148 citations · 444 across the 18 of their papers we have counts for
19 papers
The impact of wettability on the co-moving velocity of two-fluid flow in porous media
Fatimah Alzubaidi, James E. McClure, Håkon Pedersen +4
The impact of wettability on the co-moving velocity of two-fluid flow in porous media is analyzed herein. The co-moving velocity, developed by Roy et al. (2022), is a novel represe…
Controlled Ion Transport in the Subsurface: A Coupled Advection-Diffusion-Electromigration System
Kunning Tang, Zhenkai Bo, Zhe Li +5
Groundwater pollution poses a significant threat to environmental sustainability during urbanization. Existing remediation methods like pump-and-treat and electrokinetics have limi…
A pore-scale model for electrokinetic in situ recovery of copper: the Influence of mineral occurrence, zeta potential, and electric potential
Kunning Tang, Zhe Li, Ying Da Wang +4
Electrokinetic in-situ recovery is an alternative to conventional mining, relying on the application of an electric potential to enhance the subsurface flow of ions. Understanding…
DeepAngle: Fast calculation of contact angles in tomography images using deep learning
Arash Rabbani, Chenhao Sun, Masoud Babaei +3
DeepAngle is a machine learning-based method to determine the contact angles of different phases in the tomography images of porous materials. Measurement of angles in 3--D needs t…
Effective permeability of an immiscible fluid in porous media determined from its geometric state
Fatimah Alzubaidi, Peyman Mostaghimi, Yufu Niu +4
Based on the phenomenological extension of Darcy's law, two-fluid flow is dependent on a relative permeability function of saturation only that is process/path dependent with an un…
Relative permeability as a stationary process: energy fluctuations in immiscible displacement
James E. McClure, Ming Fan, Steffen Berg +4
Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work we derive the relative permeability relationship from conservation of e…
A comparative study of paired versus unpaired deep learning methods for physically enhancing digital rock image resolution
Yufu Niu, Samuel J. Jackson, Naif Alqahtani +2
X-ray micro-computed tomography (micro-CT) has been widely leveraged to characterise pore-scale geometry in subsurface porous rock. Recent developments in super resolution (SR) met…
Deep learning of multi-resolution X-Ray micro-CT images for multi-scale modelling
Samuel J. Jackson, Yufu Niu, Sojwal Manoorkar +2
Field-of-view and resolution trade-offs in X-Ray micro-computed tomography (micro-CT) imaging limit the characterization, analysis and model development of multi-scale porous syste…
Universal description of wetting on multiscale surfaces using integral geometry
Chenhao Sun, James McClure, Steffen Berg +2
Hypothesis Emerging energy-related technologies deal with multiscale hierarchical structures, intricate surface morphology, non-axisymmetric interfaces, and complex contact lines w…
Capillary fluctuations and energy dynamics for flow in porous media
James E. McClure, Steffen Berg, Ryan T. Armstrong
Capillary energy barriers have important consequences for immiscible fluid flow in porous media. We derive time-and-space averaging theory to account for non-equilibrium behavior a…
Thermodynamics of fluctuations based on time-and-space averages
James E. McClure, Steffen Berg, Ryan T. Armstrong
We develop non-equilibrium theory by using averages in time and space as a generalized way to upscale thermodynamics in non-ergodic systems. The approach offers a classical perspec…
Characterization of wetting using topological principles
Chenhao Sun, James E. McClure, Peyman Mostaghimi +5
Hypothesis Understanding wetting behavior is of great importance for natural systems and technological applications. The traditional concept of contact angle, a purely geometrical…
ML-LBM: Machine Learning Aided Flow Simulation in Porous Media
Ying Da Wang, Traiwit Chung, Ryan T. Armstrong +1
Simulation of fluid flow in porous media has many applications, from the micro-scale (cell membranes, filters, rocks) to macro-scale (groundwater, hydrocarbon reservoirs, and geoth…
Physical Accuracy of Deep Neural Networks for 2D and 3D Multi-Mineral Segmentation of Rock micro-CT Images
Ying Da Wang, Mehdi Shabaninejad, Ryan T. Armstrong +1
Segmentation of 3D micro-Computed Tomographic uCT) images of rock samples is essential for further Digital Rock Physics (DRP) analysis, however, conventional methods such as thresh…
Linking continuum-scale state of wetting to pore-scale contact angles in porous media
Chenhao Sun, James E. McClure, Peyman Mostaghimi +4
Wetting phenomena play a key role in flows through porous media. Relative permeability and capillary pressure-saturation functions show a high sensitivity to wettability, which has…
Boosting Resolution and Recovering Texture of micro-CT Images with Deep Learning
Ying Da Wang, Ryan T. Armstrong, Peyman Mostaghimi
Digital Rock Imaging is constrained by detector hardware, and a trade-off between the image field of view (FOV) and the image resolution must be made. This can be compensated for w…
Geometric evolution as a source of discontinuous behavior in soft condensed matter
James E. McClure, Steffen Berg, Ryan T. Armstrong
Geometric evolution represents a fundamental aspect of many physical phenomena. In this paper we consider the geometric evolution of structures that undergo topological changes. To…
Super Resolution Convolutional Neural Network Models for Enhancing Resolution of Rock Micro-CT Images
Ying Da Wang, Ryan Armstrong, Peyman Mostaghimi
Single Image Super Resolution (SISR) techniques based on Super Resolution Convolutional Neural Networks (SRCNN) are applied to micro-computed tomography (μCT) images of sandstone a…
A geometric state function for two-fluid flow in porous media
James E. McClure, Ryan T. Armstrong, Mark A. Berrill +4
Models that describe two-fluid flow in porous media suffer from a widely-recognized problem that the constitutive relationships used to predict capillary pressure as a function of…