Wetting Phase Relative Permeability Research Articles

A coupled fractal model for predicting the relative permeability of rocks considering both irreducible fluid saturation and stress effects

The relative permeability of rocks is an essential parameter for evaluating two-phase flow characteristics and plays an important role in engineering fields such as resource exploitation. To this end, a mathematical model for predicting relative permeability was first developed based on an equivalent capillary model and fractal theory. The proposed model considers the irreducible fluid saturation under stress and quantifies the influence of the pore structure characteristics on the relative permeability. This model was then compared with relevant experimental data and existing theoretical expressions to verify its validity. Finally, the factors affecting the two-phase seepage characteristics were discussed. The results show that the irreducible fluid saturation is intimately connected to the fractal dimensions, pore size, fluid viscosity, pressure drop gradient, and elastic modulus. Fluid properties and pore structure characteristics are the main factors affecting relative permeability. The wetting phase relative permeability is more sensitive to pore structure and irreducible fluids. Increased effective stress increases irreducible fluid saturation, reduces two-phase flow capacity, and significantly decreases the relative permeability of wetting phase fluids. Increased elastic modulus and Poisson's ratio decrease the irreducible fluid content under stress and increase the permeability.

Fluid-Fluid Interfacial Area and Its Impact on Relative Permeability: A Pore Network Modeling Study

SummaryRelative permeability (kr) is commonly modeled as an empirical function of phase saturation. Although current empirical models can provide a good match of one or two measured relative permeabilities using saturation alone, they are unable to predict relative permeabilities well when there is hysteresis or when physical properties such as wettability change. Further, current models often result in relative permeability discontinuities that can cause convergence and accuracy problems in simulation. To overcome these problems, recent research has modeled relative permeability as a state function of both saturation (S) and phase connectivity (X). Pore network modeling (PNM) data, however, show small differences in relative permeability for the same S-X value when approached from a different flow direction. This paper examines the impact of one additional Minkowski parameter (Mecke and Arns 2005), the fluid-fluid interfacial area, on relative permeability to identify if that satisfactorily explains this discrepancy.We calculate the total fluid-fluid interfacial areas (IA) during two-phase (oil/water) flow in porous media using PNM. The area is calculated from PNM simulations using the areas associated with corners and throats in pore elements of different shapes. The pore network is modeled after a Bentheimer sandstone, using square, triangular prism, and circular pore shapes. Simulations were conducted for numerous primary drainage (PD) and imbibition cycles at a constant contact angle of 0° for the wetting phase. Simultaneous measurements of capillary pressure, relative permeability, saturation, and phase connectivity are made for each displacement. The fluid-fluid IA is calculated from the PNM capillary pressure, the fluid location in the pore elements, and the pore element dimensional data.The results show that differences in the relative permeability at the same (S, X) point are explained well by differences in the fluid-fluid interfacial area (IA). That is, for a larger change in IA at these intersection points, the permeability difference is greater. That difference in relative permeability approaches zero as the difference in IA approaches zero. This confirms that relative permeability can be modeled better as a unique function of S, X, and IA. The results also show that an increase in IA restricts flow decreasing the nonwetting (oil) phase permeability. This decrease is caused by an increase in the throat area fraction compared to the corner area as the total area IA increases. The wetting phase relative permeability, however, shows the inverse trend in that its relative permeability is greater when IA becomes larger owing to a greater fraction of the total area associated with the corners. The area IA, however, impacts the nonwetting phase relative permeability more than the wetting phase relative permeability. Corner flow improves the wetting phase relative permeability because the wetting phase is continuous there. Finally, a sensitivity analysis shows that relative permeability is more sensitive to change in S than it is for IA for the case studied, implying that if only two parameters are used to model relative permeability, it is better to choose S and X.

Sensitivity Analysis of Fluid–Fluid Interfacial Area, Phase Saturation and Phase Connectivity on Relative Permeability Estimation Using Machine Learning Algorithms

Recent studies have shown that relative permeability can be modeled as a state function which is independent of flow direction and dependent upon phase saturation (S), phase connectivity (X), and fluid–fluid interfacial area (A). This study evaluates the impact of each of the three state parameters (S, X, and A) in the estimation of relative permeability. The relative importance of the three state parameters in four separate quadrants of S-X-A space was evaluated using a machine learning algorithm (out-of-bag predictor importance method). The results show that relative permeability is sensitive to all the three parameters, S, X, and A, with varying magnitudes in each of the four quadrants at a constant value of wettability. We observe that the wetting-phase relative permeability is most sensitive to saturation, while the non-wetting phase is most sensitive to phase connectivity. Although the least important, fluid–fluid interfacial area is still important to make the relative permeability a more exact state function.

Low salinity water flooding: Evaluating the effect of salinity on oil and water relative permeability curves using coupling of DLVO and geochemical reactions

Enhancing the oil recovery of carbonate reservoirs with acidic oil depends on injected brine composition and salinity throughout the low salinity water flooding. The typical description of this phenomenon on oil and water relative permeability curves is being put forward by the process-dependent interpolation function, which barely addresses the underlying fundamentals governing the direct impact of wettability alteration and geochemical reactions on flow saturation functions. The main objective of this work is to perform an integrated investigation of the effect of salinity on oil and water relative permeability curves by dynamic coupling of the Derjaguin, Landau, Verwey, and Overbeek (DVLO) theory and geochemical reactions. We studied both the single and two-phase systems using the basis of the geochemical reactions to track the variations of the wetting and non-wetting phase relative permeability curves. In the single-phase scenario, the results show the superiority of the reactive flow modeling technique with kinetic-controlled reactions, in the range between [2–4] of the Damkohler number, to yield a better result for the experimental effluent ions' concentrations than the equilibrium approach. In addition, the single-phase results under dynamic conditions propose Civan correlation as the best predictor of residual resistance factor (RRF) by numerically adjusting the correlation of coefficients based on the physical variables - salinity, dimensionless consumed ion concentration, and Peclet number. Accordingly, the results indicate a novel linkage between the single-phase and two-phase results in the sense that RRF under single-phase mode can be used to estimate the change in the wetting phase relative permeability under the two-phase mode. The single-phase methodology provides the capability for an improvement – up to 15% - in the prediction of the pressure drop curve. For two-phase cases, our procedure involved coupling the characterized geochemical reactions and the DLVO theory to consider the effect of injected water composition on contact angle as the static two-phase parameter. The phase-field method is coupled with DLVO theory to calculate the relative permeability curves for the non-wetting phase, which corresponds to the contact angle at each simulation time step. The two-phase results indicate an improvement – up to 30% - in the prediction of the recovery factor curve, on a history-matching basis, using the DLVO theory with contact angle-dependent correlation of non-wetting phase relative permeability curve. The main novelties of this study are using the single-phase dynamic permeability impairment results in calculating the variation of the wetting-phase relative permeability curve. Moreover, dynamic coupling of DLVO and non-linear contact angle-dependent correlation is used to calculate the non-wetting phase relative permeability curve. According to these novelties, more accurate prediction of the laboratory production profiles can be obtained.

Rock Typing Based on Wetting-Phase Relative Permeability Data and Critical Pore Sizes

Summary Rock typing based on mineralogical, hydraulic, or petrophysical similarities is important to reservoir characterization and simulation. In the literature, classifying rocks using single-phase data has been widely studied. Most methods use porosity and permeability measurements to identify rocks with similar characteristic pore sizes. In this study, we invoke concepts from critical-path analysis (CPA) and propose a new rock-typing method on the basis of two-phase flow data, such as water relative permeability krw. We classify rocks based on their similarities in the critical pore radius rc at the same effective water saturation Se. For this purpose, we first convert the Sw−krw plots to Se−rc curves and then apply a curve clustering method to identify similar rocks. To evaluate the proposed approach, we simulated flow in pore networks with many different pore-scale properties. By varying the pore-throat size distribution, contact angle, pore coordination number, pore-shape distribution, and clay content, we generated a wide range of pore networks. Overall, two-phase flow in 240 pore networks were simulated. In addition to synthetic pore networks, pore networks were generated based on properties of Berea, Mt. Simon, and Fontainebleau sandstones. By analyzing the single-phase simulation results, we identified 8 and 15 rock types using the porosity-formation factor and reciprocal formation factor-permeability data, respectively. However, using the two-phase data, we detect 12 rock groups.

Sensitivity of unsteady-state gas-water relative permeability to experimental artefacts and interpretation techniques; case study from a gas reservoir in south Iran

Relative permeability is a key determinant of how a reservoir simulation model performs. Although laboratory measurement techniques for two-phase relative permeability are well-established, but still the difficulties and uncertainties persist. The present study aims to investigate the effect of several parameters, including pressure difference, end-effects, interpretation techniques (analytical and numerical), and mineral dissolution, on the unsteady-state gas-water relative permeability curves. For this purpose, a number of precisely planned experiments were carried out on two subsurface anhydrite dolomite samples collected from a well-known gas reservoir in south Iran.In summary, the measured gas relative permeability (krg) was underestimated at low injection pressures mainly due to the capillary end-effect and a significantly low volume of brine production in compare to the considerable volume that was retained at the end face. Moreover, despite the end-effect was overcame at high injection pressures, but significantly high krg values were recorded at water saturations close to the residual value and the measurements were corrected considering a gas slippage factor at the endpoint.Furthermore, greater wetting phase relative permeability (krw) values were driven from numerical (history matching) interpretation of the results compared with the analytical approach that could be due to the automatic end-effect correction by the numerical techniques where the capillary pressure is accounted for.Finally, to investigate the effect of anhydride dissolution on overestimation of the measured gas relative permeability, the interaction of NaCl brine with anhydride was reviewed using the Computed Tomography (CT) images taken before and after the test.

A more generalized model for relative permeability prediction in unsaturated fractal porous media

Although lots of models for relative permeability prediction have been developed in literature, the effect of pore geometric tortuosity on relative permeability has not been well discussed, as usually the tortuosity of pores with various sizes is assumed the same. However, there is a high possibility that tortuosity is unequal and increases with the decrease in pore size. A new and more generalized analytical model for relative permeability prediction has been developed based on the fractal characteristics of pore size distribution (PSD) and tortuosity in porous media. The analytical expressions of relative permeability for wetting phase and nonwetting phase have been derived, which are the function of normalized wetting phase saturation, PSD fractal dimension, tortuosity fractal dimension and the ratio of the entry capillary pressure to the maximum capillary pressure. The studies show that the increasing PSD fractal dimension and tortuosity fractal dimension can significantly reduce wetting phase relative permeability, but the increase in nonwetting phase relative permeability is insignificant. The developed model has been validated with relative permeability experimental data and compared with other classic relative permeability models. The comparison results demonstrate the reliability of the relative permeability model developed in this paper.

Investigation on Flow Behaviour in Porous Media During Water Flooding and Following CO2 Flooding Using MRI

This article addresses the use of MRI technique to follow the process of oil, water, supercritical CO2 multiphase flow in consolidated sandstone core plug at a typical reservoir temperature and pressure condition. 2D images at various times and quantitative saturation curves were obtained during all stages of the flooding process. The fronts and interfaces between displaced and displacing fluids were also dynamics monitored in situ during water and subsequent supercritical CO2 flooding process. The results showed that the process of CO2 flooding enhanced oil recovery more than 10% based on the previous water flooding. A method of predicting the relative permeability and capillary pressure curves was successfully extended and applied to CO2 flooding, the capillary pressure, the wetting and non-wetting phase relative permeability curves were simultaneously estimated from the capillary end saturation profiles, which were measured with MRI technique. These curves are important and required in various reservoir simulations for evaluating hydrocarbon recovery processes.

Comparison of different models for predicting drainage relative permeability using pore scale numerical simulation of supercritical carbon dioxide and brine flow.

In today’s technologically growing and cost optimisation era, Digital Rock Physics (DRP) is becoming a potential alternative tool to the high cost and time-consuming method of Special Core Analyses (SCAL), for the estimation of reservoir fluid properties. The key objective of this study is to compare different models for predicting drainage relative permeability using pore scale numerical simulation of supercritical carbon dioxide and brine flow, the former being the non-wetting phase and the latter being the wetting phase. The simulations are done on an established computational fluid dynamics (CFD) simulator: ANSYS-CFX. From the simulations, we obtain the saturation values. Using these values and four common models found in the literature, we collaborate the J-function prediction model and capillary pressure values to calculate the relative permeability for the wetting and non-wetting phases. In this study, it is concluded that the Brooks-Corey-Burdine model produces the best relative permeability curves. It is demonstrated that the pore size distribution index (λ) has a positive correlation with the wetting-phase relative permeability and an inverse relation with the non-wetting phase relative permeability. Noteworthy to mention that during the study, it was found that when the J-function is substituted into the relative permeability equations, the predicted relative permeabilities of wetting and non-wetting phase outcomes appears to be more representative, yet simple to compute. The robust methodology described in this paper to evaluate the simulation results with various established models is generic and could be useful in current day oil field practices to serve as a cost-effective alternative to SCAL experiments and form key inputs for typical oil field development planning.

Relative permeability of three immiscible fluids in random porous media determined by the lattice Boltzmann method

In this article, three immiscible fluids flowing in 3D porous media were simulated by the pseudopotential-based multiple relaxation time lattice Boltzmann model for multicomponent/multiphase flow, and the effects of capillary number (Ca), wettability and viscosity ratio (M) on the relative permeability were analysed. The simulation results show that the relative permeability of the three fluids increases with increasing Ca, whereas wettability influences the effect of Ca on the wetting phase (WP) relative permeability. The enhancement of porous wettability in the three-phase system leads to a decrease in the WP relative permeability and an increase in the relative permeability of the other two fluids. When M > 1, the nonwetting phase (NWP) has a lubricating effect and its relative permeability increases with increasing M in wet porous media, whereas the other two fluids are insensitive to M variations compared with the NWP.

Real-time relative permeability prediction using deep learning

A review of the existing two- and three-phase relative permeability correlations shows a lot of pitfalls and restrictions imposed by (a) their assumptions (b) generalization ability and (c) difficulty with updating in real-time for different reservoirs systems. These increase the uncertainty in its prediction which is crucial owing to the fact that relative permeability is useful for predicting future reservoir performance, effective mobility, ultimate recovery, and injectivity among others. Laboratory experiments can be time-consuming, complex, expensive and done with core samples which in some circumstances may be difficult or impossible to obtain. Deep Neural Networks (DNNs) with their special capability to regularize, generalize and update easily with new data has been used to predict oil–water relative permeability. The details have been presented in this paper. In addition to common parameters influencing relative permeability, Baker and Wyllie parameter combinations were used as input to the network after comparing with other models such as Stones, Corey, Parker, Honapour using Corey and Leverett-Lewis experimental data. The DNN automatically used the best cross validation result (in a five-fold cross validation) for its training until convergence by means of Nesterov-accelerated gradient descent which also minimizes the cost function. Predictions of non-wetting and wetting-phase relative permeability gave good match with field data obtained for both validation and test sets. This technique could be integrated into reservoir simulation studies, save cost, optimize the number of laboratory experiments and further demonstrate machine learning as a promising technique for real-time reservoir parameters prediction.

Gas-Water Two Phase Flow Simulation Based on Pore Network Model for Reservoir Rocks

The relative permeability and capillary pressure are essential to investigate fluid flow in porous media, in terms of studying seepage characteristics of gas -water for CO2 emission reduction through deep saline sequestration. In this paper, we presented gas -water phase flow numerical simulation based on pore network extractions of four rock samples. The influence of temperature, pressure and pore structure on relative permeability and capillary pressure were carefully investigated. Analysis of evaluated results demonstrated that pore structure has significant impact on relative permeability and capillary pressure both for gas/water drainage and imbibition cycles. However, the influence of temperature and pressure on relative permeability and capillary pressure for drainage cycle is neglect-able, while during the imbibition cycle, the gas phase relative permeability is decreasing with increasing pressure and temperature, while capillary pressure and wetting phase relative permeability are decreasing with increasing pressure and increasing with increasing temperature. That might cause by change of rock wetting behavior and interactions between fluid-gas-rock as temperature, pressure change which has more impact on gas flooding process than water flooding. After comparing numerical simulation results of drainage cycle based on Berea sandstone sample to the literature, it is seemed that numerical simulation based on pore network extractions is more efficient and economical method of studying seepage characteristics of gas -water at CO2 reservoir storage conditions.

Fractal-based models for the unsaturated soil hydraulic functions

Reliable estimates of the unsaturated soil hydraulic properties are needed in many research and engineering projects. Fractal based approaches have become popular for describing the hydraulic functions. New models based on fractal geometry are presented to describe the wetting phase relative permeability (unsaturated hydraulic conductivity) of porous media. Analytical expressions were derived using the fractal capillary pressure (water retention) model proposed by Alfaro Soto and Vilar (2006) and the statistical pore size distribution models of Mualem (1976a) and Burdine (1953) for the unsaturated hydraulic conductivity. The newly derived models provide predictions of the relative permeability to water, as well as of the fractal dimension for modeling the pore structure of a soil. Results are compared with previous formulations by Brooks and Corey (1964), van Genuchten (1980) and Kosugi (1996), as well as with experimental water retention and hydraulic conductivity data of four soils having widely different soil textures. The proposed models agreed closely with observed data. The analytical models may be attractive alternative for estimating the unsaturated hydraulic conductivity when no laboratory or field measurements are available.

Estimation of sub-core permeability statistical properties from coreflooding data

Knowledge of sub-core permeability is necessary for accurate numerical modeling of coreflooding experiments and for investigation of sub-core flow phenomenon. A new method for estimating sub-core permeability geometric mean (kG) and log-permeability variance (σy2) is presented. The method is based on matching coreflooding experiment measurements of wetting phase relative permeability with semi-analytical calculations of effective relative permeability. The semi-analytical solution is formulated assuming log-normal permeability (k), steady state and capillary-limit conditions. It is based on the geometric mean and log-phase-permeability variance for isotropic k and power law averaging for anisotropic correlations. The solution is validated on synthetic k realizations by comparison with numerical calculations. Then, the estimation method is tested on synthetic data assuming various types of core capillary pressure relationships, relative permeability functions and k anisotropies. Results demonstrate high accuracy in almost all of the cases except for small anisotropy ratios lh/lv between horizontal (lh) and vertical (lv) dimensionless correlation lengths, where flow is in the horizontal direction, and when σy2 is large. The method is also validated using data from CO2-brine coreflooding experiments conducted on two different cores. It is found that the estimation method remains accurate in these realistic settings, however, accuracy of kG is reduced when the core permeability departs from a log-normal distribution.

A new model to predict the relative permeability of wetting phase for tight sandstones

As the existing model is not suitable for tight sandstone reservoirs, a new model has been derived theoretically to correlate the relative permeability of wetting phase, saturation and the tortuosity ratio based on revised Kozeny–Carman equation. According to the similarity between the flow of fluid and current, we found that the wetting phase relative permeability is a function of the tortuosity ratio, saturation and the saturation index. In order to verify the new model, 11 cores were taken from tight sandstone reservoirs in northwestern and northeastern China. By comparing with the existing models, the new model is more suitable for the core which has low permeability (<10 mD) and saturation index (<1.8).

The study of relative permeability and residual gas saturation at high pressures and high temperatures

This paper presents the results of laboratory investigation conducted with reservoir rock plugs recovered from the Gas reservoir in the North West Shelf of Western Australia. The experiments were conducted in reservoir conditions (High Pressure (HP = 41.37 MPa) and High Temperature (HT = 433.15 K)). The aim of this study was to determine residual gas saturation and quantify the effect of reservoir conditions (HP/HT) on gas-brine relative permeability. The experimental data have been analysed using relative permeability concept. Both wetting and nonwetting phase relative permeability were generated using explicit methods, i.e, Hasslar and Corey model (Power Model). The power model is then used to match experimental data through modifying the parameters of the Corey correlation. Several core plugs were used by this study representing different reservoir quality rocks in the reservoir. The core plugs were in different dimensions, the short core plugs measured around 5 cm in length while the long core plug measured 19.41 cm. The aim of using longer core plugs was to minimise the effect of capillarity and end-effects on the relative permeability measurements. Since permeability measurement under the test conditions depends on pressure drop across the core plugs. Cited as : Sidiq, H., Amin, B., Kennaird, T. The study of relative permeability and residual gas saturation at high pressures and high temperatures. Advances in Geo-Energy Research, 2017, 1(1): 64-68, doi: 10.26804/ager.2017.01.06

Modeling wetting-phase relative permeability hysteresis based on subphase evolution

A recently introduced subphase framework for modeling the nonwetting phase relative permeability is extended to the wetting phase. Within this framework, the wetting phase is divided into four subphases, which are distinguished by their connectivity; backbone, dendritic, isolated and corner-film subphases. The subphase saturations evolve according to inter-subphase volume transfer terms, which require modeling. An advantage of distinguishing the subphases is that wetting phase relative permeability relations as functions of these constituent subphases can be developed. In order to develop models for the inter-subphase volume transfer and the wetting phase relative permeability in a strongly wetted system, quasi-static flow simulations in pore networks were conducted to analyze the evolution of the wetting subphases during drainage and imbibition. The simulation results suggest that hysteresis trends apparent in experimentally obtained wetting phase relative permeability curves for Berea sandstone may be explained by accounting for corner-film flow.

Relative permeability of two immiscible fluids flowing through porous media determined by lattice Boltzmann method

This article applied the multiple relaxation time multicomponent/multiphase pseudopotential lattice Boltzmann model to simulate two immiscible fluids flow in 2D porous media, and analyzed the effects of capillary number (Ca), viscosity ratio (M) and wettability on the relative permeability curves. Simulation results indicate that the nonwetting phase (NWP) relative permeability increases with increasing Ca; while the effect of Ca on the wetting phase (WP) relative permeability depends on the wettability. When M>1, the NWP relative permeability increase with increasing M in a strong wetting condition because of the lubricating effect. The amplitude of the NWP relative permeability may even exceed the single phase permeability. However, the exact value of the amplitude and where it occurs depends on M and the structure of the porous media. The WP relative permeability is insensitive to M. When the porous media converts from strong wetting condition to neutral wetting condition, the NWP relative permeability decreases while the WP relative permeability increases.

Influence of relative permeability on injection pressure and plume configuration during CO2 injections in a mafic reservoir

Carbon capture and sequestration projects have traditionally targeted deep sedimentary basins; however, mafic reservoirs may also be attractive targets for CO2 disposal on the basis of permanent mineral trapping over relatively short time scales (101 to 102yr). Nevertheless, CCS development in mafic reservoirs is hampered by substantial uncertainty in fracture-controlled reservoir characteristics, particularly with respect to the effects of multi-phase fluid flow, e.g., relative permeability and capillary pressure. The present study quantifies uncertainty surrounding relative permeability effects in a basalt reservoir by developing a numerical modeling experiment on the basis of site characterization data from the Slack Canyon #2 flow top, which is one of three flow tops comprising the injection zone at the Wallula Basalt Sequestration Pilot Project in southeast Washington State. This numerical modeling experiment controls for the effects of curvature in the relative permeability models by performing an ensemble of 399 CO2 injection simulations with constant geometry and reservoir properties, while systematically varying the phase interference parameter (λ) and residual CO2 saturation (Sgr), which govern wetting and non-wetting phase relative permeability, respectively. The relative permeability parameter space is defined by selecting combinations of λ and Sgr that cover a wide range of experimental laboratory measurements. For each simulation, CO2 is injected into the reservoir for 10 years at a constant rate of 2.78kgs−1 (87,856metrictons(MT)yr−1), which is 10% of the annual injection rate proposed for one injection scenario at the Wallula Site. Results from the ensemble of simulations show that relative permeability alone can account for >50MPa of variability in the injection pressure and a two-fold difference in lateral CO2 plume migration. Additionally, this work shows that curvature in the wetting phase relative permeability model is the stronger influence on reservoir pressure accumulation, while curvature in the non-wetting phase relative permeability model strongly governs CO2 plume geometry.

New ν‐type relative permeability curves for two‐phase flows through subsurface fractures

AbstractAppropriate relative permeability curves for two‐phase flows through subsurface fractures remain unclear. We have conducted decane‐water and nitrogen‐water two‐phase flow experiments and simulations on real variable‐aperture fractures in rocks under confining stress. Experiments have been conducted on fractures for different combinations of rock type (granite or limestone), wettability (contact angle of water: 0° or 90°), and intrinsic fracture permeability (10−11 m2 or 10−10 m2) using different combinations of shear displacement (0 or 1 mm) and effective confining stress (1 or 40 MPa). It has been demonstrated that nonwetting phase relative permeability depends on capillary pressure, except at either a higher contact angle or higher intrinsic permeability (i.e., bigger aperture), where no influence of capillarity is expected from the Young‐Laplace equation. In the absence of an influence of capillarity, relations between wetting and nonwetting phase relative permeabilities agree with that of the X‐type relative permeability curves. In order to determine the relative permeability curves under the influence of capillarity, the experimental results have been analyzed by two‐phase flow simulations of the aperture distributions of the fractures. It has been revealed that nonwetting phase relative permeability becomes zero, even at a small wetting phase saturation of approximately 0.3, while wetting phase relative permeability exhibits Corey‐type behavior, resulting in ν‐shaped relative permeability curves. Similar curves have been reported in the literature, but have not been demonstrated for real fractures. It has been revealed that the new ν‐type and traditional X‐type relative permeability curves are appropriate for describing two‐phase flows through subsurface fractures.