Abstract
Fractures widely present in the subsurface and play a critical role in the fluid flow processes in porous media. The Fracture Pipe Network Model (FPNM) is an efficient method to represent and calculate fluid flow properties as a particular part of Discrete Fracture Networks (DFNs) method compared to direct numerical simulations. However, the current FPNM formulation can result in large deviations in computed fluid flow properties when applied to complex interconnected DFNs, although it can produce good results for simple DFNs. To enhance the performance and versatility of current FPNMs, four modifications to the FPNM formulation are introduced from different perspectives to improve the accuracy of pipe conductance assignment and ensure the correct topology of the fracture network. Two benchmarking examples with complex interconnected fractures and two real fractured samples are presented and the results show the modifications significantly improve the accuracy of computed fluid flow properties in complex DFNs.
Original language | English |
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Article number | e2020WR029450 |
Number of pages | 15 |
Journal | Water Resources Research |
Volume | 58 |
Issue number | 3 |
Early online date | 26 Feb 2022 |
DOIs | |
Publication status | Published - 1 Mar 2022 |
Bibliographical note
AcknowledgmentsChenhui Wang thanks the financial support from China Scholarship Council (CSC) for his Ph.D. study. The authors thank the discussions of the real-world case study with Dr Yu Jing at the University of New South Wales.
Open access via Wiley agreement
Data Availability Statement
For the data availability, the data that support the findings of this research are available in Mendeley data repository (Wang, 2020). All of the parameters of the DFNs (the coordinates, the aperture of the DFNs) used are available in http://dx.doi.org/10.17632/c8r645tj9v.2.Keywords
- discrete fracture network
- fracture pipe network model
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Improvements to the fracture pipe network model for complex 3D discrete fracture networks
Wang, C. (Creator), Wang, C. (Creator) & Wu, K. (Supervisor), Mendeley, 15 Dec 2020
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