数据分析应用于水力建模,可以更好地了解井/地面网络的限制,主动识别挑战,并为Greater Burgan油田提供改善系统性能的解决方案

Q. Dashti, Saad Matar, Hanan Abdulrazzaq, Nouf Al-Shammari, F. Franco, E. Haryanto, Michael Q Zhang, R. Prakash, Nelson Bolanos, Muhammad Ibrahim, Mostafa Afifi
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引用次数: 0

摘要

对15个地面收集中心进行网络建模,涉及1800多个完井管柱,有助于对现有地面管网设施的不同风险进行规划,并改进对科威特石油公司东南科威特(SEK)资产的不同业务和行动计划的筛选。井和网络的水力模型被创建和校准,以支持现场开发、规划和操作团队的工程师评估生产系统的水力系统,以确定流动保证问题和系统优化机会。稳态水力模型允许在多种操作场景下对综合井和地面网络进行分析,为改进规划和决策过程提供重要输入。该研究的重点不仅在于获得井和地面网络元素物理尺寸的准确表示,还在于创建一种工具,该工具包括能够评估井和地面网络行为的标准分析工作流程,从而有助于提供有洞察力的预测能力,并满足维持石油生产和控制不需要的流体(如水和气)的业务需求。因此,该模型需要具有足够的灵活性,以涵盖不同的网络运行条件。利用水力模型,可以更快、更有效地评估和诊断井和网络层面的作业问题,为短期和长期提供可靠的解决方案。水力模型使工程师能够研究多种情况,以确定约束条件,并改善SEK的操作性能和规划过程,重点是优化操作参数,以建立有效的井降,评估人工举升要求,集采中心集管的最佳井隔离,识别流动保证问题,并支持生产预测,以确保有效的生产管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data Analytics into Hydraulic Modelling for Better Understanding of Well/Surface Network Limits, Proactively Identify Challenges and, Provide Solutions for Improved System Performance in the Greater Burgan Field
A network modeling campaign for 15 surface gathering centers involving more than 1800 completion strings has helped to lay out different risks on the existing surface pipeline network facility and improved the screening of different business and action plans for the South East Kuwait (SEK) asset of Kuwait Oil Company. Well and network hydraulic models were created and calibrated to support engineers from field development, planning, and operations teams in evaluating the hydraulics of the production system for the identification of flow assurance problems and system optimization opportunities. Steady-state hydraulic models allowed the analysis of the integrated wells and surface network under multiple operational scenarios, providing an important input to improve the planning and decision-making process. The focus of this study was not only in obtaining an accurate representation of the physical dimension of well and surface network elements, but also in creating a tool that includes standard analytical workflows able to evaluate wells and surface network behavior, thus useful to provide insightful predictive capability and answering the business needs on maintaining oil production and controlling unwanted fluids such as water and gas. For this reason, the model needs to be flexible enough in covering different network operating conditions. With the hydraulic models, the evaluation and diagnosis of the asset for operational problems at well and network level will be faster and more effective, providing reliable solutions in the short- and long-terms. The hydraulic models enable engineers to investigate multiple scenarios to identify constraints and improve the operations performance and the planning process in SEK, with a focus on optimal operational parameters to establish effective wells drawdown, evaluation of artificial lifting requirements, optimal well segregation on gathering centers headers, identification of flow assurance problems and supporting production forecasts to ensure effective production management.
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