断裂碳酸盐岩储层 DPDP-DFN 混合建模的应用

Nikolay Shevko, Vil Shaislamov, O. Savelev
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引用次数: 1

摘要

预测天然断裂碳酸盐岩储层的行为与两种或多种介质的流体流动模型有关。高导断层和裂缝的存在使这一过程变得更加复杂。这些复杂性一般通过使用 DPDP 模型和现代显式离散裂缝网络(DFN)建模技术的常用方法来解决。如果不进行重大修改和改进,双孔隙度-双渗透率(DPDP)模型无法提供正确的结果。在全尺寸模型上以离散形式对整个断裂集进行流动模拟,计算量大,耗时长,因此不适用于实际目的。在详细的静态地质模型基础上,将单个 DFN 对象(断层和长裂缝)与传统的 DPDP 模型相结合,创建了另一种混合建模方法。所有可用的地质、地球物理和生产数据都被用来为流动模拟提供背景资料。对三种介质的数值算法进行了优化,包括单孔介质(SPM)、裂缝介质(DFN)以及代表不规则断层和长裂缝系统的离散对象。本文介绍了创建静态模型、定义断裂带和显式离散对象的通用工作流程,以及 DPDP-DFN 混合建模。所提出的方法被用于进行全尺寸模型历史匹配、优化井位、估算注气效率的风险和不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Hybrid DPDP-DFN Modeling of Fractured Carbonate Reservoirs
Predicting naturally fractured carbonate reservoir behavior is associated with fluid flow modeling of two and more mediums. Presence of highly conductive faults and fractures complicates the process. These complications are generally addressed by common approaches using DPDP models and modern techniques of explicit discrete fracture networks (DFN) modeling. Dual porosity-dual permeability (DPDP) models do not provide proper results without significant modifications and improvements. Flow simulation of the whole fracture set in discrete format on full-scale models is computationally intensive and time-consuming task thus not applicable for practical purposes. Alternative hybrid modeling approach based on combination of individual DFN objects (faults and long fractures) with traditional DPDP modeling was created based on detailed geological static model. Full scope of available geological, geophysical and production data was used to provide background for flow simulations. Numeric algorithms were optimized for three mediums including single porosity medium (SPM), fracture medium (DFN) and discrete objects representing irregular fault and long fracture systems. Generalized workflows for creating static model, defining fractured zones and explicit discrete objects, followed by DPDP-DFN hybrid modeling are described in this paper. The proposed approach was utilized to perform full-scale model history matching, optimize well locations, estimate risks and uncertainties of gas injection efficiency.
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