著改进,平均误差为 2.5%,而实验室测量误差为 5-10%。本研究的方法提供了一种成本效益高、时间效率高的替代方法,可显著提高油气行业砂岩储层的整体性能。
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
Advancing sandstone reservoir compressibility prediction: A correlation-driven methodology

This study presents a correlation-based approach for predicting the compressibility of sandstone reservoir rocks. The study proposes a matrix of new empirical equations that significantly improve the precision of measuring the pore volume compressibility, with the most optimal fit of results based on a cubic polynomial model. The accuracy of the calculations was validated through comparison with actual data using root mean square method, and the suggested correlations significantly enhance the precise prediction of rock compressibility in sandstone reservoirs. In this study, the source of data collection is consolidated and unconsolidated sandstone from East Asia offshore oilfields. Accordingly, variations in compressibility with net overburden pressure over the course of the field's lifespan have been examined. The results demonstrate the application of regression analysis in establishing a network of linkages between independent and dependent variables. The proposed correlations for consolidated and unconsolidated sandstones offer a remarkable improvement in the accurate calculation of rock compressibility compared to traditional laboratory procedures, with an average error of 2.5% compared to 5–10% for laboratory measurements. The approach of this study offers a cost-effective and time-efficient alternative to remarkedly enhance the overall performance of sandstone reservoirs in the oil and gas industry.

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
Petroleum Research
Petroleum Research Earth and Planetary Sciences-Geology
CiteScore
7.10
自引率
0.00%
发文量
90
审稿时长
35 weeks
期刊最新文献
Applicability of deep neural networks for lithofacies classification from conventional well logs: An integrated approach Investigation of a solid particle deposition velocity in drag reducing fluids with salinity Use of graphs to assess well safety in drilling projects and during operations by identification of available barrier elements and consolidation of barrier envelopes Sedimentary microfacies of Member 5 of Xujiahe Formation in the Dongfengchang area, Sichuan Basin Research on physical explosion crater model of high-pressure natural gas pipeline
×
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