Complex Approach to Creation and Maintenance of Integrated Asset Models and Implementation of Digital Data Management Platform

Pavel Vladimirovich Markov, A. V. Gorshkov, Sergey Vladimirovich Shadrin
{"title":"Complex Approach to Creation and Maintenance of Integrated Asset Models and Implementation of Digital Data Management Platform","authors":"Pavel Vladimirovich Markov, A. V. Gorshkov, Sergey Vladimirovich Shadrin","doi":"10.2118/206536-ms","DOIUrl":null,"url":null,"abstract":"\n The paper presents a complex approach based on the experience of the authors of this article for creating and maintaining integrated asset models (IAM) and implementing a digital data management platform. Problems of using IAM for the operational management of field development and production are that the data is not accurate, the measurements are spaced in time, and there is not enough data to understand the physical phenomena taking place. The complex approach is that to provide integrated asset models with high-quality data, it is necessary to build new processes, create new specialties and competencies, the key success factor is the combination of the experience of Customer (oil company), Internal oil-related service of Customer (geological and geophysical research), External contractor of oil-related service (the combination of experience in geological and geophysical research, experience in integrated asset modeling and operational support for field development using integrated asset modeling tools and digitalization of data management). The best way to implement the approach of creating joint Integrated Team of External and Internal oilfield service Contractors in the form of Complex Service Engineering Center, the task for which which was the organization of a cyber-physical system for collecting field data, verifying data, identifying problem areas in data, defining approaches to eliminating problem areas using tools of automation tools for working with data, the flexible management of well testing and survey programs, the operational formation of well testing and survey design for non-standard situations. Particular attention in this complex approach is paid to working with initial field data, this article provides a general scheme for verifying the various parameters of well operation and an example of its use for flow rates, as well as examples of the quality analysis of reservoir pressures based on the use of a two-dimensional one-phase proxy reservoir model and the quality analysis of GOR for a well. Based on the developed complex approach, the paper provides examples of strategic and operational problems for a field - the assessment of optimal production for a field and the assessment of oil shortfalls for a well, respectively.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":"23 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Wed, October 13, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/206536-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

The paper presents a complex approach based on the experience of the authors of this article for creating and maintaining integrated asset models (IAM) and implementing a digital data management platform. Problems of using IAM for the operational management of field development and production are that the data is not accurate, the measurements are spaced in time, and there is not enough data to understand the physical phenomena taking place. The complex approach is that to provide integrated asset models with high-quality data, it is necessary to build new processes, create new specialties and competencies, the key success factor is the combination of the experience of Customer (oil company), Internal oil-related service of Customer (geological and geophysical research), External contractor of oil-related service (the combination of experience in geological and geophysical research, experience in integrated asset modeling and operational support for field development using integrated asset modeling tools and digitalization of data management). The best way to implement the approach of creating joint Integrated Team of External and Internal oilfield service Contractors in the form of Complex Service Engineering Center, the task for which which was the organization of a cyber-physical system for collecting field data, verifying data, identifying problem areas in data, defining approaches to eliminating problem areas using tools of automation tools for working with data, the flexible management of well testing and survey programs, the operational formation of well testing and survey design for non-standard situations. Particular attention in this complex approach is paid to working with initial field data, this article provides a general scheme for verifying the various parameters of well operation and an example of its use for flow rates, as well as examples of the quality analysis of reservoir pressures based on the use of a two-dimensional one-phase proxy reservoir model and the quality analysis of GOR for a well. Based on the developed complex approach, the paper provides examples of strategic and operational problems for a field - the assessment of optimal production for a field and the assessment of oil shortfalls for a well, respectively.
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
集成资产模型创建与维护的复杂方法与数字数据管理平台的实现
本文根据本文作者的经验提出了一种复杂的方法,用于创建和维护集成资产模型(IAM)和实现数字数据管理平台。在油田开发和生产的操作管理中使用IAM存在的问题是数据不准确,测量时间间隔,并且没有足够的数据来理解正在发生的物理现象。复杂的方法是,要提供具有高质量数据的综合资产模型,必须建立新的流程,创造新的专业和能力,关键的成功因素是结合客户(石油公司)的经验,客户的内部石油相关服务(地质和地球物理研究),石油相关服务的外部承包商(地质和地球物理研究经验的结合),具有集成资产建模和使用集成资产建模工具和数字化数据管理为油田开发提供运营支持的经验)。以复杂服务工程中心的形式创建外部和内部油田服务承包商联合集成团队的最佳方式,其任务是组织一个网络物理系统,用于收集现场数据、验证数据、识别数据中的问题区域、定义使用自动化工具来消除问题区域的方法来处理数据、灵活管理试井和调查项目。针对非标准工况的试井设计形成了作业模式。在这种复杂的方法中,特别注意处理初始现场数据,本文提供了一个验证井操作各种参数的一般方案,并举例说明了其用于流量的情况,以及基于使用二维单相代理油藏模型和井的GOR质量分析的油藏压力质量分析的例子。在此基础上,给出了油田战略问题和作业问题的实例——油田最优产量评价和油井缺油评价。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Technological Features of Associated Petroleum Gas Miscible Injection MGI in Order to Increase Oil Recovery at a Remote Group of Fields in Western Siberia Interdisciplinary Approach for Wellbore Stability During Slimhole Drilling at Volga-Urals Basin Oilfield A Set of Solutions to Reduce the Water Cut in Well Production Production Optimiser Pilot for the Large Artificially-Lifted and Mature Samotlor Oil Field Artificial Neural Network as a Method for Pore Pressure Prediction throughout the Field
×
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