Добірка наукової літератури з теми "Dual-scale flow simulation"

Summary Thermal-reactive compositional-flow simulation in porous media is essential to model thermal-oil-recovery processes for extraheavy-hydrocarbon resources, and an example is the in-situ conversion process (ICP) developed by Shell for oil-shale production. Computational costs can be very high for such a complex system, which makes direct fine-scale simulations prohibitively time-consuming for large field-scale applications. This motivates the use of coarse grids for thermal-reactive compositional-flow simulation. However, significant errors are introduced by use of coarse-scale models without carefully computing the appropriate coarse parameters. In this paper, we develop an innovative dual-grid method to effectively capture the fine-scale reaction rates in coarse-scale ICP-simulation models. In our dual-grid method, coupled thermal-reactive compositional-flow equations are solved only on the coarse scale, with the kinetic parameters (frequency factors) calculated on the basis of fine-scale computations, such as temperature downscaling and fine-scale reaction-rate calculation. A dual-grid treatment for the heater-well model is also developed with coarse-scale heater-well indices calculated on the basis of fine-scale well results. The dual-grid heater-well treatment is able to provide accurate heater temperatures. The newly developed dual-grid method is applied to realistic cross-sectional ICP-pattern models with a vertical production well and multiple horizontal heater wells operated subject to fixed and time-varying heater powers. It is shown that the dual-grid model delivers results that are in close agreement with the fine-scale reference results for all quantities of interest. Despite the fact that the dual-grid method is implemented at the simulation-deck level, by use of the flexible scripting and monitor functionalities of our proprietary simulation package, significant computational improvements are achieved for all cases considered.

Summary A multiscale finite-volume (MSFV) framework for reservoir simulation is described. This adaptive MSFV formulation is locally conservative and yields accurate results of both flow and transport in large-scale highly heterogeneous reservoir models. IMPES and sequential implicit formulations are described. The algorithms are sensitive to the specific characteristics of flow (i.e., pressure and total velocity) and transport (i.e., saturation). To compute the fine-scale flow field, two sets of basis functions - dual and primal - are constructed. The dual basis functions, which are associated with the dual coarse grid, are used to calculate the coarse scale transmissibilities. The fine-scale pressure field is computed from the coarse grid pressure via superposition of the dual basis functions. Having a locally conservative fine scale velocity field is essential for accurate solution of the saturation equations (i.e., transport). The primal basis functions, which are associated with the primal coarse grid, are constructed for that purpose. The dual basis functions serve as boundary conditions to the primal basis functions. To resolve the fine-scale flow field in and around wells, a special well basis function is devised. As with the other basis functions, we ensure that the support for the well basis is local. Our MSFV framework is designed for adaptive computation of both flow and transport in the course of a simulation run. Adaptive computation of the flow field is based on the time change of the total mobility field, which triggers the selective updating of basis functions. The key to achieving scalable (efficient for large problems) adaptive computation of flow and transport is the use of high fidelity basis functions with local support. We demonstrate the robustness and computational efficiency of the MSFV simulator using a variety of large heterogeneous reservoir models, including the SPE 10 comparative solution problem.

Classical dual-scale reactive simulations of the RTM process assume permanent intra-tow resin storage in the saturated domain. However, recent experimental investigations revealed that permanent storage is occurring only in a limited volume of the tows. In the remaining volume, fluid is released in the channels with a rate that depends on the architecture of the textile and on the fiber volume fraction. Based on experimental observations, a new model is proposed to refine the simulation of the high speed reactive RTM process: a simplified microstructural model is used to enable permanent and partial transient storage within the tows. Additionally, a new sink term is proposed to reproduce the kinetics of the convective tow-channel fluid exchanges in the saturated domain. After a state of the art on dual-scale and reactive flow, the experimental inputs of the study are presented. The new model is then introduced, validated and characterized using the experimental inputs. Additionally, the influence of the release mechanisms on a reactive dual-scale injection is estimated by conducting comparative single-scale, and dual-scale simulations with transient or permanent storage. The new model has been demonstrated to be appropriate to reproduce accurately the release mechanisms, and simulations reveal the interest of taking these release mechanisms into account to simulate reactive dual-scale injections with an increased accuracy.

Considering the un-saturated in the experiment, the purpose of this paper is achieving a simple 1d molds unsaturated simulation of the filling process through the compiled software pore-flow and compare the single-scale result with the dual-scale result.

Summary Field-scale representation of highly heterogeneous reservoirs remains a challenge in numerical reservoir simulation. In such reservoirs, detailed geological models are important to properly represent key heterogeneities. However, high computational costs and long simulation run times make these detailed models unfeasible to use in dynamic evaluations. Therefore, the scaling up of geological models is a key step in reservoir-engineering studies to reduce computational time. Scaling up must be carefully performed to maintain integrity; both truncation errors and the smoothing of subgrid heterogeneities can cause significant errors. This work evaluates the latter—the effect of averaging small-scale heterogeneities in the upscaling process—and proposes a new upscaling technique to overcome the associated limitations. The technique is dependent on splitting the porous media into two levels guided by flow- and storage-capacity analysis and the Lorenz coefficient (LC), both calculated with static properties (permeability and porosity) from a fine-scale reference model. This technique allows the adaptation of a fine highly heterogeneous geological model to a coarse-scale simulation model in a dual-porosity/dual-permeability (DP/DP) approach and represents the main reservoir heterogeneities and possible preferential paths. The new upscaling technique is applied to different reservoir-simulation models with water injection and immiscible gas injection as recovery methods. In deterministic and probabilistic studies, we show that the resulting coarse-scale dual-permeability models are more accurate and can better reproduce the fine-scale results in different upscaling ratios (URs), without using any simulation results of the reference fine-scale simulation models, as some of the current alternative upscaling methods do.

In this paper, the permeability of fiber fabric used in liquid composite molding (LCM) is predicted by the method of numerical simulation. The three-dimensional finite element model of unit cell representing the periodic micro-structure of a plaid is established. In the process of numerical simulation, each fiber bundle in unit cell is treated as a porous medium. Stokes equation and Darcy's law are employed to model the saturated flow between the fiber bundles and the saturated flow in the fiber bundle, respectively. Steady state flow of the finite element model of unit cell is simulated. The effective permeability of the plaid is obtained from the postprocessing of the simulation results by using Darcy's law.

Dans cette thèse, nous nous intéressons aux préformes fibreuses dans le cadre du procédé Resin Transfer Moulding (RTM). L'objectif de la thèse est double : proposer une nouvelle méthodologie pour obtenir des données géométriques à la mésoéchelle des préformes et fournir un nouveau modèle numérique capable de prédire la perméabilité ou d'effectuer des simulations d’écoulement efficaces à la méso-échelle. Dans la première partie, l'accent est mis sur l'acquisition de données géométriques : nous proposons une nouvelle méthodologie basée sur l'analyse du champ de pression supporté par une préforme sèche sous compactage. Un film sensible à la pression mesure le champ de pression par un empilement de plis contre les parois du moule. Profitant de l’architecture périodique des textiles, les empreintes révélées par le champ de pression sont interprétées par analyse spectrale de Moiré pour mesurer l'orientation et la distribution spatiale de chaque couche dans l’empilement. Dans la seconde partie, le modèle numérique de la préforme est utilisé pour effectuer des simulations numériques d'écoulement à l'échelle des fils, afin d’en caractériser la perméabilité ou d’effectuer directement des simulations de remplissage. La géométrie 3D de l’empilement est remplacée par un squelette préservant les propriétés topologiques nécessaires à la résolution numérique du problème d'écoulement bidimensionnel, réduisant considérablement le coût de calcul par rapport à une approche 3D complète. Ce modèle de réduction du volume poreux en squelette est d'abord formulé dans sa version simple échelle (écoulement inter-mèche), puis étendu en double échelle (écoulement inter- et intra-mèche). Le potentiel du modèle est illustré à travers plusieurs cas tests. Cette recherche propose une méthodologie allant de l'acquisition de données géométriques à la simulation numérique double-échelle de l'écoulement au sein dans un empilement de tissus
In this work, we study continuous fiber preforms in the context of Resin Transfer Moulding (RTM) processes. The aim of the thesis is two-fold: propose a new methodology to obtain mesoscale geometrical data from preforms and provide a new numerical model able to predict permeability or perform mesoscale filling simulations in a computationally efficient way. In the first part, the focus is on the acquisition of geometrical data from preforms: we propose a novel methodology based on the analysis of the pressure field experienced by a dry preform under compaction. By using a commercial pressure-sensitive film, the pressure field exerted by a stack of layers against mould walls is captured and analyzed. Taking advantage of the periodic morphology of textiles, geometric patterns revealed by the pressure field are interpreted according to spectral Moiré analysis to recover the orientation and spatial distribution of each individual layer in the stack. In the second part, the reconstructed digital architecture of the preform is used to carry out numerical flow simulations at the scale of the yarns, to characterize permeability of the stack or directly perform filling simulations. The stack geometry is replaced by a skeletonized representation of the same, on which a two-dimensional flow problem can be solved numerically, greatly reducing the computational cost when compared to a full 3D approach. This “medial skeleton” model is first formulated in its single-scale version (flow in channels) and then extended to dual-scale (flow in channels and yarns). The model potential is illustrated through several test cases. This research establishes a pathway going from the non-destructive acquisition of data to the simulation of the dual-scale flow inside a multi-layer layup of textiles

Gardiens de l’espace, les lanceurs de fusée font l’objet d’une amélioration continue et concurrentielle, grâce à des campagnes de tests expérimentaux et numériques. Les simulations prédictives sont devenues indispensables pour accroître notre compréhension de la physique. Ajustables, elles se prêtent parfaitement à la conception et l’optimisation, en particuliers de la chambre de combustion, pour garantir la sureté et maximiser l’efficacité. L’atomisation primaire est l’un des phénomènes déterminants de la combustion du combustible et de l’oxydant, pilotant à la fois la distribution de gouttes et les potentielles instabilités hautes-fréquences en conditions sous-critiques. Elle couvre un large spectre de topologies d’écoulement diphasique, depuis ceux de type phases séparées jusqu’à la phase dispersée, en passant par une région mixte caractérisée par la complexité de la physique à petites échelles et de la topologie de l’écoulement. Les modèles d’ordre réduit constituent de bons candidats pour réaliser des simulations numériques prédictives et relativement peu coûteuses en ressource de calcul sur des configurations industrielles. Cependant, jusqu’à présent ils ne décrivent correctement que la dynamique des grandes échelles et doivent donc être couplés à des modèles de phase dispersée nécessitant un réglage minutieux de paramètres pour prédire la formation du spray. Afin de décrire à la fois les régions mixte et dispersée, l’amélioration de la hiérarchie de modèles d’ordre réduit repose sur quelques principes clefs au cœur de la thèse ci-présente et fournit des problèmes interdisciplinaires faisant appel tant à l’analyse mathématique et la modélisation physique de ces systèmes d’EDP qu’à leur discrétisation numérique et leur implémentation dans des codes de CFD à des fins industriels. Grâce d’une part à l’extension de la théorie des équations de conservation supplémentaires à des systèmes impliquant des termes non-conservatifs et d’autre part à un formalisme de thermodynamique multi-fluide tenant compte des effets non-idéaux, nous proposons de nouvelles pistes pour définir une entropie de mélange strictement convexe et consistante avec le système d’équation et les lois de pression, dans le but de permettre la symmétrisation entropique des modèles diphasiques, de prouver leur hyperbolicité et d’obtenir des termes sources généraux. De plus, en rompant avec la vision géométrique de l’interface, nous proposons une description multi-échelle de l’interface pour décrire un mélange multi-fluide comportant une dynamique interfaciale complexe. Le Principe de Moindre Action a permis de dériver un modèle bifluide à une vitesse couplant grandes et petites échelles de l’écoulement. Nous avons ensuite développé une stratégie de séparation d’opérateurs basée sur la discrétisation par Volumes Finis, et nous avons implémenté le nouveau modèle dans le logiciel industriel multiphysique de CFD, CEDRE, de l’ONERA afin d’évaluer numériquement ce dernier. Enfin, nous avons construit et analysé les fondations d’une hiérarchie de cas tests accessibles à la DNS tout en étant au plus proche de configurations industrielles, dans le but d’évaluer les résultats de simulations du nouveau modèle ou de tout autre modèle à venir
Gatekeepers to the open space, launchers are subject to intense and competitive enhancements, through experimental and numerical test campaigns. Predictive numerical simulations have become mandatory to increase our understanding of the physics. Adjustable, they provide early-stage optimization processes, in particular of the combustion chamber, to guaranty safety and maximize efficiency. One of the major physical phenomenon involved in the combustion of the fuel and oxidizer is the jet atomization, which pilotes both the droplet distributions and the potential high-frequency instabilities in subcritical conditions. It encompasses a large sprectrum of two-phase flow topologies, from separated phases to disperse phase, with a mixed region where the small scale physics and topology of the flow are very complex. Reduced-order models are good candidates to perform predictive but low CPU demanding simulations on industrial configurations but have only been able so far to capture large scale dynamics and have to be coupled to disperse phase models through adjustable and weakly reliable parameters in order to predict spray formation. Improving the hierarchy of reduced order models in order to better describe both the mixed region and the disperse region requires a series of building blocks at the heart of the present work and give on to complex problems in the mathematical analysis and physical modelling of these systems of PDE as well as their numerical discretization and implementation in CFD codes for industrial uses. Thanks to the extension of the theory on supplementary conservative equations to system of non-conservation laws and the formalism of the multi-fluid thermodynamics accounting for non-ideal effects, we give some new leads to define a strictly convex mixture entropy consistent with the system of equations and the pressure laws, which would allow to recover the entropic symmetrization of two-phase flow models, prove their hyperbolicity and obtain generalized source terms. Furthermore, we have departed from a geometric approach of the interface and proposed a multi-scale rendering of the interface to describe multi-fluid flow with complex interface dynamics. The Stationary Action Principle has returned a single velocity two-phase flow model coupling large and small scales of the flow. We then have developed a splitting strategy based on a Finite Volume discretization and have implemented the new model in the industrial CFD software CEDRE of ONERA to proceed to a numerical verification. Finally, we have constituted and investigated a first building block of a hierarchy of test-cases designed to be amenable to DNS while close enough to industrial configurations in order to assess the simulation results of the new model but also to any up-coming models

Abstract Streamline-based methods have proven to be effective for various subsurface flow and transport modeling problems. However, the applications are limited in dual-porosity and dual-permeability (DPDK) system due to the difficulty in describing interactions between matrix and fracture during streamline tracing. In this work, we present a robust streamline tracing algorithm for DPDK models and apply the new algorithm to rate allocation optimization in a waterflood reservoir. In the proposed method, streamlines are traced in both fracture and matrix domains. The inter-fluxes between fracture and matrix are described by switching streamlines from one domain to another using a probability computed based on the inter-fluxes. The approach is fundamentally similar to the existing streamline tracing technique and can be utilized in streamline-assisted applications, such as flow diagnostics, history matching, and production optimization. The proposed method is benchmarked with a finite-volume based approach where grid-based time-of-flight was obtained by solving the stationary transport equation. We first validated our method using simple examples. Visual time-of-flight comparisons as well as tracer concentration and allocation factors at wells show good agreement. Next, we applied the proposed method to field scale models to demonstrate the robustness. The results show that our method offers reduced numerical artifacts and better represents reservoir heterogeneity and well connectivity with sub-grid resolutions. The proposed method is then used for rate allocation optimization in DPDK models. A streamline-based gradient free algorithm is used to optimize net present value by adjusting both injection and production well rates under operational constraints. The results show that the optimized schedule offers significant improvement in recovery factor, net present value, and sweep efficiency compared to the base scenario using equal rate injection and production. The optimization algorithm is computationally efficient as it requires only a few forward reservoir simulations.

Abstract Due to growing needs for energy in our life, research in the wind energy field has increased significantly. There has been global concern towards the development of smart techniques and devices that could optimize the energy conversion and maximize the output power from the wind. Investigating such alternative solutions are required in order to meet the continuous increase in the power demand. The Dual Rotor Wind Turbine system (DRWT) offers higher energy extraction rates from the wind. In the present study, it is proposed to utilize the dual rotor configuration in a ducted system using wind lens in order to enable its application in regions of low wind speeds. The aerodynamic performance of ducted dual rotor wind turbine is investigated using CFD to solve three dimensional, turbulent-steady incompressible flow equations, using the k-ε Realizable and k-ω shear stress transport (SST) turbulence models. Several difficulties due to complexity of geometry and meshing requirements have been encountered. Mesh independence study was conducted to ensure the accuracy and validate the results. Power curves were obtained, detailed investigation of the wind turbine performance in different configurations are highlighted in order to explore the benefit and effect of each configuration to the output power. The final results of combined configuration for dual rotor wind turbine (DRWT) with lens show a considerable improvement to the performance of wind turbine over wide range of wind speeds.

Abstract Upscaling of discrete fracture networks to continuum models such as the dual porosity/dual permeability (DPDP) model is an industry-standard approach in modelling of fractured reservoirs. While flow-based upscaling provides more accurate results than analytical methods, the application of flow-based upscaling is limited due to its high computational cost. In this work, we parametrize the fine-scale fracture geometries and assess the accuracy of several convolutional neural networks (CNNs) to learn the mapping between this parametrization and the DPDP model closures such as the upscaled fracture permeabilities and the matrix-fracture shape factors. We exploit certain similarities between this task and the problem of image classification and adopt several best practices from the state-of-the-art CNNs used for image classification. By running a sensitivity study, we identify several key features in the CNN structure which are crucial for achieving high accuracy of predictions for the DPDP model closures, and put forward the corresponding CNN architectures. Obtaining a suitable training dataset is challenging because i) it requires a dedicated effort to map the fracture geometries; ii) creating a conforming mesh for fine-scale simulations in presence of intersecting fractures typically leads to bad quality mesh elements; iii) fine-scale simulations are time-consuming. We alleviate some of these difficulties by pre-training a suitable CNN on a synthetic random linear fractures’ dataset and demonstrate that the upscaled parameters can be accurately predicted for a realistic fracture configuration from an outcrop data. The accuracy of the DPDP results with the predicted model closures is assessed by a comparison with the corresponding fine-scale discrete fracture-matrix (DFM) simulation of a two-phase flow in a realistic fracture geometry. The DPDP results match well the DFM reference solution, while being significantly faster than the latter.

Subsonic, transitional flow through a low-pressure turbine (LPT) cascade is investigated using high-order compact difference scheme in conjunction with large-eddy simulation (LES). Three-dimensional simulations are performed at chord inlet Reynolds numbers (Re) of 25,000 and 50,000. The inlet Mach number is approximately 0.06. An MPI-based higher-order accurate, Chimera version of the FDL3DI flow solver developed by the Air Force Research Laboratory at Wright Patterson Air Force base, is extended for the present turbomachinery application. The implicit solver is based on an approximate factored time-integration method of Beam and Warming. Fourth-order compact-difference formulations are used for discretizing spatial derivatives in conjunction with sixth-order non-dispersive filtering. Solutions are obtained both with and without a sub-grid scale (SGS) model. A dual topology, 16-block, structured grid generated using GridPro is utilized for all simulations. The flow features are examined, and the results for both LES approaches are compared to each other, and with experimental data.

Abstract Detailed geological description of fractured reservoirs is typically characterized by the discrete-fracture model (DFM), in which the rock matrix and fractures are explicitly represented in the form of unstructured grids. Its high computation cost makes it infeasible for field-scale applications. Traditional flow-based and static-based methods used to upscale detailed geological DFM to reservoir simulation model suffer from, to some extent, high computation cost and low accuracy, respectively. In this paper, we present a novel deep learning-based upscaling method as an alternative to traditional methods. This work aims to build an image-to-value model based on convolutional neural network to model the nonlinear mapping between the high-resolution image of detailed DFM as input and the upscaled reservoir simulation model as output. The reservoir simulation model (herein refers to the dual-porosity model) includes the predicted fracture-fracture transmissibility linking two adjacent grid blocks and fracture-matrix transmissibility within each coarse block. The proposed upscaling workflow comprises the train-validation samples generation, convolutional neural network training-validating process, and model evaluation. We apply a two-point flux approximation (TPFA) scheme based on embedded discrete-fracture model (EDFM) to generate the datasets. We perform trial-error analysis on the coupling training-validating process to update the ratio of train-validation samples, optimize the learning rate and the network architecture. This process is applied until the trained model obtains an accuracy above 90 % for both train-validation samples. We then demonstrate its performance with the two-phase reference solutions obtained from the fine model in terms of water saturation profile and oil recovery versus PVI. Results show that the DL-based approach provides a good match with the reference solutions for both water saturation distribution and oil recovery curve. This work manifests the value of the DL-based method for the upscaling of detailed DFM to the dual-porosity model and can be extended to construct generalized dual-porosity, dual-permeability models or include more complex physics, such as capillary and gravity effects.

The macroscopic flow during processing of composite structures by liquid composite molding is accompanied by the microscopic flow through individual fiber bundles. This concurrent microscopic flow occurs at length and time scales different than those of the macroscopic flow and influences the macroscopic flow behavior, impacting the void formation during composite manufacturing. A reduced-order model developed by the authors of this paper in [Proc. 2005 ASME Conf., IMECE2005-82436] for modeling the microscopic impregnation of individual fiber bundles is currently used to simulate the transient dynamics of the 1-D two-phase flow though a dual-scale porous medium during resin transfer molding (RTM). As has been show in our previous work [Inter. J. of Multiphase Flow, Vol. 32, pp. 1219–1233, 2006] the vapor-liquid phase transition and multidimensional effects of the gas entrapped inside fiber tows can play a significant role in the advancement of the macroscopic resin front and the formation of voids, thus indicating the need to account for these phenomena in the simulation of liquid composite molding processes. These effects are quantified by introducing a nonzero sink term into the right hand side of the mass conservation equation for the dual-scale porous medium, which couples the microscopic two-phase flow inside fiber bundles with the macro-flow through the perform. Two numerical methods, one of which is based on the moving coordinate system associated with the macroscopic resin front and the other one based on the fill factor technique on a fixed Eulerian coordinate system, are used to solve the resin flow through the preform. The comparative analysis of the fill factor and moving front methods as well as the results demonstrating the effect of phase transition and impregnation of individual fiber bundles on macroscopic flow parameters during RTM are presented.

The key technology of furnace for utility boiler is the combustion organizing of burner. The whirl burners are gradually adopted in large-scale utility boiler. A new structure based on dual register whirl burner was proposed and studied by experiment and numerical simulation. From experiment work carried out on cold modeling test, we obtained axial velocity distribution, refluxing extent and turbulence with different spouts, swirl intensity, and blast air distribution. The flow fields were also calculated by computational fluid dynamic (CFD) simulations which accorded with experimental results. By both studies it was found that the new structure whirl burner has high turbulence near the spout and favorable reflowing for ignition and steady combustion. Air distribution controlling could adjust flow field for variable coal. Total refluxing extent variable was proposed to predict the refluxing ratio. The multi-blocks concentrator of pulverized coal was also studied. And favorable dense-lean particle separation was observed which is helpful to dense-lean combustion for low NOx emission.

Abstract Compositional reservoir simulation is essential to represent the complex interactions associated with gas flooding processes. Generally, an improved description of such small-scale phenomena requires the use of very detailed reservoir models, which impact the computational cost. We provide a practical and general upscaling procedure to guide a robust selection of the upscaling approaches considering the nature and limitations of each reservoir model, exploring the differences between the upscaling of immiscible and miscible gas injection problems. We highlight the different challenges to achieve improved upscaled models for immiscible and miscible gas displacement conditions with a stepwise workflow. We first identify the need for a special permeability upscaling technique to improve the representation of the main reservoir heterogeneities and sub-grid features, smoothed during the upscaling process. Then, we verify if the use of pseudo-functions is necessary to correct the multiphase flow dynamic behavior. At this stage, different pseudoization approaches are recommended according to the miscibility conditions of the problem. This study evaluates highly heterogeneous reservoir models submitted to immiscible and miscible gas flooding. The fine models represent a small part of a reservoir with a highly refined set of grid-block cells, with 5 × 5 cm2 area. The upscaled coarse models present grid-block cells of 8 × 10 m2 area, which is compatible with a refined geological model in reservoir engineering studies. This process results in a challenging upscaling ratio of 32 000. We show a consistent procedure to achieve reliable results with the coarse-scale model under the different miscibility conditions. For immiscible displacement situations, accurate results can be obtained with the coarse models after a proper permeability upscaling procedure and the use of pseudo-relative permeability curves to improve the dynamic responses. Miscible displacements, however, requires a specific treatment of the fluid modeling process to overcome the limitations arising from the thermodynamic equilibrium assumption. For all the situations, the workflow can lead to a robust choice of techniques to satisfactorily improve the coarse-scale simulation results. Our approach works on two fronts. (1) We apply a dual-porosity/dual-permeability upscaling process, developed by Rios et al. (2020a), to enable the representation of sub-grid heterogeneities in the coarse-scale model, providing consistent improvements on the upscaling results. (2) We generate specific pseudo-functions according to the miscibility conditions of the gas flooding process. We developed a stepwise procedure to deal with the upscaling problems consistently and to enable a better understanding of the coarsening process.

Abstract Advances in high-resolution micro computed tomography (micro-CT) allow obtaining high-quality rock images with a resolution of up to a few micrometres. Novel direct numerical simulation methods provide the opportunity to precisely predict the flow properties in the resolved pore space. However, a large fraction of porosity lies below the resolution of modern micro-CT scanners. These, so called, micro-pores may significantly affect the physics of flow in geologically complex dual-porosity heterogeneous formations (carbonates, shales, and coals) and are currently not accounted for in traditional micro-CT based simulations. In this work, we have employed a multiphase multi-scale Darcy-Brinkman approach to simulate immiscible two-phase flow in a hybrid system containing both macro-porous solid-free regions and a micro-porous permeable matrix. This approach solves the Navier-Stokes based volume of fluid equations system in macro-pores and accounts for multiphase Darcy equations in micro-porous regions. By combining available information on micro-porosity with relative permeability curves estimated from the synthetically generated image with both macro- and micro-porous regions fully resolved, we solve the inverse problem to account for micro-porous contribution in our Darcy-Brinkman simulation. This approach allows us to estimate relative-permeability curves in the micro-porous region and correct the multi-scale simulation so it coincides with the data from the fully-resolved image. As a result, we were able to account for the impact of micro-porosity on the residual saturation and correct the shape of relative permeability curves and their end-points in the micro-porous domain. The proposed approach provides a workflow which can be used to history-match the Darcy-Brinkman pore-scale simulation with core-scale petrophysical data with respect to the relative permeability. Thus, it is possible to account for heterogeneity in complex rock formations by incorporating the whole range of porosity. The inclusion of micro-porosity in pore-scale image-based simulations for predicting relative permeability curves may help in a more reliable modelling and estimation of filed-scale subsurface flows, production profiles, recoverable reserves and carbon capture and storage mechanisms.

In liquid composite molding technologies such as Resin Transfer Molding (RTM), a thermoset resin is injected into a mold cavity with a pre-placed preform made of fiber mats to create a cured part. In order to improve the physics of resin flow in dual-scale (woven, stitched or braided) fiber mats, the authors carried out many transient 1-D mold-filling experiments to investigate the onset of unsaturated flow through the inlet-pressure history. Their study revealed that the measured pressure history, which droops downwards for dual-scale fiber mats, is at a variance with the linear pressure profile predicted by state-of-the-art Liquid Composite Molding (LCM) mold-filling simulation physics. It was also observed that the drooping of the inlet pressure increases with an increase in the compression of fiber mats. In this paper, the correlation between a previously proposed dimensionless number pore volume ratio and the droop in the inlet pressure history has been sought. Studying the micrographs of composite samples, pore volume ratio is measured for various fiber mat compression. It is observed that the droop in the inlet pressure profiles increase with an increase in the pore volume ratio. This is the first attempt to quantitatively validate the previous theories on the unsaturated flow.