Understanding flow mechanisms in fractured media is essential for geoscientific research and geological development industries. This study used 3‐D printed fracture networks in order to control the properties of fracture distributions inside the sample. The accuracy and appropriateness of creating samples by the 3‐D printer was investigated by using a X‐ray CT scanner. The CT scan images suggest that the 3‐D printer is able to reproduce complex three‐dimensional spatial distributions of fracture networks. Use of hexane after printing was found to be an effective way to remove wax for the posttreatment. Local permeability was obtained by the cubic law and used to calculate the global mean. The experimental value of the permeability was between the arithmetic and geometric means of the numerical results, which is consistent with conventional studies. This methodology based on 3‐D printed fracture networks can help validate existing flow modeling and numerical methods.

Topological data analysis is an emerging concept of data analysis for characterizing shapes. A state-of-the-art tool in topological data analysis is persistent homology, which is expected to summarize quantified topological and geometric features. Although persistent homology is useful for revealing the topological and geometric information, it is difficult to interpret the parameters of persistent homology themselves and difficult to directly relate the parameters to physical properties. In this study, we focus on connectivity and apertures of flow channels detected from persistent homology analysis. We propose a method to estimate permeability in fracture networks from parameters of persistent homology. Synthetic 3D fracture network patterns and their direct flow simulations are used for the validation. The results suggest that the persistent homology can estimate fluid flow in fracture network based on the image data. This method can easily derive the flow phenomena based on the information of the structure.