通过气举优化GLO释放棕地生产潜力

B. Hammadi, Karim Agoudjil, A. Fahem, Fateh Tadjine, Hamza Moussa Benabdellah, A. Makhloufi, Abdelghani Djebrouni, B. Bouchikhi, Toufik Younsi
{"title":"通过气举优化GLO释放棕地生产潜力","authors":"B. Hammadi, Karim Agoudjil, A. Fahem, Fateh Tadjine, Hamza Moussa Benabdellah, A. Makhloufi, Abdelghani Djebrouni, B. Bouchikhi, Toufik Younsi","doi":"10.2523/iptc-19786-abstract","DOIUrl":null,"url":null,"abstract":"\n As a Brown Field, located in North Africa. Approximately 95% of Zarzaitine field wells are utilizing Gas Lift as an artificial lift method. The field has a challenging situation to optimize its Oil production; A detailed understanding of the production sys tem thermohydraulic, facility design and the amount of gas injection will ultimately have a major effect on production target. For this purpose, modeling the entire production system was necessary to properly account for the interdependency of wells and surface equipment and determine the system deliverability as a whole by optimizing Gas Lift injection.\n This paper presents an approach which was introduced for the first time in this field to ensure gas is used efficiently using a multiphase flow simulator for wells and pipelines to model the entire field Production Network in addition to the Oil producing wells including Gas lift mandrels. The model includes 112 Gas Lift wells with a detailed Gas Lift valves system currently on production, each one has been matched against the latest valid well test, Seven Separation Centers, Production gathering pipelines, Production gathering Center and Gas Lift Injection Center. The study has been executed in three major phases: Well Modeling & Calibration, Network Modeling and Gas Lift Optimization.\n Total Oil production rate has been defined as an objective function during the optimization phase where the total Injected Gas Lift rate for the entire network and for each individual well have been defined as varying parameters; By having a network model calibrated against field data representing the operational conditions of the asset, performing Gas Lift Optimization was the natural next step. Subsequently, by simulating the production system with different Gas Lift Optimization scenarios to maximize Oil production rate under specific surface facilities constraints using the Production Network Model, a better insight of how gas injection rate affects the total production and an understanding of whether a smarter allocation of the current available gas is possible in comparison to the different scenarios has been accomplished. As a result of this Optimization by applying some local and global constraints a 10% Oil production increase has been achieved.\n This practice has been shown to be successful as predictive technique in a variety of ways specially for such brown fields with more than 60 years of production history. As a next step, to properly manage the real potential of Brown fields, a full field Integrated Asset Model could be created to capture the interaction between the surface and the sub-surface. This model will account for the complex interactions between reservoir, wells and pipelines.","PeriodicalId":11058,"journal":{"name":"Day 2 Tue, January 14, 2020","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Unlocking the Production Potential of Brown Fields through Gas Lift Optimization GLO\",\"authors\":\"B. Hammadi, Karim Agoudjil, A. Fahem, Fateh Tadjine, Hamza Moussa Benabdellah, A. Makhloufi, Abdelghani Djebrouni, B. Bouchikhi, Toufik Younsi\",\"doi\":\"10.2523/iptc-19786-abstract\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n As a Brown Field, located in North Africa. Approximately 95% of Zarzaitine field wells are utilizing Gas Lift as an artificial lift method. The field has a challenging situation to optimize its Oil production; A detailed understanding of the production sys tem thermohydraulic, facility design and the amount of gas injection will ultimately have a major effect on production target. For this purpose, modeling the entire production system was necessary to properly account for the interdependency of wells and surface equipment and determine the system deliverability as a whole by optimizing Gas Lift injection.\\n This paper presents an approach which was introduced for the first time in this field to ensure gas is used efficiently using a multiphase flow simulator for wells and pipelines to model the entire field Production Network in addition to the Oil producing wells including Gas lift mandrels. The model includes 112 Gas Lift wells with a detailed Gas Lift valves system currently on production, each one has been matched against the latest valid well test, Seven Separation Centers, Production gathering pipelines, Production gathering Center and Gas Lift Injection Center. The study has been executed in three major phases: Well Modeling & Calibration, Network Modeling and Gas Lift Optimization.\\n Total Oil production rate has been defined as an objective function during the optimization phase where the total Injected Gas Lift rate for the entire network and for each individual well have been defined as varying parameters; By having a network model calibrated against field data representing the operational conditions of the asset, performing Gas Lift Optimization was the natural next step. Subsequently, by simulating the production system with different Gas Lift Optimization scenarios to maximize Oil production rate under specific surface facilities constraints using the Production Network Model, a better insight of how gas injection rate affects the total production and an understanding of whether a smarter allocation of the current available gas is possible in comparison to the different scenarios has been accomplished. As a result of this Optimization by applying some local and global constraints a 10% Oil production increase has been achieved.\\n This practice has been shown to be successful as predictive technique in a variety of ways specially for such brown fields with more than 60 years of production history. As a next step, to properly manage the real potential of Brown fields, a full field Integrated Asset Model could be created to capture the interaction between the surface and the sub-surface. This model will account for the complex interactions between reservoir, wells and pipelines.\",\"PeriodicalId\":11058,\"journal\":{\"name\":\"Day 2 Tue, January 14, 2020\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 2 Tue, January 14, 2020\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2523/iptc-19786-abstract\",\"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, January 14, 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2523/iptc-19786-abstract","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

作为一个棕地,位于北非。Zarzaitine油田大约95%的井采用气举作为人工举升方法。油田优化采油面临着严峻的挑战;详细了解生产系统、热水力、设施设计和注气量最终将对生产目标产生重大影响。为此,有必要对整个生产系统进行建模,以适当地考虑井和地面设备的相互依赖性,并通过优化气举注入来确定整个系统的产能。本文提出了一种在该领域首次引入的方法,利用井和管道的多相流模拟器来模拟除产油井外的整个油田生产网络,包括气举心轴,以确保天然气的有效利用。该模型包括112口气举井,目前正在生产详细的气举阀系统,每口井都与最新的有效试井、7个分离中心、生产集输管道、生产集输中心和气举注入中心相匹配。该研究分为三个主要阶段:井建模与校准、网络建模和气举优化。在优化阶段,总产油量被定义为一个目标函数,其中整个网络和每口井的总注入气举率被定义为不同的参数;通过根据代表资产操作条件的现场数据校准网络模型,进行气举优化是自然的下一步。随后,通过使用生产网络模型模拟不同气举优化方案的生产系统,在特定地面设施约束下实现产油量最大化,从而更好地了解注气量如何影响总产量,并了解与不同方案相比,是否可以更智能地分配当前可用天然气。通过应用局部和全局约束条件进行优化,实现了10%的石油产量增长。实践证明,这种预测技术在多种方面都是成功的,特别是对于具有60多年生产历史的棕地。下一步,为了正确管理Brown油田的真正潜力,可以创建一个完整的油田综合资产模型,以捕获地表和地下之间的相互作用。该模型将考虑储层、井和管道之间复杂的相互作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unlocking the Production Potential of Brown Fields through Gas Lift Optimization GLO
As a Brown Field, located in North Africa. Approximately 95% of Zarzaitine field wells are utilizing Gas Lift as an artificial lift method. The field has a challenging situation to optimize its Oil production; A detailed understanding of the production sys tem thermohydraulic, facility design and the amount of gas injection will ultimately have a major effect on production target. For this purpose, modeling the entire production system was necessary to properly account for the interdependency of wells and surface equipment and determine the system deliverability as a whole by optimizing Gas Lift injection. This paper presents an approach which was introduced for the first time in this field to ensure gas is used efficiently using a multiphase flow simulator for wells and pipelines to model the entire field Production Network in addition to the Oil producing wells including Gas lift mandrels. The model includes 112 Gas Lift wells with a detailed Gas Lift valves system currently on production, each one has been matched against the latest valid well test, Seven Separation Centers, Production gathering pipelines, Production gathering Center and Gas Lift Injection Center. The study has been executed in three major phases: Well Modeling & Calibration, Network Modeling and Gas Lift Optimization. Total Oil production rate has been defined as an objective function during the optimization phase where the total Injected Gas Lift rate for the entire network and for each individual well have been defined as varying parameters; By having a network model calibrated against field data representing the operational conditions of the asset, performing Gas Lift Optimization was the natural next step. Subsequently, by simulating the production system with different Gas Lift Optimization scenarios to maximize Oil production rate under specific surface facilities constraints using the Production Network Model, a better insight of how gas injection rate affects the total production and an understanding of whether a smarter allocation of the current available gas is possible in comparison to the different scenarios has been accomplished. As a result of this Optimization by applying some local and global constraints a 10% Oil production increase has been achieved. This practice has been shown to be successful as predictive technique in a variety of ways specially for such brown fields with more than 60 years of production history. As a next step, to properly manage the real potential of Brown fields, a full field Integrated Asset Model could be created to capture the interaction between the surface and the sub-surface. This model will account for the complex interactions between reservoir, wells and pipelines.
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