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Unlocking Well Potential Using an Automated Well Allowable Analysis in a Digital IAOM Framework

机译:使用数字IAOM框架中的自动良好允许分析解锁井潜力

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This paper describes an efficient, accurate, and timesaving approach for setting well allowable using advanced and automated workflows in a digital oil field with more than 300 producing and injecting strings from multi-layered reservoirs having varied reservoir characteristics. This paper provides an insight on the usage of ADNOC shareholders guidelines, well characteristics, surface facility constraints, and integrated asset models to compute the well allowable rate. An integrated asset operations model (IAOM) within a digital framework provides an automation of engineering approach where shareholder/reservoir management guidelines, in conjunction with a calibrated well and network models, are used to improve efficiency and accuracy of setting wells allowable. This process incorporates the interaction among various components, including wellbore dynamics (Inflow and outflow performance), surface network backpressure effect, and complex system constraints. "System Efficiency and Well Availability" factors as well as predicted well parameters such as GOR and watercut. This advance workflow computes the rate that can be delivered from each well corresponding to each guideline and constraint, thereby providing key inputs to various business objective scenarios for production efficiency improvement. This automated "Setting Well Allowable" workflow, using an IAOM solution in a digital framework, has enabled the asset to identify true potential of wells and overcoming potential challenges of computational time saving while identifying opportunities. This automated validation workflows ensured usage of updated and validated well models, allowing effective use of the well test information and real time data for further analysis and sensitivities. The use of the automated workflow has reduced the time to compute the well allowable rates and well technical rates by more than 50%. This workflow prevented engineers from performing tedious manual calculations on a well-by-well basis, therefore engineers focus on engineering and analytical problems rather than collecting data. Additionally, this robust engineering approach provides users with key information associated with a well's performance under various guideline index such as potential rates, well technical rate, minimum backpressure rate, rate to maintain drawdown/ minimum bottom hole pressure limit to ensure a homogenous reservoir withdraw to avoid pressure sink areas. This work process also highlights the wells with increased watercut (WC) and gas oil ratio (GOR), thus providing crucial information for deteriorating well performance. A short-term forecasting with diagnostic curve fitting and trend analysis enabled users to validate deliverability of allowable rates in a calibrated network model scenario, thereby incorporating potential surface constraints and facility bottlenecks. The robustness of advanced and automated setting of well allowable workflow enables the operator to establish well performance with a solid engineering analysis base, and thereby unlocks key opportunities for saving cost, computational time and assuring short-term production mandate deliverables. This approach supports standardization of the work process across the whole organization.
机译:本文介绍了使用数字油田中的先进和自动化工作流程的高效,准确和令人惊叹的方法,该方法在数字油田中使用超过300的多层储存器具有多种储存器特性的多层储存器。本文介绍了Adnoc股东指南,井特征,表面设施限制和集成资产模型的识别,以计算良好的允许速率。数字框架内的集成资产运营模式(IAOM)提供了一种工程方法的自动化,其中股东/储层管理指南与校准的井和网络模型一起使用,用于提高允许的井的效率和准确性。该过程包括各种组件之间的相互作用,包括井筒动力学(流入和流出性能),表面网络背压效应和复杂的系统约束。 “系统效率和井可用性”因素以及预测GOR和Watercut等井参数。该提前工作流计算可以从对应于每个指南和约束的每个井交付的速率,从而为各种商业客观方案提供用于生产效率改进的关键输入。这种自动化的“设置良好允许的”工作流程,在数字框架中使用IAOM解决方案,使得资产能够识别井的真正潜力,并在识别机会时克服计算时间的潜在挑战。这种自动验证工作流程确保了使用更新和验证的井模型,允许有效地使用井测试信息和实时数据进行进一步的分析和敏感性。自动化工作流程的使用减少了将允许允许的速率和良好技术速率计算的时间超过50%。这种工作流程阻止了工程师在良好的基础上进行了繁琐的手动计算,因此工程师专注于工程和分析问题而不是收集数据。此外,这种强大的工程方法为用户提供了在各种指导指标下与井性能相关的关键信息,例如潜在的速率,良好的技术速率,最小的背压率,保持拉出/最小底部孔压力限制,以确保均匀的水库退出避免压力水槽。该工作过程还突出了随着西葫芦(WC)和瓦斯油比(GOR)增加的井,从而提供了降低井性能的重要信息。具有诊断曲线拟合和趋势分析的短期预测使用户能够在校准网络模型场景中验证允许的速率的可交付性,从而包含潜在的表面约束和设施瓶颈。良好允许的工作流程的先进和自动化设置的鲁棒性使操作员能够使用实体工程分析基础建立良好的性能,从而解锁节省成本,计算时间和确保短期生产授权可交付成本的关键机会。这种方法支持整个组织的工作过程的标准化。

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