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Integration of Discrete Feature Network Methods with Conventional Simulator Approaches

机译:离散特征网络方法与常规模拟器方法的集成

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The discrete feature network (DFN) approach offers many key advantages over conventional dual porosity (DP) approaches, particularly when issues of conectivity dominate recovery and reservoir stimulation in fractured and heterogeneous reservoirs. DP models have been developed for complex multiphase and thermal effects, and have been implemented for basin scale modeling. However, DP models address only the dual porosity nature of fractured reservoirs, generally simplifying connectivity and scale-dependent heterogeneity issues which are modeled efficiently and more accurately by the DFN approach. This paper describes the development of techniques to integrate DFN and DP approaches. These techniques allow the analyst to maintain many of the advantages of the DP simulator approach without losing the realism of complex fracture system geometry and connectivity, as captured by DFN models. The techniques described are currently used within a DOE funded research project for linking a DFN and a DP thermal simulation model for the Yates Field, Texas. The paper describes some of the geological and engineering aspects of the Yates Field and gives two examples how DP parameters for the thermal simulation can be derived using DFN modeling techniques.
机译:离散特征网络(DFN)方法比常规的双重孔隙度(DP)方法具有许多关键优势,特别是当隐性问题主导着裂缝性和非均质油藏的采收率和油藏增产时。已为复杂的多相和热效应开发了DP模型,并已将其用于盆地尺度建模。但是,DP模型仅解决了裂缝性储层的双重孔隙性质,通常简化了连通性和与比例有关的非均质性问题,这些问题已通过DFN方法得以有效且更准确地建模。本文介绍了将DFN和DP方法集成在一起的技术的发展。这些技术使分析人员能够保留DP仿真器方法的许多优点,而不会失去DFN模型所捕获的复杂裂缝系统几何形状和连通性的真实性。所描述的技术目前在美国能源部(DOE)资助的研究项目中使用,用于将DFN和DP热模拟模型链接到德克萨斯州的Yates油田。本文描述了Yates油田的一些地质和工程方面,并给出了两个示例,如何使用DFN建模技术得出用于热模拟的DP参数。

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