一种基于Kozeny-Carmen方程改进的渗透率预测新方法

A New Method for Predicting Permeability Based on Modified Kozeny-Carmen Equation

在计算复杂孔隙结构储层渗透率时,常规采用的孔渗指数方法或流动单元分类方法几乎很难准确评价渗透率。针对这一问题,本文提出一种引入修正迂曲度因子的改进的Kozeny-Carmen方程渗透率计算新方法。首先引入迂曲度因子修正Kozeny-Carmen方程,迂曲度因子可以表达为孔隙度与岩电参数的函数;然后对改进的Kozeny-Carmen方程进行推演变换,得到新的流动单元指数,能够更好地将储层进行分类;最后利用自适应神经模糊推理系统建立取心段岩心渗透率与测井曲线的模型,并将此模型应用到非取心段的渗透率评价中。岩心渗透率与预测渗透率的对比验证了该方法的正确性与有效性,且渗透率计算精度较常规孔渗指数方法和流动单元分类方法有较大提高。该方法在南海西部海域莺歌海盆地东方气田储层评价中应用效果良好。

In the calculation of reservoir permeability of complex pore structure, it is very difficult to accurately evaluate the permeability. To solve this problem, this paper presents a new method to improve the calculation of permeability based on the Kozeny-Carmen equation by introducing the modified tortuosity factor. Firstly, the Kozeny-Carmen equation is modified by adding the tortuosity factor, which can be expressed as a function of porosity and electrical parameters; then the modified Kozeny-Carmen equation is deduced and transformed to get the new flow unit index for better reservoir classification; finally, a model of core premeability and log curve of coring and logging section using adaptive permeab permeab is much neural fuzzy inference system, and this model is applied to the non-coring section in ility evaluation. The correctness and effectiveness of the method is verified by comparing the ility of the core and the predicted permeability, and the accuracy of the permeability calculation classification er than both that of the conventional porosity exponential method and the flow unit method. This method has good effects in the gas reservoir evaluation of Yinggehai basin east in western South China Sea.