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On the development of a relative permeability equation of state

机译:关于相对渗透率状态方程的发展

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Standard compositional simulators use composition-dependent cubic equations of state (EoS), but saturation-dependent relative permeability and capillary pressure. This discrepancy causes discontinuities, increasing computational time and reducing accuracy. In addition, commonly used empirical correlations, such as the Corey relative permeability model, show a sole dependence of relative permeability on phase saturation, lumping the effect of other pore-scale phenomena into one tuning exponent. To rectify this problem, relative permeability has been recently defined as a state function, so that it becomes compositional dependent and single valued. Such a form of the relative permeability EoS can significantly improve the convergence in compositional simulation for both two- and three-phase flows. This paper revisits the recently developed EoS for relative permeability by defining relevant state variables and deriving functional forms of the partial derivatives in the state function. The state variables include phase saturation, phase connectivity, wettability index, capillary number, and pore topology. The developed EoS is constrained to key physical boundary conditions. The model coefficients are estimated through linear regression on data collected from a pore-scale simulation study that estimates relative permeability based on micro-CT image analysis. The results show that a simple quadratic expression with few calibration coefficients gives an excellent match to two-phase flow simulation measurements from the literature. The goodness of fit, represented by the coefficient of determination (R~2) value, is 0.97 for relative permeability at variable phase saturation and phase connectivity, and constant wettability, pore structure, and capillary number (~ 10~(-4)). The quadratic response for relative permeability also shows excellent predictive capabilities.
机译:标准的成分模拟器使用成分依赖的状态立方方程(EoS),但使用饱和度相关的相对渗透率和毛细管压力。这种差异会导致不连续性,从而增加计算时间并降低准确性。此外,常用的经验相关性(例如Corey相对渗透率模型)显示出相对渗透率对相饱和度的唯一依赖关系,将其他孔隙尺度现象的影响归纳为一个调整指数。为了解决这个问题,最近将相对磁导率定义为状态函数,以使它成为成分相关的且具有单一值。这种形式的相对渗透率EoS可以显着改善两相和三相流组成模拟中的收敛性。本文通过定义相关状态变量并推导状态函数中偏导数的函数形式,对最近开发的相对渗透率EoS进行了回顾。状态变量包括相饱和度,相连接性,润湿性指数,毛细管数和孔拓扑。所开发的EoS仅限于关键的物理边界条件。通过对根据微CT图像分析估算相对渗透率的孔隙度模拟研究收集的数据进行线性回归,可以估算模型系数。结果表明,具有很少校正系数的简单二次表达式可以很好地匹配文献中的两相流模拟测量结果。用确定系数(R〜2)表示的拟合优度是可变相饱和度和相连接性以及恒定的润湿性,孔结构和毛细管数(〜10〜(-4))下的相对渗透率的0.97。 。相对渗透率的二次响应也显示出出色的预测能力。

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