利用递减趋势分析技术初步估算油田储量的非常规方法

Celestine A. Udie, F. Faithpraise, Agnes Anuka
{"title":"利用递减趋势分析技术初步估算油田储量的非常规方法","authors":"Celestine A. Udie, F. Faithpraise, Agnes Anuka","doi":"10.2118/207109-ms","DOIUrl":null,"url":null,"abstract":"\n Methods to estimate reserves, recovery factor and time are highlighted using uconventional method, to reduce the challenges in an oilfield development. General Information about reserves production estimation using long and short production data is collated. The collated data are plotted against time to build production decline curves. The curves are used to estimate the decline rate trends and constants. The decline constant is then used to predict reserves cumulative recovery. The rate trend is extrapolated to abandonment for estimation of reserves initially in place, recovery factor and the correspondent time. The reserves values are compared with field values for accuracy. It was observed that the result using data from long time production history accuracy was 99.98% while evaluation models built with data from short production history accuracy was 98.64%. The models are then adopted after validation. The validated curves are used to build the governing models which are finally used in estimating cumulative reserves recovery and initially in place. It is concluded that accurate reserves, recovery factor and time estimation challenges can be achieved/matched up using rate decline trend techniques.","PeriodicalId":10899,"journal":{"name":"Day 2 Tue, August 03, 2021","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unconventional Method of Estimating Oilfield Reserve Initially in Place Using Decline Trends Analyses Techniques\",\"authors\":\"Celestine A. Udie, F. Faithpraise, Agnes Anuka\",\"doi\":\"10.2118/207109-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Methods to estimate reserves, recovery factor and time are highlighted using uconventional method, to reduce the challenges in an oilfield development. General Information about reserves production estimation using long and short production data is collated. The collated data are plotted against time to build production decline curves. The curves are used to estimate the decline rate trends and constants. The decline constant is then used to predict reserves cumulative recovery. The rate trend is extrapolated to abandonment for estimation of reserves initially in place, recovery factor and the correspondent time. The reserves values are compared with field values for accuracy. It was observed that the result using data from long time production history accuracy was 99.98% while evaluation models built with data from short production history accuracy was 98.64%. The models are then adopted after validation. The validated curves are used to build the governing models which are finally used in estimating cumulative reserves recovery and initially in place. It is concluded that accurate reserves, recovery factor and time estimation challenges can be achieved/matched up using rate decline trend techniques.\",\"PeriodicalId\":10899,\"journal\":{\"name\":\"Day 2 Tue, August 03, 2021\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 2 Tue, August 03, 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/207109-ms\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, August 03, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/207109-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

重点介绍了利用非常规方法估算储量、采收率和时间的方法,以减少油田开发中的挑战。对利用长、短生产数据估计储量、产量的一般信息进行了整理。将整理后的数据按时间绘制成产量递减曲线。这些曲线用于估计下降速率趋势和常数。然后利用递减常数预测储量累积采收率。将速率趋势外推到弃井,以估计初始储量、采收率和相应的时间。为了准确性,将储量值与现场值进行比较。结果表明,利用长时间生产历史数据建立的评价模型准确率为99.98%,而利用短时间生产历史数据建立的评价模型准确率为98.64%。模型验证后采用。验证曲线用于建立控制模型,最终用于估计累积储量采收率和初始就位。结果表明,采用速率递减趋势技术可以实现准确的储量、采收率和时间估算。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unconventional Method of Estimating Oilfield Reserve Initially in Place Using Decline Trends Analyses Techniques
Methods to estimate reserves, recovery factor and time are highlighted using uconventional method, to reduce the challenges in an oilfield development. General Information about reserves production estimation using long and short production data is collated. The collated data are plotted against time to build production decline curves. The curves are used to estimate the decline rate trends and constants. The decline constant is then used to predict reserves cumulative recovery. The rate trend is extrapolated to abandonment for estimation of reserves initially in place, recovery factor and the correspondent time. The reserves values are compared with field values for accuracy. It was observed that the result using data from long time production history accuracy was 99.98% while evaluation models built with data from short production history accuracy was 98.64%. The models are then adopted after validation. The validated curves are used to build the governing models which are finally used in estimating cumulative reserves recovery and initially in place. It is concluded that accurate reserves, recovery factor and time estimation challenges can be achieved/matched up using rate decline trend techniques.
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
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信