The SMART SRP Well – Application of Edge Analytics for Automated Well Performance Control and Condition Monitoring in a Mature Brownfield Environment – A Case Study from Austria

Christian Windisch
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Abstract

This paper presents a holistic approach to modern oilfield and well surveillance through the inclusion of state-of-the-art edge computing applications in combination with a novel type of data transmission technology and algorithms developed in-house for automatic condition monitoring of SRP systems. The objective is to enable the responsible specialist staff to focus on the most important decisions regarding oilfield management, rather than wasting time with data collection and preparation. An own operated data communication system, based on LPWAN-technology transfers the dyno-cards, generated by an electric load cell, into the in-house developed production assistance software platform. Suitable programmed AI-algorithms enable automatic condition detection of the incoming dyno cards, including conversion and analysis of the corresponding subsurface dynamograms. A smart alarming system informs about occurring failure conditions and specifies whether an incident of rod rupture, pump-off condition, gas lock or paraffin precipitation occurred in the well. A surface mounted measuring device delivers liquid level and bottomhole pressure information automatically into the software. Based on these diverse data, the operations team plans the subsequent activities. The holistic application approach is illustrated using the case study of an SPR-operated well in an Austrian brownfield.
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SMART SRP井-边缘分析在成熟棕地环境中自动井情控制和状态监测中的应用-奥地利案例研究
本文通过将最先进的边缘计算应用与新型数据传输技术和内部开发的用于SRP系统自动状态监测的算法相结合,提出了一种全面的现代油田和油井监测方法。目的是使负责的专业人员能够专注于有关油田管理的最重要决策,而不是将时间浪费在数据收集和准备上。基于lpwan技术的自主操作数据通信系统将由电动称重传感器生成的动态卡传输到内部开发的生产辅助软件平台。合适的编程人工智能算法能够自动检测输入的动态卡,包括相应地下动态图的转换和分析。智能报警系统可以通知发生的故障情况,并指定井中是否发生了抽油杆断裂、抽离、气锁或石蜡沉淀等事件。安装在地面的测量装置将液位和井底压力信息自动输入软件。基于这些不同的数据,运营团队计划后续的活动。以奥地利棕地的spr井为例,说明了整体应用方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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