首页> 外文期刊>Journal of Multiscale Modelling >COUPLING MULTIPHASE PORE-SCALE MODELS TO ACCOUNT FOR BOUNDARY CONDITIONS: APPLICATION TO 2D QUASI-STATIC PORE NETWORKS
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COUPLING MULTIPHASE PORE-SCALE MODELS TO ACCOUNT FOR BOUNDARY CONDITIONS: APPLICATION TO 2D QUASI-STATIC PORE NETWORKS

机译:耦合多相孔尺度模型以解决边界条件:在二维准静态孔网络中的应用

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摘要

Accurate predictions of macroscopic multiphase flow properties (relative permeability and capillary pressure) are necessary for modeling flow and transport in subsurface applications, such as hydrocarbon recovery, carbon sequestration and nuclear waste storage. These properties are usually measured experimentally, but pore-scale network modeling has become an efficient alternative for understanding fundamental flow behavior and predicting macroscopic properties. In many cases, network modeling gives excellent agreement with experiment by using models physically representative of real media. Void space within a rock sample can be extracted from high resolution images and converted to a topologically equivalent network of pores and throats. Multiphase fluid transport is then modeled in the network and macroscopic properties extracted from the model. Advancements continue to be made in making multiphase network models (both qua-sistatic and dynamic) predictive, but one limitation is that arbitrary (e.g., constant pressure) boundary conditions are usually assumed; they do not reflect the local saturations and pressure distributions that are affected by flow and transport in the surrounding media. In this work we demonstrate that transport behavior at the pore scale, and therefore, upscaled macroscopic properties are directly affected by the boundary conditions. Pore-scale drainage in 2D quasi-static networks is modeled by direct coupling to other pore-network models so that the boundary conditions reflect local variations of transport behavior in the surrounding media. Phase saturations are coupled at model boundaries to ensure continuity between adjacent models. Macroscopic petrophysical properties are shown to be largely dependent upon the surrounding media, which are manifested in the form of boundary conditions. The predictive ability of network simulations is thus improved using the novel network coupling scheme.
机译:宏观预测多相流动特性(相对渗透率和毛细压力)对于建模地下应用中的流动和运输(例如碳氢化合物回收,碳固存和核废料存储)是必要的。这些性质通常是通过实验测量的,但是孔尺度网络建模已成为理解基本流动行为和预测宏观性质的有效替代方法。在许多情况下,通过使用物理上代表真实媒体的模型,网络建模可以很好地与实验保持一致。可以从高分辨率图像中提取岩石样品中的空隙空间,并将其转换为孔隙和喉部的拓扑等效网络。然后在网络中对多相流体传输进行建模,并从模型中提取宏观属性。在使多相网络模型(准静态和动态)可预测方面继续取得进展,但是一个局限性是通常假定任意(例如恒压)边界条件。它们没有反映受周围介质中的流动和传输影响的局部饱和度和压力分布。在这项工作中,我们证明了在孔尺度上的传输行为,因此,高阶宏观性质直接受边界条件的影响。通过直接耦合到其他孔隙网络模型对二维准静态网络中的孔隙水排放进行建模,以便边界条件反映周围介质中运输行为的局部变化。相饱和度在模型边界处耦合,以确保相邻模型之间的连续性。宏观的岩石物理特性显示出很大程度上取决于周围的介质,这些介质以边界条件的形式表现出来。因此,使用新颖的网络耦合方案可以提高网络仿真的预测能力。

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