Transport in Porous Media最新文献

We present a new, computationally efficient, and massively parallelized pore-network modeling (PNM) platform, referred to as the loosely-coupled dynamic PNM (LCD-PNM). To the best of our knowledge, this study introduces the first dynamic PNM framework that is capable of performing physics-based pore-scale simulations of two-phase flow processes in large-scale disordered pore networks under a wide range of fluid properties, wettability scenarios, and flow conditions. To validate the LCD-PNM platform, we perform primary drainage and waterflooding simulations under both water-wet and mixed-wet conditions on equivalent pore networks of Berea and Bentheimer sandstone miniature core plugs. We then compare the oil and water relative permeability and oil recovery curves predicted under steady-and unsteady-state simulations against their experimental counterparts. The pore networks have been extracted in a seamless and deterministic manner from micro-CT images of the entire core sample. For comparison, we also present the relative permeability predictions obtained from quasi-static PNM simulations to highlight the improvements we observe in the LCD-PNM results, such as more accurate predictions of oil breakthrough and relative permeability curves during the primary drainage processes. In our analysis, we find the dynamic simulation results to be in close agreement with experimental data. Additionally, we employ the LCD-PNM to investigate the effects of wettability and flow conditions on oil and water relative permeabilities and remaining oil saturation. To this end, we investigate different displacement flow regimes including viscous fingering, capillary fingering, and stable front displacement by adjusting injection flow rate and fluid viscosity ratio. The simulation results provide invaluable insights into the complex interplay between the viscous and capillary forces that controls pore-scale displacements and ultimately influences the macroscopic behavior of two-phase flow processes.

We present a novel and efficient pore-network extraction (PNE) platform that utilizes a seamless merging algorithm to extract core-sized pore networks directly from high-resolution segmented micro-computed tomography images of rock samples. This platform has the distinct advantage of being parallel friendly, allowing the entire computational workload of the extraction process to be distributed across multiple compute nodes. The superior computational efficiency of this approach paves the way for the extraction of deterministic pore networks with physical dimensions that are comparable to those of core samples employed in conventional core-flooding experiments. Sensitivity analysis studies are performed on digital replicates of Berea and Bentheimer sandstone rock samples. To illustrate the role of a user-defined adjustment coefficient on the extraction process, a set of conventional-sized pore networks are extracted and analyzed for both rock samples. To ascertain the quality of these pore networks, comparisons are made with equivalent pore networks extracted using a well-characterized open-source pore-network extractor. After rigorous examination of these conventional-sized pore networks, the validated PNE platform is applied to extract miniature-core-sized pore networks, and their relevant statistics and petrophysical properties are presented. In addition, these networks are extensively utilized in both quasi-static and dynamic pore-network modeling (PNM) simulations of two-phase flow processes. The predicted two-phase flow properties of the rock samples are benchmarked against the corresponding experimental data and the results are presented in both the current and the second volume of this work.

The relative performance of H₂O and sCO₂ as geothermal working fluids (GWFs) in liquid-dominated enhanced geothermal systems (EGSs) was investigated in this study. Such systems rely on the injection of GWFs (geothermal working fluids) to sustain geothermal energy recovery, which is dominated by conduction-based heat exchange from the rock to the GWF in the hydraulic fracture. H₂O is currently the only GWF considered for EGS operations, but supercritical CO₂ has been proposed as a potential GWF because of its lower density and viscosity, which lead to the hypothesis of potentially significant thermal energy recovery. However, H₂O appears to have an initial advantage because of its significantly higher thermal conductivity. We compared the performance of H₂O and SCO₂ as GWFs in a 3D stencil (minimum repeatable element) of an EGS involving a hydraulic fracture connecting the injection and the production wells, the main body of the EGS rock that provides the heat source, and boundaries that are sufficiently distant from the main body of the main body of the rock to maintain constant pressure and temperature conditions over a 30-year period of EGS operations In our studies we considered variations in the initial reservoir temperature, in the injection method (at a constant-rate and at a constant bottomhole pressure) and in the reservoir permeability, in an effort (a) not only to compare the EGS performance of H₂O and sCO₂ as GWFs but also (b) to determine the conditions (if any) under which sCO₂ can be more effective than H₂O. The results of the study indicated the overwhelming superiority of H₂O as a GWF under any and all of the conditions covered by the study, producing fluids at dependably much higher temperatures and yielding invariably drastically higher energy recovery than sCO₂ despite the consistently higher GWF injection and production rates attained with sCO₂.

The purpose of this paper is to describe the stead MHD mixed convection flow over a permeable vertical flat plate embedded in a Darcy–Forchheimer porous medium. Using appropriate similarity variables, the partial differential equations are transformed into ordinary (similar) differential equations, which are numerically solved using the bvp4c function in MATLAB. The numerical results are used to present graphically and in tables, illustrations of the reduced skin friction, reduced Nusselt number, velocity, and temperature profiles. Dual (upper and lower branch) solutions are discovered in this exciting analysis. Although numerous studies on the mixed convection past a vertical plate embedded in a fluid-saturated porous medium exist, none of the researchers have focused on the Darcy–Forchheimer flow with asymptotic solutions. The behavior of the flow and heat transfer has been thoroughly analyzed with the variations in governing parameters, such as Darcy–Forchheimer (G,) suction/injection (S), MHD (M,) and mixed convection (lambda) parameters.

Nuclear magnetic resonance (NMR) techniques are key in the study of porous reservoir rocks. They can provide valuable insight into the pore size distribution of the pore space of a given rock sample due to its dependence on the magnetic fluid/matrix interaction. The pore space is often studied at the μm scale through the use of micro-CT images, which are often composed of hundreds of millions of voxels, posing significant challenges to numerical simulations. In this paper, we present an image-based, fully explicit, and matrix-free finite element implementation for the simulation of NMR relaxation process that is capable of handling such large 3D problems in single GPUs. The chosen explicit time-integration scheme uses a lumped capacitance formulation and stabilization via hyperbolization, and it is capable of handling arbitrary time-step sizes with controllable error levels. The image-based representation of the pore space is used for a memory-efficient, matrix-free formulation of the time integration using massively parallel processes on a single GPU. In addition, we propose the substitution of a global digital roughness correction factor that depends on the porous space’s geometry for a problem-independent local correction factor, based on nodal neighborhoods. We show that the numerical scheme converges with successive refinements as expected and that our local correction coefficient is capable of estimating the correct S/V parameter of several different classical geometries. We tested our formulation against an image-based Random Walk simulation of four digital rock core samples, achieving good agreement between them. We manage to simulate a giga-voxel image-based model on a personal use GPU (less than 10GB of memory use) in 33 min with our FEM implementation.

Highlights

In this study, we present a successful application of the Computational Fluid Dynamics–Discrete Element Method (CFD–DEM) for simulating the complex phenomenon of multi-particle arch formation within high-concentration packed-bed environments. We investigate the roles of physical forces in this phenomenon, shedding light on aspects that are challenging to explore through experimentation. Our research is motivated by the desire to comprehend the conditions and parameters influencing the formation, stability, disruption, and reformation of multi-particle sand arches within filter openings. This arching phenomenon serves as an efficient particle retention mechanism, particularly in heavy oil production wells. We delve into factors like particle size, shape, and particle size distribution that may impact multi-particle arch performance. Additionally, we explore the physics behind multi-particle arching by examining the effects of various physical forces on arch performance. Utilizing a Computational Fluid Dynamics–Discrete Element Model, we investigate the multi-particle arching phenomenon under steady-state flow conditions in packed-bed environments. Our approach employs the unresolved coupling method in STAR-CCM+ (Siemens PLM). We test various filter slot geometries, including straight slots, keystone slots, wire-wrapped screens (WWS), and seamed slots, all under laminar flow conditions. Our findings highlight the significance of gravity, inter-particle forces, and interactions between the filter wall and the particles in multi-particle arch formation at both the slot opening and microscale levels. We confirm that a multi-particle arch can be formed within a specific slot width. Interestingly, while maintaining a constant slot width, we observe that the slot length has an insignificant effect on multi-particle arch formation and stability. In summary, our CFD–DEM model successfully simulates and predicts multi-particle arch formation, stabilization, breakage, and reformation, allowing for comprehensive testing of the effects of various parameters. This research offers valuable insights into a complex phenomenon that is crucial in packed-bed filtration systems.

The co-moving velocity is a new variable in the description of immiscible two-phase flow in porous media. It is the saturation-weighted average over the derivatives of the seepage velocities of the two immiscible fluids with respect to saturation. Based on analysis of relative permeability data and computational modeling, it has been proposed that the co-moving velocity is linear when plotted against the derivative of the average seepage velocity with respect to the saturation, the flow derivative. I show here that it is enough to demand that the co-moving velocity is characterized by an additive parameter in addition to the flow derivative to be linear. This has profound consequences for relative permeability theory as it leads to a differential equation relating the two relative permeabilities describing the flow. I present this equation together with two solutions.

We consider a cross-sectional study of immiscible displacement under the influence of gravity, anisotropic permeability, and capillary effects. We propose the similarity criteria characterizing the relative role of these effects and qualitatively different flows. We present a classification of the flow regimes in four limiting cases of the displacement. The recovery and sweep efficiencies in such cases can be compromised by the gravity override, channeling, and coning effects. In the phase plane, we constrain the parameter ranges at which these effects become relevant. We then aim at evaluating the range of the similarity criteria characterized by the maximum efficiencies and describe the placements of horizontal wells allowing to reach these maxima. We show that the placement of the producing well is generally more relevant. In the limiting cases, the variety of placements can be merged in groups by their efficiencies. We eventually come up with the maps of the maximal efficiencies and associated placements allowing for a quick assessment of the optimal injection scenarios. The proposed classification of the flow regimes and the calculated maps can be useful in evaluating various scenarios of waterflooding and gas injection.

The rate of oxygen diffusion directly affects the distribution of oxygen concentration within concrete, which in turn influences the corrosion performance of reinforcing steel within the concrete. However, research on cross-scale prediction models for oxygen diffusion in dry concrete is still lacking. In this study, the complex pore structure of concrete is simplified into a sponge model, and three types of diffusion are quantitatively characterized based on the pore size distribution density function. The influence of porosity, water–cement ratio, hydration degree, gel–space ratio and pore tortuosity on the oxygen diffusion coefficient is considered, and a cross-scale prediction model for oxygen diffusion in dry concrete is established. Secondly, an oxygen diffusion coefficient determination device developed independently is used to measure the oxygen diffusion coefficient of concrete specimens under dry conditions. The results show that the experimental values agree well with the calculated values, and the model is compared with other models proposed by scholars, verifying its superiority and accuracy. Finally, a parameter sensitivity analysis is conducted on five microscale parameters and their influence on the behavior of oxygen transmission into concrete is discussed. The establishment of the cross-scale prediction model for oxygen diffusion in dry concrete will first provide a positive role in the theoretical research on reinforcement expansion and cracking, and secondly, it will be able to better explain the mechanism of oxygen diffusion in concrete.