Special Issue "Modeling and Simulation of Fluid flows in Fractured Porous Media: Current Trends and Prospects"

Submission Deadline: 30 June 2020 (closed)
Guest Editors
Dr. Richeng Liu, China University of Mining and Technology, China
Prof. Yujing Jiang, Nagasaki University, Japan
Dr. Qian Yin, China University of Mining and Technology, China

Summary

Understanding the fluid flow mechanisms in fractured porous media plays an important role in many engineering activities, such as nuclear waste disposal, geothermal energy extraction, oil and natural gas production, as well as performance and safety of underground projects including coal mines and tunnels. In recent years, many methods including numerical simulation, laboratory experiment, and theoretical analysis have been employed to investigate the flow process and permeability response of rock fractures, from kilometer scale to microscale. However, the rocks/coals are in deep underground that is very complex and exists some uncertainties. Therefore, new numerical simulation methods and deep explanations of fluid flow behaviors in fractured porous media are still needed.

This special issue aims at presenting recent advances in studies on the 3D fracture network reconstruction, fluid flow modeling and permeability estimation of rock fractures. We invite you to submit comprehensive review papers and original articles. 

Potential topics include but are not limited to the following:

• Intelligent and secure face recognition system in Smart Cities

• Reconstruction of 3D rock fractures and permeability estimation

• Fluid flow and solute transport in fractured porous media

• Flow regime transition modeling in complicated fracture networks

• Usages of 3D printing, micro-CT scanning and scanning electron microscope (SEM) techniques

• Fracture shear behavior and shear-flow process

• Effects of thermal treatment on dynamic and physical properties of rocks

• Stability control modeling of underground surrounding rocks



Published Papers


  • Shear Induced Seepage and Heat Transfer Evolution in a Single-Fractured Hot-Dry-Rock
  • Abstract In the enhanced geothermal system (EGS), the injected fluid will induce shear sliding of rock fractures (i.e., hydroshearing), which consequently, would increase the fracture aperture and improve the heat transfer efficiency of the geothermal reservoir. In this study, theoretical analysis, experimental research and numerical simulation were performed to uncover the permeability and heat transfer enhancement mechanism of the Hot-Dry-Rock (HDR) mass under the impact of shearing. By conducting the direct shear test with the fractured rock samples, the evolution process of fracture aperture during the shearing tests was observed, during which process, cubic law was adopted to depict the rock… More
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  • Thermal Analysis of MHD Non-Newtonian Nanofluids over a Porous Media
  • Abstract In the present research, Tiwari and Das model are used for the impact of a magnetic field on non-Newtonian nanofluid flow in the presence of injection and suction. The PDEs are converted into ordinary differential equations (ODEs) using the similarity method. The obtained ordinary differential equations are solved numerically using shooting method along with RK-4. Part of the present study uses nanoparticles (NPs) like TiO2 and Al2O3 and sodium carboxymethyl cellulose (CMC/water) is considered as a base fluid (BF). This study is conducted to find the influence of nanoparticles, Prandtl number, and magnetic field on velocity and temperature profile, however,… More
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  • Prediction of Permeability Using Random Forest and Genetic Algorithm Model
  • Abstract Precise recovery of Coalbed Methane (CBM) based on transparent reconstruction of geological conditions is a branch of intelligent mining. The process of permeability reconstruction, ranging from data perception to real-time data visualization, is applicable to disaster risk warning and intelligent decision-making on gas drainage. In this study, a machine learning method integrating the Random Forest (RF) and the Genetic Algorithm (GA) was established for permeability prediction in the Xishan Coalfield based on Uniaxial Compressive Strength (UCS), effective stress, temperature and gas pressure. A total of 50 sets of data collected by a self-developed apparatus were used to generate datasets for… More
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