石油工程
多相流
储层模拟
油页岩
线性化
离散化
非常规油
致密气
达西定律
水库工程
流量(数学)
流体力学
地质学
计算机科学
页岩气
多孔介质
水力压裂
石油
多孔性
机械
岩土工程
非线性系统
数学
古生物学
数学分析
物理
量子力学
出处
期刊:Journal of Energy Resources Technology-transactions of The Asme
[ASM International]
日期:2020-03-30
卷期号:142 (10)
被引量:19
摘要
Abstract Conventional hydrocarbon reservoirs, from an engineering and economic standpoint, are the easiest and most cost-efficient deposits to develop and produce. However, as economic deposits of conventional oil/gas become scarce, hydrocarbon recovered from tight sands and shale deposits will likely fill the void created by diminished conventional oil and gas sources. The purpose of this paper is to review the numerical methods available for simulating multiphase flow in highly fractured reservoirs and present a concise method to implement a fully implicit, two-phase numerical model for simulating multiphase flow, and predicting fluid recovery in highly fractured tight gas and shale gas reservoirs. The paper covers the five primary numerical modeling categories. It addresses the physical and theoretical concepts that support the development of numerical reservoir models and sequentially presents the stages of model development starting with mass balance fundamentals, Darcy’s law and the continuity equations. The paper shows how to develop and reduce the fluid transport equations. It also addresses equation discretization and linearization, model validation and typical model outputs. More advanced topics such as compositional models, reactive transport models, and artificial neural network models are also briefly discussed. The paper concludes with a discussion of field-scale model implementation challenges and constraints. The paper focuses on concisely and clearly presenting fundamental methods available to the novice petroleum engineer with the goal of improving their understanding of the inner workings of commercially available black box reservoir simulators. The paper assumes the reader has a working understanding of flow a porous media, Darcy’s law, and reservoir rock and fluid properties such as porosity, permeability, saturation, formation volume factor, viscosity, and capillary pressure. The paper does not explain these physical concepts neither are the laboratory tests needed to quantify these physical phenomena addressed. However, the paper briefly addresses these concepts in the context of sampling, uncertainty, upscaling, field-scale distribution, and the impact they have on field-scale numerical models.
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