Intelligent Digital Oilfield Implementation: Production Optimization Using North Kuwait Integrated Digital Oil Field NK KwIDF

Dalal Al-Subaiei, M. Al-Hamer, Ahmed Al-Zaidan, H. Chetri, Mohammad Sami Nawaz
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Abstract

Global oil demand has led to the development of new smarter drilling, completion, reservoir management technique and technology to optimize reservoirs production. The production of Kuwait Oil Company (KOC) has reached 3 MMBOPD and KOC’s 2030 vision is to boost the production to 4 MMBOPD. In order to achieve this vision, KOC has started several technical projects and development plans. One of these projects is the North Kuwait Integrated Digital Oil Field (NK-KwIDF) a full-fledged Field project implemented in KOC. This Paper will discuss the scale, complexity, technology used, and advantage of using the NK-KwIDF. The North Kuwait (NK) asset has five fields, around twelve hundred active wells, and seven Gathering Centers (GCs). A complex network of pipeline, trunk line, and manifold are used to connect these twelve hundred wells to GCs. In order to optimize the production from NK every barrel of production opportunity has to be considered by optimizing suitable wells and minimizing downtime from each field, resulting the development of an extensive surface network model. The extensive surface network model takes into consideration of each and every details of field e.g. pipelines, manifolds, details of GCs and wells. For each and every well in NK assets a well model is prepared considering all PVT parameters, completions, and surface co-ordinate and finally connected to surface network model with all piping information. Once the extensive surface model was prepared, several integrated workflows were developed in order to efficiently run the surface model and analyze the output from the run. Some of these workflows are ESP Optimization and ESP Analysis workflows, which have capability to identify the Oil Gain Opportunities and diagnose ESP performance. The identify opportunities are logged into ticketing system, which monitors the life cycle of the opportunity right from the identification till implementation into the field for Oil Gains. The full-fledged development of NK-KwIDF took almost 3 years from the day it was started, as a pilot project with 133 wells. When an excellent result in terms of production optimization and downtime minimization was recorded from the pilot project, the pilot project was expanded to full-fledged field project. The NK-KwIDF project gave an outstanding result of Oil gain from well level as well as Network level optimization. It established an excellent reputation in the oil industry where it was a source of attraction for many NOC’s and IOC’s to visit and follow the flag ship for their development and implementation of digital field technology.
智能数字油田实施:利用北科威特集成数字油田NK KwIDF优化生产
全球石油需求推动了新型智能钻井、完井、油藏管理技术和技术的发展,以优化油藏产量。科威特石油公司(KOC)的产量已达到300万桶/天,KOC的2030年愿景是将产量提高到400万桶/天。为了实现这一愿景,KOC已经启动了几个技术项目和开发计划。其中一个项目是北科威特综合数字油田(NK-KwIDF),这是一个在科威特石油公司实施的成熟的油田项目。本文将讨论使用NK-KwIDF的规模、复杂性、使用的技术和优势。北科威特(NK)资产拥有5个油田,约1200口活跃井和7个聚集中心(gc)。一个由管道、干线和歧管组成的复杂网络被用来将这1200口井与gc连接起来。为了优化NK的产量,必须考虑每一桶的生产机会,优化合适的井,最大限度地减少每个油田的停机时间,从而建立一个广泛的地面网络模型。广泛的地面网络模型考虑了油田的每一个细节,如管道、歧管、gc和井的细节。对于NK资产中的每口井,都要考虑所有PVT参数、完井和地面坐标,并最终与具有所有管道信息的地面网络模型相连接。一旦准备好了广泛的曲面模型,为了有效地运行曲面模型并分析运行的输出,需要开发几个集成的工作流程。其中一些工作流程是ESP优化和ESP分析工作流程,它们能够识别出采油机会并诊断ESP的性能。识别机会被记录在票务系统中,该系统监控机会的生命周期,从识别到实施到油田,以获得石油收益。NK-KwIDF的全面开发从启动之日起花了近3年的时间,作为一个133口井的试点项目。当试验项目在生产优化和停机时间最小化方面取得了优异的成绩时,该试验项目扩展到成熟的现场项目。NK-KwIDF项目在井级和网络级优化方面都取得了显著的效果。它在石油行业建立了良好的声誉,吸引了许多NOC和IOC参观并跟随其旗舰船开发和实施数字油田技术。
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