Empirical Design of Optimum Frequency of Well Testing for Deepwater Operation

E. Udofia
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Abstract

Well testing could be described as a process required to calculate the volumes of (oil, water and gas) production from a well in a bid to identify the current state of the well. Amongst other things, well testing aims to provide information for effective Well, Reservoir and Facility Management. Normally, as a means of well performance health-check, reconciliation factor (RF) is generated by comparing the fiscal production volume against the theoretical well test volume. Experiences from the Coronavirus pandemic has brought about the new normal into well test execution. In deepwater environment, the process of well testing is more challenging and this paper aims to address these challenges and propose optimum well test frequency for deepwater operations. It is usually required that routine well test be conducted once every month on all flowing strings, this is for statutory compliance and well health-check purposes. However, in deepwater environment, it is difficult to comply with this periodic well test requirement mainly due to production flow line slugging, plant process upset and/or tripping resulting in production deferment and operational risk exposure. Furthermore, to carry out well test in deepwater operation, production cutback is required for flow assurance purpose and this usually results in huge production deferment. In this field of interest, this challenge has been managed by deploying a data-driven application to monitor production on individual flowing strings in real-time thereby optimizing the frequency of well test on every flowing well. Varying rate well test data are captured and used to calibrate this tool or application for subsequent real-time production monitoring. This initiative ensures that all the challenges earlier mentioned are managed while actually optimizing the frequency of testing the wells using intelligent application which serves as a ‘virtual meter’ for testing all producing wells in real time. As mentioned, well testing in most deepwater assets remain a big challenge but this project based field experience has ensured effective well testing operation resulting in reduction of production deferment and safety exposure during plant tripping whilst optimizing frequency of testing the wells. Following this achievement of the optimized well test to quarterly frequency in this field in Nigerian deepwater, recommendation from this paper will assist other deepwater field operators in managing routine well testing operation optimally.
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深水作业最佳试井频率的经验设计
试井可以被描述为计算油井(油、水和气)产量的过程,以确定油井的当前状态。除其他外,试井旨在为有效的油井、油藏和设施管理提供信息。通常,作为井况健康检查的一种手段,调节因子(RF)是通过比较实际产量和理论试井量来产生的。新冠肺炎疫情给试井带来新常态。在深水环境中,试井过程更具挑战性,本文旨在解决这些挑战,并提出深水作业的最佳试井频率。通常要求每个月对所有流动管柱进行一次常规试井,这是为了符合法律规定和检查井的健康状况。然而,在深水环境中,由于生产流水线段塞、工厂过程中断和/或起下钻导致生产延迟和操作风险暴露,很难遵守这一定期试井要求。此外,为了在深水作业中进行试井,需要削减产量以保证流动,这通常会导致巨大的生产延迟。在这一领域,通过部署数据驱动的应用程序来实时监测单个流动管柱的产量,从而优化每口流动井的试井频率,解决了这一挑战。捕获不同速率的试井数据,并用于校准该工具或应用程序,以进行后续的实时生产监控。这一举措确保了前面提到的所有挑战都得到了管理,同时利用智能应用程序优化了测试井的频率,该应用程序可以作为“虚拟仪表”,实时测试所有生产井。如前所述,大多数深水资产的试井仍然是一个巨大的挑战,但该项目基于现场经验,确保了有效的试井作业,从而减少了工厂起下钻期间的生产延迟和安全风险,同时优化了测试井的频率。在尼日利亚深水油田实现了优化试井的季度频率之后,本文的建议将帮助其他深水油田运营商以最佳方式管理常规试井作业。
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