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arXiv 2302.03072cond-mat.soft

模型混合润湿多孔介质中流体-流体驱替的特征:图案、压力与标度

Characteristics of fluid-fluid displacement in model mixed-wet porous media: patterns, pressures, and scalings

Ashkan Irannezhad, Bauyrzhan K. Primkulov, Ruben Juanes, Benzhong Zhao

AI总结:

本文使用动态孔隙网络模型研究混合润湿多孔微模型中的流体驱替特征,发现润湿性比例与接触角的相互作用显著影响低毛细管数下的驱替图案分形维数与注入压力,并提出标度分析可有效预测图案形态变化。

摘要:

我们使用动态孔隙网络模型,通过数值方法研究了简单混合润湿多孔微模型中流体-流体驱替的特征。该多孔微模型由明显的水湿和油湿区域组成,其比例被系统性地改变,以在很宽的毛细管数范围内产生多种驱替图案。我们发现,混合润湿性的影响在低毛细管数下最为显著,并且它取决于润湿性比例和水湿区域固有接触角之间的复杂相互作用。例如,在具有强水湿簇的流动单元中,驱替图案的分形维数是润湿性比例的单调递增函数,但在具有弱水湿簇的流动单元中,它相对于润湿性比例变为非单调的。此外,混合润湿性也体现在注入压力特征上,该特征表现出波动,特别是在低润湿性比例下。具体而言,水湿区域的优先填充导致有效渗透率降低和注入压力升高,即使在极小的毛细管数下也是如此。最后,我们证明基于混合润湿系统整体润湿状态加权平均描述的标度分析,能够有效捕捉观察到的驱替图案形态的变化。

英文摘要:

We study the characteristics of fluid-fluid displacement in simple mixed-wet porous micromodels numerically using a dynamic pore network model. The porous micromodel consists of distinct water-wet and oil-wet regions, whose fractions are systematically varied to yield a variety of displacement patterns over a wide range of capillary numbers. We find that the impact of mixed-wettability is most prominent at low capillary number, and it depends on the complex interplay between wettability fraction and the intrinsic contact angle of the water-wet regions. For example, the fractal dimension of the displacement pattern is a monotonically increasing function of wettability fraction in flow cells with strongly water-wet clusters, but it becomes non-monotonic with respect to wettability fraction in flow cells with weakly water-wet clusters. Additionally, mixed-wettability also manifests itself in the injection-pressure signature, which exhibits fluctuations especially at low wettability fraction. Specifically, preferential filling of water-wet regions leads to reduced effective permeability and higher injection pressure, even at vanishingly small capillary numbers. Finally, we demonstrate that scaling analyses based on a weighted average description of the overall wetting state of the mixed-wet system can effectively capture the variations in observed displacement pattern morphology.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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