Konno M, Patsoukis Dimou A, Suzuki A. Using 3D-printed fracture networks to obtain porosity, permeability, and tracer response datasets.
Data Brief 2023;
47:109010. [PMID:
36909018 PMCID:
PMC9993027 DOI:
10.1016/j.dib.2023.109010]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/14/2023] [Accepted: 02/20/2023] [Indexed: 02/26/2023] Open
Abstract
An in-depth understanding of flow through fractured media is vital to optimise engineering applications, including geothermal energy production, enhanced oil recovery, CO2 storage, and nuclear waste disposal. Advances in 3D-printing technologies have made it possible to generate 3D printed fracture networks with different fracture characteristics. By performing fluid flow experiments in the 3D-printed fractured networks, the impact of the fracture parameters, such as the density, orientation, aperture, dip, and azimuth, on the overall flow can be investigated. This data article contains a detailed description of the framework followed to design fractured networks with different fracture parameters and to create 3D-printed samples, including fracture networks. Furthermore, it contains the experimental protocols used to measure the porosity, permeability, and tracer responses of the 3D-printed samples. The generated datasets provided include geometry data describing the fracture networks, as well as porosity, permeability and tracer response data obtained from flow experiments conducted in the fracture networks.
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