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A permeability prediction method based on pore structure and lithofacies

机译:一种基于孔隙结构和岩型的渗透性预测方法

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Permeability prediction using linear regression of porosity always has poor performance when the reservoir with complex pore structure and large variation of lithofacies. A new method is proposed to predict permeability by comprehensively considering pore structure, porosity and lithofacies. In this method, firstly, the lithofacies classification is carried out using the elastic parameters, porosity and shear frame flexibility factor. Then, for each lithofacies, the elastic parameters, porosity and shear frame flexibility factor are used to obtain permeability from regression. The permeability prediction test by logging data of the study area shows that the shear frame flexibility factor that characterizes the pore structure is more sensitive to permeability than the conventional elastic parameters, so it can predict permeability more accurately. In addition, the permeability prediction is depending on the precision of lithofacies classification, reliable lithofacies classification is the precondition of permeability prediction. The field data application verifies that the proposed permeability prediction method based on pore structure parameters and lithofacies is accurate and effective. This approach provides an effective tool for permeability prediction.
机译:使用线性回归孔隙率的渗透性预测总是在储层具有复杂的孔隙结构和岩散的大变化时具有差的性能。提出了一种新方法,以通过全面考虑孔隙结构,孔隙度和岩型来预测渗透性。在该方法中,首先,使用弹性参数,孔隙率和剪切框架柔性因子进行锂外分类。然后,对于每个锂外,弹性参数,孔隙率和剪切框架柔韧性因子用于获得回归的渗透性。研究区域的测井数据的渗透性预测测试表明,剪切框架柔韧性因子表征孔结构的渗透性比传统弹性参数更敏感,因此它可以更准确地预测渗透率。此外,渗透性预测取决于岩散分类的精度,可靠的锂外分类是渗透预测的前提。现场数据应用验证了基于孔隙结构参数和锂外的所提出的渗透预测方法是准确的,有效的。该方法提供了一种有效的渗透性预测工具。

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