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Samarang Integrated Operations (IO): Well Performance Workflows Enable Continuous Well Status and Performance Monitoring

机译:Samarang综合操作(IO):井性能工作流使得持续良好的状态和性能监控

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Samarang field is located offshore Sabah, East Malaysia with first oil in 1975. Majority of the platforms are provided with fully pneumatic instrumentation / control and shutdown systems, with no provision for remote monitoring/control. This has caused limitation in acquiring data for monitoring and analyzing hence optimizing the asset. The field is undergoing a major redevelopment project with Integrated Operations (IO) being part of initiatives that covers re-instrumentation, telemetry and telecommunication infrastructure installation, Collaborative Working Environment construction and Workflows implementation. The limitation of status quo instrumentation situation has posed challenges for Samarang asset to monitor flowing status of the wells. Consequently, a number of indirect inferences were being used to determine the status and uptime of the wells including sporadic well head observation (i.e. “feeling” or “touching” the well head assembly for vibrations) and well head fluid sampling. Added to the complexity is the flow from multiple strings and wells commingling in production headers in each of the well platforms, it is not uncommon to have cases wherein the individual string or well’s actual status and production contribution is unknown for many days (or even weeks). At best, Well Testing, which is a direct measurement of the well or string’s deliverability, is carried out once a month. This paper describes a novel methodology of implementing workflow to achieve continuous well status monitoring objective. Workflow that combines the data feeding and processing through data driven logics as well as well models driven logics has enabled continuous well status awareness. The workflow has enabled the followings: 1. Continuous well rate estimation using nodal analysis well model by automating data input and result output process 2. Well flowing or quitting status inference by using wellhead pressure, temperature, valve status, gas lift injection pressure, MIG, pump voltage and frequency for natural, gas lifted as well as ESP wells 3. Automated notification of well status through Tri-node Collaborative Working Environment 4. Faster reaction and decision 5. Reduction of production deferment and increase awareness to the well status and performance.
机译:Samarang Field位于近海沙巴,1975年东马来西亚东马来西亚拥有First Oil.大部分平台配有全气动仪表/控制和关闭系统,无需远程监控/控制。这使得在获取监控和分析数据的情况下造成了限制,因此可以优化资产。该领域正在进行一个主要的重建项目,综合运营(IO)是涵盖重新识别,遥测和电信基础设施安装,协作工作环境建设和工作流程实施的举措的一部分。现状仪器仪表情况的限制对萨马朗资产的挑战构成,以监测井的流动状态。因此,正在使用许多间接推论来确定井中的井的状态和正常运行时间(即“感觉”或“触摸”振动的井头组件)和井头流体采样。添加到复杂性是从多个弦和井中的流程中的流程在每个井平台中的生产标题中,在许多天(甚至周的几周内)未知)。最佳,测试良好的测试,即直接测量井或字符串的可交付性,每月进行一次。本文介绍了实现工作流程的新方法,以实现连续井状态监测目标。通过数据驱动逻辑以及模型驱动逻辑结合数据馈送和处理的工作流程使得能够连续良好的地位感知。工作流程已启用以下操作流程:1。通过自动化数据输入和结果输出过程使用节点分析井模型连续井速率估计。通过使用井口压力,温度,阀状态,气体升降喷射压力,MIG良好流动或退出状态推断,天然气泵电压和频率,气体升降,尤其是通过三节点协作工作环境自动通知井地位4.更快的反应和决定5.减少生产延迟并提高对井地位和性能的认识。

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