Browsing by Subject "Upscaling"

Now showing 1 - 12 of 12

A new upscaling method for flow simulation of fractured systems
(2018-12-06) Chen, Youguang; Sepehrnoori, Kamy, 1951-
Fractured reservoirs have gained continuous attention in oil and gas industry since a huge amount of reserves are stored in such reservoirs. Fractures add complexity in reservoir models and thus have potentially large effects on the reservoir simulation results. Though a lot of fine scale fracture models for reservoir simulation have been developed to capture the fracture effects, they are generally complicated and time consuming for the cases with large number of fractures and problems (for example, some inverse problems and optimization problems) where lots of forward simulations are required. Upscaling is a method to fasten the flow simulations by constructing reduced models in coarse scale to approximate the original fine scale models. It is important to construct coarse models in a proper way since the approximated models will generate errors as opposed to the fine scale models. Therefore, a new upscaling method is proposed in this work to capture the effects of fractures in fractured reservoir. First, two hypothetical flow problems are presented to provide pressure solutions for calculation of parameters in coarse models. Unsteady state method, one of these two flow problems, is firstly introduced in this work to obtain reasonable pressure solutions for reservoirs without source term. Second, we developed two partitioning methods to associate coarse grids with fine grids. Since these two partitioning approaches are suitable for different types of fracture networks, we proposed a multi-level partitioning method that is a general approach and could capture fracture effects of different fracture patterns. Third, we developed an efficient time-stepping algorithm for the unsteady state problem to reduce the computational efforts of upscaling process. The applicability of the new upsclaing methodology is verified from numerical tests of different types of reservoirs with different fracture patterns and well configurations. Errors of pressure solution, oil saturation, and production solutions are generally limited below 5% in coarse scale. Furthermore, speedup of simulation is significant in all of the presented numerical tests
Global upscaling of secondary and tertiary displacements
(2014-05) Jain, Lokendra; Lake, Larry W.
Fluids injected during secondary and tertiary floods often leave parts of the reservoir unswept mostly because of large heterogeneity and mobility ratio. Several applications require an analytical scheme that could predict production with as few parameters possible. We develop such an analytical model of volumetric sweep that aims to apply an extension of Koval’s theory where flow is assumed to be segregated under vertical equilibrium conditions for secondary and tertiary displacements. The unified theory for vertical equilibrium (viscous and dispersive) is also derived as a precursor to model development. The original Koval factor is applicable for upscaling secondary miscible floods. The new analytical model for secondary and tertiary floods is applied to provide quick estimates of oil recovery of miscible as well as immiscible displacements, which is then calibrated against field data. The model parameters, Koval factor, sweep efficiency and pore volume, estimated after history matching could be used to make reservoir management decisions. The model is very simple; history matching can be done in a spreadsheet. Single-front, gravity-free, displacements can be modeled using Koval factors. Two-front, gravity-free, displacements can also be modeled using Koval-type factors for both the fronts. These Koval-type factors, coupled with laboratory scale relative permeabilities, allows for scaling the displacement to a larger reservoir system. The new method incorporates by-passed pore volume as a parameter, a difference between this work and that of Molleai, along with Koval factors and local front velocities. For two front displacements, it also accounts for the interaction between the fronts which honors correct mass conservation, another difference with the work of Molleai. The results from new models for secondary and tertiary displacements were verified by comparing them against numerical simulations. The application was also demonstrated on actual field examples. Current techniques for reservoir surveillance rely on numerical models. The parameters on which these numerical models depend on are very large in number, introducing large uncertainty. This technique provides a way to predict performance without the use of computationally expensive fine scale simulation models, which could be used for reservoir management while reducing the uncertainty.
Hierarchical modeling of fractures for naturally fractured reservoirs
(2010-08) Anupam, Ankesh; Srinivasan, Sanjay; Sen, Mrinal
Discrete Fracture Networks (DFN) models have long been used to represent heterogeneity associated with fracture networks but all previous approaches have been either in 2D (assuming vertical fractures) or for simple models within a small domain. Realistic representation of DFN on field scale models have been impossible due to two reasons - first because the representation of extremely large number of fractures requires significant computational capability and second, because of the inability to represent fractures on a simulation grid, due to extreme aspect ratio between fracture length and aperture. This thesis presents a hierarchal approach for fracture modeling and a novel random walker simulation to upscale the fracture permeability. The modeling approach entails developing effective flow characteristics of discrete fractures at micro and macrofracture scales without explicitly representing the fractures on a grid. Separate models were made for micro scale and macro scale fracture distribution with inputs from the seismic data and field observations. A random walker simulation is used that moves walkers along implicit fractures honoring the intersection characteristics of the fracture network. The random walker simulation results are then calibrated against high-resolution flow simulation for some simple fracture representations. The calibration enables us to get an equivalent permeability for a complex fracture network knowing the statistics of the random walkers. These permeabilities are then used as base matrix permeabilities for random walker simulation of flow characteristics of the macro fractures. These are again validated with the simulator to get equivalent upscaled permeability. Several superimposed realizations of micro and macrofracture networks enable us to capture the uncertainty in the network and corresponding uncertainty in permeability field. The advantage of this methodology is that the upscaling process is extremely fast and works on the actual fractures with realistic apertures and yields both the effective permeability of the network as well as the matrix-fracture transfer characteristics.
Improved upscaling scheme for steam assisted gravity drainage (SAGD) and semi-analytical modeling of the SAGD rising phase
(2015-05) Murugesu, Mayuri; Srinivasan, Sanjay; Lake, Larry W.
Steam assisted gravity drainage (SAGD) process commonly applied for heavy oil and bitumen recovery consists of two production phases: a steam rising phase and a spreading phase. Extensive research has been done on modeling the SAGD spreading phase, but fewer analytical/semi-analytical models exist for the unstable rising phase. This thesis presents a semi-analytical method, MS-SAGD, to model the SAGD rising phase. In addition, an improved upscaling technique that takes into account the unique flow geometry observed during SAGD is presented that enables more accurate predictions of oil recovery rates in heterogeneous reservoirs during both phases. The MS-SAGD semi analytical method, based on the Myhill and Stegemeier frontal advance model for steam drive processes, tracks the growth of the steam chamber as a function of time. Two different oil production rate models are proposed and the comparison of results from flow and transport simulations is presented. Model 1 is similar to Butler’s approach using the rising steam finger theory. Model 2 is obtained by modifying Butler's spreading phase model and applying it to the rising phase. Both models use the outputs of the MS-SAGD model to estimate the oil production rates during the SAGD rising phase. The application of the MS-SAGD model is extended to heterogeneous reservoirs by treating the heated volume estimated by the original MS-SAGD model as an effective heated volume. In addition, the homogeneous permeability in the proposed oil production rate model is replaced with an upscaled effective permeability that is a function of time. The improved upscaling technique is based on a global approach that minimizes the differences between the fine scale and upscaled model pressure solutions. Sources and sinks by means of wells are used in the upscaling to simulate the convergent flow pattern observed during the SAGD process. The proposed models outperform existing analytical/semi-analytical methods and are in good agreement with the results obtained from CMG-STARS reservoir simulation. Both oil production rate models perform comparatively well, producing similar results in terms of cumulative oil production. However, Model 2 performs better than Model 1 in describing the overall behavior of the oil production observed in the reservoir simulation and is thus a better model for the SAGD rising phase.
Investigation of scale-dependent dispersivity and its impact on upscaling miscible displacements
(2010-05) Garmeh, Gholamreza; Johns, Russell T.; Lake, Larry W.; Sepehrnoori, Kamy; Bryant, Steven L.; Jennings, James W.
Mixing of miscible gas with oil in a reservoir decreases the effective strength of the gas, which can adversely affect miscibility and recovery efficiency. The mixing that occurs in a reservoir, however, is widely debated and often ignored in reservoir simulation, where very large grid blocks are used. Large grid blocks create artificially large mixing that can cause errors in predicted oil recovery. Reservoir mixing, or dispersion, is caused by diffusion of particles across streamlines of varying velocities. Mixing is enhanced by any mechanism that increases the area of contact between the gas and the oil, thereby allowing the effects of diffusion to be magnified. This is, in essence, the cause of scale-dependent dispersion. The contact area grows primarily because of variations in streamlines and their velocities around grains and through layers of various permeabilities (heterogeneity). Mixing can also be enhanced by crossflow, such as that caused by gravity and by the effects of other neighboring wells. This dissertation focuses on estimation of the level of effective local mixing at the field scale and its impact on oil recovery from miscible gas floods. Pore-level simulation was performed using the Navier-Stokes and convection-diffusion equations to examine the origin of scale dependent dispersion. We then estimated dispersivity at the macro scale as a function of key scaling groups in heterogeneous reservoirs. Lastly, we upscaled grid blocks to match the level of mixing at the pattern scale. Once the contact area ceases to grow with distance traveled, dispersion has reached its asymptotic limit. This generally occurs when the fluids are well mixed in transverse direction. We investigated a variety of pore-scale models to understand the nature of scale dependency. From the pore-scale study, we found that reservoir mixing or dispersion is caused by diffusion of particles across streamlines. Diffusion can be significantly enhanced if the surface area of contact between the reservoir and injected fluid are increased as fluids propagate through the reservoir. Echo and transmission dispersivities are scale dependent. They may or may not reach an asymptotic limit depending on the scale of heterogeneities encountered. The scale dependence results from an increase in the contact area between solute (gas) and resident fluid (oil) as heterogeneities are encountered, either at the pore or pattern-scale. The key scaling groups for first-contact miscible (FCM) flow are derived and their impact on mixing is analyzed. We examine only local mixing, not apparent mixing caused by variations in streamline path lengths (convective spreading). Local mixing is important because it affects the strength of the injected fluid, and can cause an otherwise multicontact miscible (MCM) flood to become immiscible. We then showed how to upscale miscible floods considering reservoir mixing. The sum of numerical dispersion and physical dispersion associated with the reservoir heterogeneities, geometry and fluid properties must be equal at both the fine- and large-scales. The maximum grid-block size allowed in both the x- and z-directions is determined from the scaling groups. Small grid-blocks must be used for reservoirs with uncorrelated permeabilities, while larger grid blocks can be used for more layered reservoirs. The predicted level of mixing for first-contact miscible floods can be extended with good accuracy to multicontact miscible (MCM) gas floods.
Local capillary trapping in geological carbon storage
(2012-08) Saadatpoor, Ehsan, 1982-; Bryant, Steven L.; Sepehrnoori, Kamy, 1951-
After the injection of CO₂ into a subsurface formation, various storage mechanisms help immobilize the CO₂. Injection strategies that promote the buoyant movement of CO₂ during the post-injection period can increase immobilization by the mechanisms of dissolution and residual phase trapping. In this work, we argue that the heterogeneity intrinsic to sedimentary rocks gives rise to another category of trapping, which we call local capillary trapping. In a heterogeneous storage formation where capillary entry pressure of the rock is correlated with other petrophysical properties, numerous local capillary barriers exist and can trap rising CO₂ below them. The size of barriers depends on the correlation length, i.e., the characteristic size of regions having similar values of capillary entry pressure. This dissertation evaluates the dynamics of the local capillary trapping and its effectiveness to add an element of increased capacity and containment security in carbon storage in heterogeneous permeable media. The overall objective is to obtain the rigorous assessment of the amount and extent of local capillary trapping expected to occur in typical storage formations. A series of detailed numerical simulations are used to quantify the amount of local capillary trapping and to study the effect of local capillary barriers on CO₂ leakage from the storage formation. Also, a research code is developed for finding clusters of local capillary trapping from capillary entry pressure field based on the assumption that in post-injection period the viscous forces are negligible and the process is governed solely by capillary forces. The code is used to make a quantitative assessment of an upper bound for local capillary trapping capacity in heterogeneous domains using the geologic data, which is especially useful for field projects since it is very fast compared to flow simulation. The results show that capillary heterogeneity decreases the threshold capacity for non-leakable storage of CO₂. However, in cases where the injected volume is more than threshold capacity, capillary heterogeneity adds an element of security to the structural seal, regardless of how CO₂ is accumulated under the seal, either by injection or by buoyancy. In other words, ignoring heterogeneity gives the worst-case estimate of the risk. Nevertheless, during a potential leakage through failed seals, a range of CO₂ leakage amounts may occur depending on heterogeneity and the location of the leak. In geologic CO₂ storage in typical saline aquifers, the local capillary trapping can result in large volumes that are sufficiently trapped and immobilized. In fact, this behavior has significant implications for estimates of permanence of storage, for assessments of leakage rates, and for predicting ultimate consequences of leakage.
Modeling steam assisted gravity drainage in heterogeneous reservoirs using different upscaling techniques
(2014-05) Kumar, Dhananjay; Srinivasan, Sanjay
This thesis presents different methods that improve the ability to relate the flow properties of heterogeneous reservoirs to equivalent anisotropic flow properties in order to predict the performance of the Steam Assisted Gravity Drainage (SAGD) process. Process simulation using full scale heterogeneous reservoirs are inefficient and so the need arises to develop equivalent anisotropic reservoirs that can capture the effect of reservoir heterogeneity. Since SAGD is highly governed by permeability in the reservoir, effective permeability values were determined using different upscaling techniques. First, a flow-based upscaling technique was employed and a semi-analytical model, derived by Azom and Srinivasan, was used to determine the accuracy of the upscaling. The results indicated inadequacy of flow-based upscaling schemes to derive effective direction permeabilities consistent with the unique flow geometry during the SAGD process. Subsequently, statistical upscaling was employed using full 3D models to determine relationships between the heterogeneity variables: k[subscript italic v]⁄k[subscript italic h] , correlation length and shale proportion. An iterative procedure coupled with an optimization algorithm was deployed to determine optimal k[subscript italic v] and k[subscript italic k] values. Further regression analysis was performed to explore the relationship between the variables of shale heterogeneity in a reservoir and the corresponding effective properties. It was observed that increased correlation lengths and shale proportions both decrease the dimensionless flow rates at given dimensionless times and that the semi-analytical model was more accurate for cases that contained lower shale proportions. Upscaled heterogeneous values inputted into the semi-analytical model resulted in underestimation of oil flow rate due to the inability to fully account for the impact of reservoir barriers and the configuration of flow streamlines during the SAGD process. Statistical upscaling using geometric averaging as the initial guess was used as the basis for developing a relationship between correlation length, shale proportion and k[subscript italic v]⁄k[subscript italic h]. The initial regression models did not accurately predict the anisotropic ratio because of insufficient data points along the regression surface. Subsequently a non-linear regression model that was 2nd order in both length and shale proportion was calibrated by executing more cases with varying levels of heterogeneity and the regression model revealed excellent matches to heterogeneous models for the prediction cases.
Scale-up of dispersion for simulation of miscible displacements
(2013-05) Adepoju, Olaoluwa Opeoluwa; Lake, Larry W.; Johns, Russell T.
Dispersion has been shown to degrade miscibility in miscible displacements by lowering the concentration of the injected solute at the displacement fronts. Dispersion can also improve oil recovery by increasing sweep efficiency. Either way, dispersion is an important factor in understanding miscible displacement performance. Conventionally, dispersion is measured in the laboratory by fitting the solution of one-dimensional convection-dispersion equation (CDE) to the effluent concentration from a core flood. However dispersion is anisotropic and mixing occurs in both longitudinal and transverse directions. This dissertation uses the analytical solution of the two-dimensional CDE to simultaneously determine longitudinal and transverse dispersion. The two-dimensional analytical solution for an instantaneous finite volume source is used to investigate anisotropic mixing in miscible displacements. We conclude that transverse mixing becomes significant with large a concentration gradient in the transverse direction and significant local variation in flow directions owing to heterogeneity. We also utilized simulation models similar to Blackwell's (1962) experiments to determine transverse dispersion. This model coupled with the analytical solution for two-dimensional CDE for continuous injection source is used to determine longitudinal and transverse dispersivity for the flow medium. The validated model is used to investigate the effect of heterogeneity and other first contact miscible (FCM) scaling groups on dispersion. We derive the dimensionless scaling groups that affect FCM displacements and determine their impact on dispersion. Experimental design is used to determine the impact and interactions of significant scaling groups and generate a response surface function for dispersion based on the scaling groups. The level of heterogeneity is found to most significantly impact longitudinal dispersion, while transverse dispersion is most significantly impacted by the dispersion number. Finally, a mathematical procedure is developed to use the estimated dispersivities to determine a-priori the maximum grid-block size to maintain an equivalent level of dispersion between fine-scale and upscaled coarse models. Non-uniform coarsening schemes is recommended and validated for reservoir models with sets of different permeability distributions. Comparable sweep and recovery are observed when the procedure was extended to multi-contact miscible (MCM) displacements.
Scale-up of reactive processes in heterogeneous media
(2014-12) Singh, Harpreet, active 21st century; Srinivasan, Sanjay
Physical and chemical heterogeneities cause the porous media transport parameters to vary with scale, and between these two types of heterogeneities geological heterogeneity is considered to be the most important source of scale-dependence of transport parameters. Subsurface processes associated with chemical alterations result in changing reservoir properties with interlinked spatial and temporal scale, and there is uncertainty in the evolution of those properties and the chemical processes. This dissertation provides a framework and procedures to quantify the spatiotemporal scaling characteristics of reservoir attributes and transport processes in heterogeneous media accounting for chemical alterations in the reservoir. Conventional flow scaling groups were used to assess their applicability in scaling of recovery and Mixing Zone Length (MZL) in presence of chemical reactivity and permeability heterogeneity through numerical simulations of CO₂ injection. It was found out that these scaling groups are not adequate enough to capture the scaling of recovery and transport parameters in the combined presence of chemical reactivity and physical heterogeneity. In this illustrative example, MZL was investigated as a function of spatial scale, temporal scale, multi-scale heterogeneity, and chemical reactivity; key conclusions are that 1) the scaling characteristics of MZL distinctly differ for low permeability and high permeability media, 2) heterogeneous media with spatial arrangements of both high and low permeability regions exhibit scaling characteristics of both high and low permeability media, 3) reactions affect scaling characteristics of MZL in heterogeneous media, 4) a simple rescaling can combine various MZL curves by merging them into a single MZL curve irrespective of the correlation length of heterogeneity, and 5) estimates of MZL (and consequently predictions of oil recovery) will fluctuate corresponding to displacements in a permeable medium whose lateral length is smaller than the correlation length of geological formation. We illustrate and extend the procedure of estimating Representative Elementary Volume (REV) to include temporal scale by coupling it with spatial scale. The current practice is to perform spatial averaging of attributes and account for residual variability by calibration and history matching. This results in poor predictions of future reservoir performance. The proposed semi-analytical technique to scale-up in both space and time provides guidance for selection of spatial and temporal discretizations that takes into account the uncertainties due to sub-processes. Finally, a probabilistic particle tracking (PT) approach is proposed to scale-up flow and transport of diffusion-reaction (DR) processes while addressing multi-scale and multi-physics nature of DR mechanisms and also maintaining consistent reservoir heterogeneity at different levels of scales. This multi-scale modeling uses a hierarchical approach which is based on passing the macroscopic subsurface heterogeneity down to the finer scales and then returning more accurate reactive flow response. This PT method can quantify the impact of reservoir heterogeneity and its uncertainties on statistical properties such as reaction surface area and MZL, at various scales.
Upscaling and multiscale simulation by bridging pore scale and continuum scale models
(2012-08) Sun, Tie, Ph. D.; Balhoff, Matthew T.; DiCarlo, David; Arbogast, Todd; Lake, Larry; Wheeler, Mary
Many engineering and scientific applications of flow in porous media are characterized by transport phenomena at multiple spatial scales, including pollutant transport, groundwater remediation, and acid injection to enhance well production. Carbon sequestration in particular is a multiscale problem, because the trapping and leakage mechanisms of CO2 in the subsurface occur from the sub-pore level to the basin scale. Quantitative and predictive pore-scale modeling has long shown to be a valuable tool for studying fluid-rock interactions in porous media. However, due to the size limitation of the pore-scale models (10-4-10-2m), it is impossible to model an entire reservoir at the pore scale. A straightforward multiscale approach would be to upscale macroscopic parameters (e.g. permeability) directly from pore-scale models and then input them into a continuum-scale simulator. However, it has been found that the large-scale models do not predict in many cases. One possible reason for the inaccuracies is oversimplified boundary conditions used in this direct upscaling approach. The hypothesis of this work is that pore-level flow and upscaled macroscopic parameters depends on surrounding flow behavior manifested in the form of boundary conditions. The detailed heterogeneity captured by the pore-scale models may be partially lost if oversimplified boundary conditions are employed in a direct upscaling approach. As a result, extracted macroscopic properties may be inaccurate. Coupling the model to surrounding media (using finite element mortars to ensure continuity between subdomains) would result in more realistic boundary conditions, and can thus improve the accuracy of the upscaled parameters. To test the hypothesis, mortar coupling is employed to couple pore-scale models and also couple pore-scale models to continuum models. Flow field derived from mortar coupling and direct upscaling are compared, preferably against a true solution if one exists. It is found in this dissertation that pore-scale flow and upscaled parameters can be significantly affected by the surrounding media. Therefore, using arbitrary boundary conditions such as constant pressure and no-flow boundaries may yield misleading results. Mortar coupling captures the detailed variation on the interface and imposes realistic boundary conditions, thus estimating more accurate upscaled values and flow fields. An advanced upscaling tool, a Super Permeability Tensor (SPT) is developed that contains pore-scale heterogeneity in greater detail than a conventional permeability tensor. Furthermore, a multiscale simulator is developed taking advantage of mortar coupling to substitute continuum grids directly with pore-scale models where needed. The findings from this dissertation can significantly benefit the understanding of fluid flow in porous media, and, in particular, CO2 storage in geological formations which requires accurate modeling across multiple scales. The fine-scale models are sensitive to the boundary conditions, and the large scale modeling of CO2 transport is sensitive to the CO2 behavior affected by the pore-scale heterogeneity. Using direct upscaling might cause significant errors in both the fine-scale and the large-scale model. The multiscale simulator developed in this dissertation could integrate modeling of CO2 physics at all relevant scales, which span the sub-pore or pore level to the basin scale, into one single simulator with effective and accurate communication between the scales. The multiscale simulator provides realistic boundary conditions for the fine scales, accurate upscaled information to continuum-scale, and allows for the distribution of computational power where needed, thus maintaining high accuracy with relatively low computational cost.
Upscaling and parallel reservoir simulation
(2011) Wang, Kefei; Sepehrnoori, Kamy, 1951-; Killough, John E.
Reservoir characterization techniques have made possible geological reservoir models with multi-million grid blocks populated with permeability, porosity, and fluid saturations. These geological models are often too large to be simulated because of computational limits. These computational limits mean that typical full-field reservoir simulation models are limited to fewer than 1 million cells - at least two orders of magnitude smaller than the geological models. Upscaling techniques have been used to bridge the gap between these geological models and full-field reservoir simulation. Although there have been significant efforts in developing single-phase and two-phase upscaling algorithms, a limited verification of upscaling methods has been performed on a full-field basis. In addition to upscaling techniques, parallel simulation approaches have been developed to solve multi-million cell models with reasonable computational efficiency. Parallel simulations take up to a few hours of CPU time instead of days to run multi- million cell models. However, when many simulations are to be performed over a large range of parameter values for uncertainty studies, parallel simulations again become prohibitive and upscaling must be employed. On the other hand, the results from these upscaled simulations must be validated with results from fine-scale simulations to give confidence on the reliability of the results. There is really no way of knowing how good the results are unless we are able to perform the fine-scale simulations for verification. Parallel ultra-fine-scale simulations may provide the tool for this verification requirement. In this work, we developed several new single-phase upscaling algorithms, and investigated the verification of these techniques applied to a reservoir model and a synthetic model. For complicated multi-phase flow, the single-phase upscaling may lead to large errors. To overcome the inaccuracy, a new relative permeability upscaling approach was investigated in this dissertation research. The new approach was verified by using three-phase, 3D, and highly heterogeneity reservoir model. Based on case studies, the results from the fine-scale model may appropriately be used to guide the upscaling. The parallel simulation may guide engineers to find appropriate upscaled models through a tuning procedure. This tuning procedure has been explored in the current study to obtain results that are in close agreement with the fine-scale simulation results. The combination of parallel simulation technology and upscaling algorithms can be used to provide a better estimation of the amount of uncertainty in predicted oil recovery for real fields.
Using mortars to upscale permeability in heterogeneous porous media from the pore to continuum scale
(2009-12) Bhagmane, Jaideep Shivaprasad; Balhoff, Matthew T.; DiCarlo, David
Pore-scale network modeling has become an effective method for accurate prediction and upscaling of macroscopic properties, such as permeability. Networks are either mapped directly from real media or stochastic methods are used that simulate their heterogeneous pore structure. Flow is then modeled by enforcing conservation of mass in each pore and approximations to the momentum equations are solved in the connecting throats. In many cases network modeling compares favorably to experimental measurements of permeability. However, computational and imaging restrictions generally limit the network size to the order of 1 mm3 (few thousand pores). For extremely heterogeneous media these models are not large enough in capturing the petrophysical properties of the entire heterogeneous media and inaccurate results can be obtained when upscaling to the continuum scale. Moreover, the boundary conditions imposed are artificial; a pressure gradient is imposed in one dimension so the influence of flow behavior in the surrounding media is not included. In this work we upscale permeability in large, heterogeneous media using physically-representative pore-scale network models (domain ~106 pores). High-performance computing is used to obtain accurate results in these models, but a more efficient, novel domain decomposition method is introduced for upscaling the permeability of pore-scale models. The medium is decomposed into hundreds of smaller networks (sub-domains) and then coupled with the surrounding models to determine accurate boundary conditions. Finite element mortars are used as a mathematical tool to ensure interfacial pressures and fluxes are matched at the interfaces of the networks boundaries. The results compare favorably to the more computationally intensive (and impractical) approach of upscaling the media as a single model. Moreover, the results are much more accurate than traditional hierarchal upscaling methods. This upscaling technique has important implications for using pore-scale models directly in reservoir simulators in a multiscale setting. The upscaling techniques introduced here on single phase flow can also be easily extended to other flow phenomena, such as multiphase and non-Newtonian behavior.