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自吸动力网络模型是建立在复杂的薄膜流动、膨胀和流体的自吸跃迁的客观描述基础上的。该模型表明,薄膜膨胀是受毛管力控制的非线性的扩散过程;前缘驱替与跃迁的竞争与速率相关,这就决定了速率与相对渗透率和残余饱和度有关。为了对比目前使用的拟静态模型,模型中跃迁只受接触角控制,动力网络模型把驱替速率作为一种附加的跃迁抑制机理。网络模型用于分析驱替速率、接触角、孔喉比、孔喉形状对相对渗透率的影响。计算的相对渗透率和残余饱和度与实验室对强水湿的贝雷砂岩实测数据进行了对比。驱替速率对特定岩石和湿相影响的程度取决于孔喉比的大小,孔喉比越大,影响程度越高。
The self-priming dynamic network model is based on the objective description of complex thin-film flow, expansion and fluid self-priming transitions. The model shows that the membrane expansion is a nonlinear diffusion process controlled by the capillary force. The competition between frontal displacement and transition is related to the rate, which determines the rate dependent on relative permeability and residual saturation. In order to compare the quasi-static model currently used, the transition in the model is only controlled by the contact angle, and the dynamic network model regards the displacement rate as an additional mechanism of transition suppression. The network model is used to analyze the influence of displacement rate, contact angle, pore throat ratio, pore throat shape on relative permeability. The calculated relative permeability and residual saturation are compared with laboratory data from a strong wet Berea sandstone. The extent to which the displacement rate affects a particular rock and wet phase depends on the pore-to-throat ratio, and the greater the pore-to-wall ratio, the greater the impact.