Intelligent oil field technology maturity level assessment: using the technology readiness level criteria

IF 2.9 Q2 MANAGEMENT
Hajar Pouran Manjily, Mahmood Alborzi, Turaj Behrouz, Seyed Mohammad Seyed- Hosseini
{"title":"Intelligent oil field technology maturity level assessment: using the technology readiness level criteria","authors":"Hajar Pouran Manjily, Mahmood Alborzi, Turaj Behrouz, Seyed Mohammad Seyed- Hosseini","doi":"10.1108/jstpm-11-2022-0191","DOIUrl":null,"url":null,"abstract":"Purpose This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner. Design/methodology/approach This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies. Findings None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields. Originality/value This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.","PeriodicalId":45751,"journal":{"name":"Journal of Science and Technology Policy Management","volume":"47 10","pages":"0"},"PeriodicalIF":2.9000,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Science and Technology Policy Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jstpm-11-2022-0191","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner. Design/methodology/approach This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies. Findings None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields. Originality/value This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.
智能油田技术成熟度水平评价:采用技术成熟度标准
本研究旨在对伊朗油田情报的技术准备水平(TRL)进行全面评估,并与其他具有类似油藏的国家进行比较。最终目标是利用智能技术优化该油田的石油开采。将智能技术应用于油田可以大大简化作业,特别是在难以进入的区域,并增加石油产量,从而为油田所有者带来更高的收入和利润。本研究从智能油田的角度,通过使用衡量技术成熟度的标准来评估当前油田技术的成熟度水平。设计了一份调查表,分发给18名石油工业专业人员。利用加权标准,从受访者的回答中得出油田技术成熟度的平均估计值。研究人员利用科学研究评估了文莱、科威特和沙特阿拉伯油田的技术准备水平。没有一个受访者认为伊朗的智能油田是高度发达的,具有TRL 9准备水平。大多数专家认为,伊朗石油工业的智能技术仅达到TRL 2和TRL 1,或者仅仅处于基础和应用研究的转移阶段。显然,文莱、科威特和沙特阿拉伯拥有世界上最发达的油田。在伊朗,智能油田领域的学者、执行和承包公司正致力于智能开发年轻油田。独创性/价值本研究探讨了伊朗某油田智能技术的成熟程度。并将其与全球其他几个智能油田的智能技术成熟水平进行了比较。智能油田TRL的增加可以更好地管理油藏,提高利润和采收率。
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
CiteScore
5.90
自引率
8.70%
发文量
57
×
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