Production Performance Analysis of Volga-Ural Mature Waterflood with PRIME Diagnostic Metrics

A. Aslanyan, B. Ganiev, A. Lutfullin, I. Farkhutdinov, M. Garnyshev, R. Farakhova, Alfiya Nurimanovna Mustafina
{"title":"Production Performance Analysis of Volga-Ural Mature Waterflood with PRIME Diagnostic Metrics","authors":"A. Aslanyan, B. Ganiev, A. Lutfullin, I. Farkhutdinov, M. Garnyshev, R. Farakhova, Alfiya Nurimanovna Mustafina","doi":"10.2118/206513-ms","DOIUrl":null,"url":null,"abstract":"\n The paper presents a practical case of production performance analysis at one of the mature waterflood oil fields located at the Volga-Ural oil basin with a large number of wells. It is a big challenge to analyse such a large production history and requires a systematic approach.\n The main production complication is quite common for mature waterflood projects and includes non-uniform sweep, complicated by thief injection and thief water production. The main challenge is to locate the misperforming wells and address their complications.\n With the particular asset, the conventional single production analysis techniques (oil production trend, watercut trend, reservoir and bottom-hole pressure trend, productivity trend, conventional pressure build-up surveys and production logging) in the vast majority of cases were not capable of qualifying the well performance and assessing of remaining reserves status. The performance analysis of such an asset should be enhanced with new diagnostic tools and modern methods of data integration.\n The current study has made a choice in favor of using a PRIME analysis which is multi-parametric analytical workflow based on a set of conventional and non-conventional diagnostic metrics. The most effective diagnostics in this study have happened to be those are based on 3D dynamic micro-models, which are auto-generated from the reservoir data logs.\n PRIME also provided useful insights on well performance, formation properties and the current conditions of drained reserves which helped to select the candidates for infill drilling, pressure maintenance, workovers, production target adjustments and additional surveillance.\n The paper illustrates the entire PRIME workflow, starting from the top-level field data analysis, all the way to generating a summary table containing well diagnostics, justifications and recommendations.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Wed, October 13, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/206513-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

Abstract

The paper presents a practical case of production performance analysis at one of the mature waterflood oil fields located at the Volga-Ural oil basin with a large number of wells. It is a big challenge to analyse such a large production history and requires a systematic approach. The main production complication is quite common for mature waterflood projects and includes non-uniform sweep, complicated by thief injection and thief water production. The main challenge is to locate the misperforming wells and address their complications. With the particular asset, the conventional single production analysis techniques (oil production trend, watercut trend, reservoir and bottom-hole pressure trend, productivity trend, conventional pressure build-up surveys and production logging) in the vast majority of cases were not capable of qualifying the well performance and assessing of remaining reserves status. The performance analysis of such an asset should be enhanced with new diagnostic tools and modern methods of data integration. The current study has made a choice in favor of using a PRIME analysis which is multi-parametric analytical workflow based on a set of conventional and non-conventional diagnostic metrics. The most effective diagnostics in this study have happened to be those are based on 3D dynamic micro-models, which are auto-generated from the reservoir data logs. PRIME also provided useful insights on well performance, formation properties and the current conditions of drained reserves which helped to select the candidates for infill drilling, pressure maintenance, workovers, production target adjustments and additional surveillance. The paper illustrates the entire PRIME workflow, starting from the top-level field data analysis, all the way to generating a summary table containing well diagnostics, justifications and recommendations.
基于PRIME诊断指标的伏尔加—乌拉尔成熟注水生产动态分析
本文介绍了伏尔加-乌拉尔油区一个井数较多的成熟注水油田的生产动态分析实例。分析如此庞大的生产历史是一个巨大的挑战,需要一个系统的方法。对于成熟的水驱项目来说,主要的生产复杂性是相当普遍的,包括不均匀波及、不均匀注入和不均匀产水。主要的挑战是定位表现不佳的井并解决其复杂问题。对于特定的资产,在绝大多数情况下,常规的单一生产分析技术(产量趋势、含水趋势、油藏和井底压力趋势、产能趋势、常规压力增加调查和生产测井)无法确定油井的性能和评估剩余储量状况。应该使用新的诊断工具和现代数据集成方法来增强对此类资产的性能分析。目前的研究选择使用PRIME分析,这是一种基于一组常规和非常规诊断指标的多参数分析工作流程。在这项研究中,最有效的诊断方法是基于3D动态微观模型,该模型是根据储层数据测井自动生成的。PRIME还提供了有关油井性能、地层性质和泄油储量现状的有用见解,有助于选择进行填充钻井、压力维护、修井、生产目标调整和额外监视的候选井。本文阐述了整个PRIME工作流程,从顶级现场数据分析开始,一直到生成包含油井诊断、论证和建议的汇总表。
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 求助全文
来源期刊
自引率
0.00%
发文量
0
文献相关原料
公司名称 产品信息 采购帮参考价格
×
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