Prediction of the inertial permeability of a 2D single rough fracture based on geometric information

The apparent permeability of a single rough fracture undergoes complex evolution in a non-Darcy flow regime, making description of the nonlinear flow challenging. The inertial permeability can be used to effectively solve this problem but is very sensitive to the geometric information and difficult to determine directly. Here, a model for predicting the inertial permeability is proposed by considering the geometric information of rough rock fractures. A massive training database of nonlinear flow in single rough fractures was built based on direct numerical simulations. The database consists of 1225 fractures and contains 12 geometric parameters, including 9 morphological and 3 aperture parameters. To predict the inertial permeability, four geometric parameters highly correlated with the inertial permeability were selected by correlation analysis. A robust prediction model was then established based on the support vector machine theory and the artificial bee colony algorithm. Forty-five fractures constructed from Barton's profiles were used to verify the model performance. The validation results show that the proposed method can accurately predict the inertial permeability based on the geometric information of rough fractures. Finally, the proposed prediction model was used to determine the critical Reynolds number.