{"title":"Real-Time Production Optimization - Applying a Digital Twin Model to Optimize the Entire Upstream Value Chain","authors":"B. Okhuijsen, K. Wade","doi":"10.2118/197693-ms","DOIUrl":null,"url":null,"abstract":"\n The oil and gas industry is increasingly looking toward data-driven solutions to boost performance, enhance efficiency and reduce costs. However, understanding such complex systems requires the consideration of data from multiple sources in real time. Digital Twin modelling is at the heart of the next generation of real-time production monitoring and optimization systems. Using the integration of data, simulation, and visualization of the entire operating company value chain, from the subsurface equipment to central processing facilities, it's a solution that maximizes production. Such a system for Real-time Production Optimization (RTPO) has been developed jointly by Siemens and Process Systems Enterprise by combining their XHQ and gPROMS Oilfield technology.","PeriodicalId":11061,"journal":{"name":"Day 1 Mon, November 11, 2019","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, November 11, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/197693-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
The oil and gas industry is increasingly looking toward data-driven solutions to boost performance, enhance efficiency and reduce costs. However, understanding such complex systems requires the consideration of data from multiple sources in real time. Digital Twin modelling is at the heart of the next generation of real-time production monitoring and optimization systems. Using the integration of data, simulation, and visualization of the entire operating company value chain, from the subsurface equipment to central processing facilities, it's a solution that maximizes production. Such a system for Real-time Production Optimization (RTPO) has been developed jointly by Siemens and Process Systems Enterprise by combining their XHQ and gPROMS Oilfield technology.
石油和天然气行业越来越多地寻求数据驱动的解决方案，以提高性能、提高效率和降低成本。然而，理解如此复杂的系统需要实时考虑来自多个来源的数据。数字孪生模型是下一代实时生产监控和优化系统的核心。通过整合从地下设备到中央处理设施的整个运营公司价值链的数据、模拟和可视化，该解决方案可以最大限度地提高产量。这种实时生产优化(RTPO)系统是由西门子和Process Systems Enterprise联合开发的，结合了XHQ和gPROMS油田技术。
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