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Utilizing New Proven Technologies in Enhancing Geological Modeling Reservoir Simulation History-Matching: Case Study of A Giant Carbonate Field

机译:利用新的经过新验证技术提高地质建模与储层仿真历史匹配:巨型碳酸盐田的案例研究

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Oil and gas field developments in the 21st century gained from the benefits of new technologies in reservoir characterization, including: intelligent field data, fine resolution geologic and mega-cell simulation modeling, and super-computing computer clusters. This paper elaborates how these technologies have been fully utilized - in the building of the geologic and simulation models for a giant carbonate oil field - and in understanding well and reservoir behaviors, as well as quantifying inter-reservoir communication between two carbonate reservoirs. The model building process includes: Facimage matrix permeability; fracture characterization; conditioning to dynamic permeability from pressure transient tests and flow-meter profiles; Thomeer function based water saturation distribution; and matching intelligent field well production, injection and pressure data. The fine layers resolution model allows capturing of detailed heterogeneity in wells as well as minimizing the error associated with model upscaling. Use of smart and assisted history matching tools - coupled with the powerful hardware - make possible the use of different discriminators to quickly test the following: possible baffles and barriers, high flow layer and/or local permeability enhancement. These geological features are not easy to map. Matching of numerous intelligent field well production/injection data and pressure improves the reliability of this simulation model. A simulation model that could both reproduce short- and long-term production performance enables a wider application - to support operations and proactive management of the field - as an outcome of utilizing these proven technologies.
机译:21世纪的石油和天然气场发育从储层特征中的新技术的好处获得,包括:智能现场数据,精细分辨率地质和巨型电池仿真建模和超计算计算机集群。本文详细阐述了这些技术如何充分利用 - 在建立巨型碳酸盐油田的地质和仿真模型 - 以及了解井和储层行为,以及量化两种碳酸盐储层之间的储层间通信。模型构建过程包括:Facimage矩阵渗透率;裂缝表征;从压力瞬态测试和流量计型材动态渗透性的调理;基于函数的水饱和分布;并匹配智能现场井生产,注射和压力数据。细层分辨率模型允许在井中捕获详细的异质性,以及最小化与模型Ummaling相关的错误。使用智能和辅助历史匹配工具 - 加上强大的硬件 - 尽可能使用不同的鉴别器来快速测试以下内容:可能的挡板和障碍,高流量层和/或局部渗透性增强。这些地质特征不容易映射。匹配众多智能场井生产/注入数据和压力提高了该模拟模型的可靠性。一种仿真模型,可以复制短期和长期的生产性能,使得更广泛的应用 - 支持该领域的操作和主动管理 - 作为利用这些经过验证技术的结果。

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