长期生产策略——应用动态集成储采模型识别压缩需求并解决大型气田生产延迟问题

A. Alsaeedi, E. Latypov, M. Elabrashy, M. Alzeyoudi, A. Al-Ameri, M. Albadi, A. A. Al Bairaq, Sandeep Soni, Jose Isambertt, Deepak Tripathi, M. Hidalgo, Hamda Alkuwaiti
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引用次数: 0

摘要

在循环开采或枯竭开采模式下,气田面临着一些操作挑战,包括合理的预测和稳健的生产策略规划。复杂的储层动态进一步要求更快、更合理的分析决策。本文讨论了一种全面的集成建模方法,以设计包含详细压缩机设计要求的生产策略,以确保在考虑技术和经济方面的长期一致的生产流。拟议的生产策略是一种双重方法。在第一步,该过程在生产预测模型中使用当前油藏模拟数据。该历史匹配模型捕捉了油藏动态,如油藏压力下降,并考虑了未来的钻井需求。然而,该模型并未捕获井眼和地面设施的详细生产水力信息。此外,考虑到井性能下降和设施瓶颈,需要进行综合分析。因此,在第二步中,将油藏模拟模型动态集成,以从生产模型中获取输入,包括详细的油井和地面设施数字孪生。这种持续的相互作用提供了一个高度可靠的生产概况,可用于制定未来压缩机设计的生产策略。数字平台中强大的交互式用户界面使用户能够有效地配置各种假设场景,考虑到所有预期的未来事件和生产条件。该工艺的主要成果是在生产过程中准确识别多个地面设施位置的压力分布。利用商业计划、油田开发策略、生产剖面和油藏模拟输出,获得了可靠的压力剖面,并给出了集输管压力随时间下降的指示。井位生产剖面预测有助于确定井的优先改道顺序和修井要求。研究结果表明,由于储层压力下降,一些管汇容易受到高压下降的影响。为了捕捉这种压力下降,安装了一个压缩机机构,将流体输送到其输送点。由于该研究使用了多个时间步来进行产量预测,因此还为工程师提供了灵活的常规选择,以确保将反压力降至最低,从而避免因快速收益而产生较大的井背压力。之前的方法完全依赖于油藏模拟模型来捕捉井口压力下降,以预测压缩机需求,而该解决方案提高了效率。在这种方法中,捕获每个节点的压力分布以模拟真实的生产场景。这种整体方法符合作业者的业务计划策略,以确定外部能源的需求,以避免生产延迟。
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Long Term Production Strategy - Application of a Dynamically Integrated Reservoir and Production Model to Identify Compression Requirements and to Address Production Deferral in a Giant Gas Field
There are several operational challenges associated with a gas field producing in recycle or depletion mode, including a reasonable forecast and a robust production strategy planning. The complex reservoir dynamics further demands faster and reasonable analysis and decision-making. This paper discusses an all-inclusive integrated modeling approach to devise a production strategy incorporating the detailed compressor design requirements to ensure that a consistent production-stream is available in the long-term considering technical and economic aspects. The proposed production strategy is a two-fold approach. In the first step, the process utilizes the current reservoir simulation data in the production-forecast model. This history matched model captures the reservoir dynamics such as reservoir pressure decline and accounts for future wells drilling-requirements. However, the detailed production hydraulics in wellbore and surface facilities is not captured in the model. Further, to consider the declining well-performance and facility bottlenecks, integrated analysis is required. So, in the second step, the reservoir simulation model is dynamically integrated to take the input from the production model, encompassing detailed well and surface facility digital twins. The continuous interaction provides a highly reliable production profile that can be used to produce a production strategy of compressor design for the future. A strong interactive user-interface in the digital platform enables the user to configure various what-if scenarios efficiently, considering all anticipated future events and production conditions. The major output of the process was the accurate identification of the pressure-profile at multiple surface facility locations over the course of the production. Using the business-plan, field development strategy, production-profile, and the reservoir simulation output, reliable pressure-profiles were obtained, giving an indication of the declining pressures at gathering manifold over time. A well level production-profile-forecast helped in prioritizing wells for rerouting as well as workover requirements. As an outcome of this study, several manifolds were identified that are susceptible to high-pressure decline caused by declining reservoir pressures. To capture this pressure decline, a compressor mechanism was put in place to transfer the fluid to its delivery point. As this study utilizes several timesteps for the production forecast estimation, flexible routine options are also provided to the engineers to ensure that backpressure is minimized to avoid a larger back pressure on the wells for quick gains. This solution improves the efficiency of the previous approaches that were entirely relying on the reservoir simulation model to capture the pressure decline at the wellhead to forecast the compressor needs. In this methodology, the pressure profile at each node was captured to simulate a real production scenario. This holistic approach is in line with Operator's business plan strategy to identify the needs of external energy-source to avoid production-deferral.
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