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A Surveillance 'Smart Flow' for Intelligent Digital Production Operations

机译:智能数字生产运营的监视“智能流”

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Intelligent digital oilfield (iDOF) operations include the transfer, monitoring, visualization, analysis, and interpretation of real-time data. Enabling this process requires a significant investment to upgrade surface, subsurface, and well instrumentation and also the installation of a sophisticated infrastructure for data transmission and visualization. Once upgraded, the system has the capability to transfer massive quantities of data, converting it into real information at the right time. The transformation of raw data into information is achieved through intelligent, automated work processes, referred to here as "smart flows," which assist engineers in their daily well surveillance activities, helping make them more productive and improve decision making. A major oil and gas operator in the Middle East has invested in such an infrastructure and is developing a set of smart flows for key activities and work flows for its production operations, with the ultimate goal of improved asset performance. This paper explains the development of the production surveillance smart flow, which provides engineers with automated artificial intelligence that analyzes data, provides guidance on well operations, and, when necessary, gives warning and alarms as conditions warrant them. The suite of artificial intelligence consists of advanced correlation statistics, neural- network predictive algorithms, and expert systems.
机译:智能数字油田(IDOF)操作包括实时数据的传输,监视,可视化,分析和解释。启用此过程需要大量投资来升级表面,地下和良好的仪器,以及安装复杂的基础设施,以实现数据传输和可视化。一旦升级,系统就具有传输大量数据的能力,将其转换为正确的时间。通过智能,自动化工作流程将原始数据转换为信息,在此称为“智能流动”,这在其日常监控活动中帮助工程师,帮助他们更加富有成效,改善决策。中东的主要石油和天然气运营商投资于此类基础设施,正在为其生产运营开发一组智能流程,以实现其生产运营的关键活动和工作流程,具有改善资产绩效的最终目标。本文解释了生产监控智能流量的发展,为工程师提供了自动化人工智能分析数据,提供了对井作用的指导,并且在必要时向警告和警报提供警告和警报,因为条件保证。人工智能套件包括先进的相关统计,神经网络预测算法和专家系统。

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