Petroleum Development Oman Forecasting Management System

Hilal Mudhafar Al Riyami, Hilal Mohammed Al Sheibani, Hamed Ali Al Subhi, Hussain Taqi Al Ajmi, Zeinab Youssef Zohny, Azzan Qais Al Kindy
{"title":"Petroleum Development Oman Forecasting Management System","authors":"Hilal Mudhafar Al Riyami, Hilal Mohammed Al Sheibani, Hamed Ali Al Subhi, Hussain Taqi Al Ajmi, Zeinab Youssef Zohny, Azzan Qais Al Kindy","doi":"10.2118/208108-ms","DOIUrl":null,"url":null,"abstract":"\n Production performance forecasting is considered as one of the most challenging and time consuming tasks in petroleum engineering disciplines, it has important implications on decision-making, planning production and processing of facilities. In Petroleum Development Oman (PDO), which is the major petroleum company in Oman, production forecast provides a technical input basis for the economic decisions throughout the exploration and production lifecycle. Reservoir engineers spend more than 250 days per year to complete this process. PDO Forecast Management System (FMS) was introduced to transform the conventional forecasting of gas production. Employing the latest state-of-the-art technologies in the field of data management and machine learning (ML), PDO FMS aims at optimizing and automating the process of capturing, reporting, and predicting hydrocarbon production. This new system covers the full forecast processes including long and short-term forecasting for gas, condensate, and water production. As a pilot project, PDO FMS was deployed on a cluster of 272 wells and relied on agile project management approach to realize the benefits during the development phase. Deployment of the new system resulted in a significant reduction of the forecasting time, optimization of manpower and forecasting accuracy.","PeriodicalId":10967,"journal":{"name":"Day 1 Mon, November 15, 2021","volume":"31 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, November 15, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/208108-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

Production performance forecasting is considered as one of the most challenging and time consuming tasks in petroleum engineering disciplines, it has important implications on decision-making, planning production and processing of facilities. In Petroleum Development Oman (PDO), which is the major petroleum company in Oman, production forecast provides a technical input basis for the economic decisions throughout the exploration and production lifecycle. Reservoir engineers spend more than 250 days per year to complete this process. PDO Forecast Management System (FMS) was introduced to transform the conventional forecasting of gas production. Employing the latest state-of-the-art technologies in the field of data management and machine learning (ML), PDO FMS aims at optimizing and automating the process of capturing, reporting, and predicting hydrocarbon production. This new system covers the full forecast processes including long and short-term forecasting for gas, condensate, and water production. As a pilot project, PDO FMS was deployed on a cluster of 272 wells and relied on agile project management approach to realize the benefits during the development phase. Deployment of the new system resulted in a significant reduction of the forecasting time, optimization of manpower and forecasting accuracy.
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
阿曼石油开发预测管理系统
生产动态预测是石油工程学科中最具挑战性和最耗时的任务之一,它对设施的生产和加工决策、规划具有重要意义。阿曼石油开发公司(PDO)是阿曼主要的石油公司,产量预测为整个勘探和生产生命周期的经济决策提供了技术投入基础。油藏工程师每年要花费250多天的时间来完成这一过程。引入PDO预测管理系统(FMS)对传统的天然气产量预测进行了改造。PDO FMS采用数据管理和机器学习(ML)领域的最新技术,旨在优化和自动化捕获、报告和预测油气产量的过程。这套新系统涵盖了天然气、凝析油和水产量的长期和短期预测。作为一个试点项目,PDO FMS部署在272口井的集群上,并依靠敏捷项目管理方法在开发阶段实现了效益。新系统的部署大大缩短了预测时间,优化了人力资源,并提高了预测的准确性。
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
Produced Water Reuse for Drilling and Completion Fluids Using Ion Exchange Resins Human Factors in HSE Performance – Role of User-Friendly HSE Documentation How Do Bankruptcies in the Shale Sector Induce Operators to Focus on Value Creation? Unconventional Waste & Flare Gas Recovery System UFGRS in New Circular Economy Transformation Management Office as a Vehicle to Accelerate Digital Transformation
×
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