Scaling Up Low-Salinity Waterflooding in Heterogenous Reservoirs

SPE Journal ◽  
2021 ◽  
pp. 1-22
Author(s):  
Hasan Al-Ibadi ◽  
Karl Stephen ◽  
Eric Mackay
Keyword(s):  
Relative Permeability ◽  
Coarse Grid ◽  
Numerical Dispersion ◽  
Absolute Permeability ◽  
Scale Model ◽  
Salinity Range ◽  
Fine Scale ◽  
Fractional Flow ◽  
Low Salinity ◽  
Low Salinity Waterflooding

SummaryModeling the dynamic fluid behavior of low-salinity waterflooding (LSWF) at the reservoir scale is a challenge that requires a coarse-grid simulation to enable prediction in a feasible time scale. However, evidence shows that using low-resolution models will result in a considerable mismatch compared with an equivalent fine-scale model with the potential of strong, numerically induced pulses and other dispersion-related effects. This work examines two new upscaling methods that have been applied to improve the accuracy of predictions in a heterogeneous reservoir where viscous crossflow takes place.We apply two approaches to upscaling to bring the flow prediction closer to being exact. In the first method, we shift the effective-salinity range for the coarse model using algorithms that we have developed to correct for numerical dispersion and associated effects. The second upscaling method uses appropriately derived pseudorelative permeability curves. The shape of these new curves is designed using a modified fractional-flow analysis of LSWF that captures the relationship between dispersion and the waterfront velocities. This second approach removes the need for explicit simulation of salinity transport to model oil displacement. We applied these approaches in layered models and for permeability distributed as a correlated random field.Upscaling by shifting the effective-salinity range of the coarse-grid model gave a good match to the fine-scale scenario, while considerable mismatch was observed for upscaling of the absolute permeability alone. For highly coarsened models, this method of upscaling reduced the appearance of numerically induced pulses. On the other hand, upscaling by using a single (pseudo)relative permeability produced more robust results with a very promising match to the fine-scale scenario. These methods of upscaling showed promising results when they were used to scale up fully communicating and noncommunicating layers as well as models with randomly correlated permeability.Unlike documented methods in the literature, these newly derived methods take into account the substantial effects of numerical dispersion and effective concentration on fluid dynamics using mathematical tools. The methods could be applied for other models where the phase mobilities change as a result of an injected solute, such as surfactant flooding and alkaline flooding. Usually these models use two sets of relative permeability and switch from one to another as a function of the concentration of the solute.

Extended Fractional-Flow Model of Low-Salinity Waterflooding Accounting for Dispersion and Effective Salinity Range

SPE Journal ◽  
2019 ◽  
Vol 24 (06) ◽  
pp. 2874-2888 ◽  
Author(s):  
Hasan Al–Ibadi ◽  
Karl D. Stephen ◽  
Eric J. Mackay
Keyword(s):  
Relative Permeability ◽  
Flow Behavior ◽  
Flow Analysis ◽  
Salinity Range ◽  
Fractional Flow ◽  
Low Salinity ◽  
Low Salinity Water ◽  
Low Salinity Waterflooding ◽  
Salinity Water ◽  
The Impact

Summary Low–salinity waterflooding (LSWF) is an emergent technology developed to increase oil recovery. Laboratory–scale testing of this process is common, but modeling at the production scale is less well–reported. Various descriptions of the functional relationship between salinity and relative permeability have been presented in the literature, with respect to the differences in the effective salinity range over which the mechanisms occur. In this paper, we focus on these properties and their impact on fractional flow of LSWF at the reservoir scale. We present numerical observations that characterize flow behavior accounting for dispersion. We analyzed linear and nonlinear functions relating salinity to relative permeability and various effective salinity ranges using a numerical simulator. We analyzed the effect of numerical and physical dispersion of salinity on the velocity of the waterflood fronts as an expansion of fractional–flow theory, which normally assumes shock–like behavior of water and concentration fronts. We observed that dispersion of the salinity profile affects the fractional–flow behavior depending on the effective salinity range. The simulator solution is equal to analytical predictions from fractional–flow analysis when the midpoint of the effective salinity range lies between the formation and injected salinities. However, retardation behavior similar to the effect of adsorption occurs when these midpoint concentrations are not coincidental. This alters the velocities of high– and low–salinity water fronts. We derived an extended form of the fractional–flow analysis to include the impact of salinity dispersion. A new factor quantifies a physical or numerical retardation that occurs. We can now modify the effects that dispersion has on the breakthrough times of high– and low–salinity water fronts during LSWF. This improves predictive ability and also reduces the requirement for full simulation.

Fast Upscaling of Polymer Flood Simulations Using Fractional Flow and Scaled Mobilities

2021 ◽  
Author(s):  
Hasan Al-Ibadi ◽  
Karl Stephen ◽  
Eric Mackay
Keyword(s):  
Relative Permeability ◽  
Control Method ◽  
Pressure Profile ◽  
Polymer Flooding ◽  
Mobility Control ◽  
Scale Model ◽  
Fine Scale ◽  
Fractional Flow ◽  
Water Viscosity ◽  
Flow Mobility

Abstract We introduce a pseudoisation method to upscale polymer flooding in order to capture the flow behaviour of fine scale models. This method is also designed to improve the predictability of pressure profiles during this process. This method controls the numerical dispersion of coarse grid models so that we are able to reproduce the flow behaviour of the fine scale model. To upscale polymer flooding, three levels of analysis are required such that we need to honour (a) the fractional flow solution, (b) the water and oil mobility and (c) appropriate upscaling of single phase flow. The outcome from this analysis is that a single pseudo relative permeability set that honours the modification that polymer applies to water viscosity modification without explicitly changing it. The shape of relative permeability can be chosen to honour the fractional flow solution of the fine scale using the analytical solution. This can result in a monotonic pseudo relative permeability set and we call it the Fractional-Flow method. To capture the pressure profile as well, individual relative permeability curves must be chosen appropriately for each phase to ensure the correct total mobility. For polymer flooding, changes to the water relative permeability included the changes to water viscosity implicitly thus avoiding the need for inclusion of a polymer solute. We call this type of upscaling as Fractional-Flow-Mobility control method. Numerical solution of the upscaled models, obtained using this method, were validated against fine scale models for 1D homogenous model and as well as 3D models with randomly distributed permeability for various geological realisations. The recovery factor and water cut matched the fine scale model very well. The pressure profile was reasonably predictable using the Fractional-Flow-Mobility control method. Both Fractional-Flow and Fractional-flow-Mobility control methods can be calculated in advance without running a fine scale model where the analysis is based on analytical solution even though produced a non-monotonic pseudo relative permeability curve. It simplified the polymer model so that it is much easier and faster to simulate. It offers the opportunity to quickly predict oil and water phase behaviour.

Novel Observations of Salinity Transport in Low-Salinity Waterflooding

SPE Journal ◽  
2019 ◽  
Vol 24 (03) ◽  
pp. 1108-1122 ◽  
Author(s):  
Hasan Al-Ibadi ◽  
Karl Stephen ◽  
Eric Mackay
Keyword(s):  
Analytical Solution ◽  
Weighting Function ◽  
Numerical Dispersion ◽  
Salinity Range ◽  
Low Salinity ◽  
Salinity Profile ◽  
Salinity Transport ◽  
Advection Term ◽  
Input Parameters ◽  
Low Salinity Waterflooding

Summary Low-salinity waterflooding (LSWF) is a promising process that could lead to increased oil recovery. To date, the greatest attention has been paid to the complex oil/water/rock chemical reactions that might explain the mechanisms of LSWF, and it is generally accepted that these result in behavior equivalent to changing oil and water mobility. This behavior is modeled using an effective salinity range and weighting function to gradually switch from high- to low-salinity relative permeability curves. There has been limited attention on physical transport of fluids during LSWF, particularly at large scale. We focus on how the salinity profile interacts with water fronts through the effective salinity range and dispersion to alter the transport behavior and change the flow velocities, particularly for the salinity profile. We examined a numerical simulation of LSWF at the reservoir scale. Various representations of the effective salinity range and weighting function were also examined. The dispersion of salinity was compared with a theoretical form of numerical dispersion based on input parameters. We also compared salinity movement with the analytical solution of the conventional dispersion/advection equation. From simulations we observed that salinity is dispersed as analytically predicted, although the advection velocity might be changed. In advection-dominated flow, the salinity profile moves at the speed of the injected water. However, as dispersion increases, the mixing zone falls under the influence of the faster-moving formation water and, thus, speeds up. To predict the salinity profile theoretically, we have modified the advection term of the analytical solution as a function of the formation- and injected-water velocities, Péclet number, and effective salinity range. This important result enables prediction of the salinity transport by this newly derived modification of the analytical solution for 1D flow. We can understand the correction to the flow behavior and quantify it from the model input parameters. At the reservoir scale, we typically simulate flow on coarse grids, which introduces numerical dispersion or must include physical dispersion from underlying heterogeneity. Corrections to the equations can contribute to improving the precision of the coarse-scale models, and, more generally, the suggested form of the correction can also be used to calculate the movement of any solute that transports across an interface between two mobile fluids. We can also better understand the relative behaviors of passive tracers and those that are adsorbed.

An Analysis of Numerically Induced Pulses in Simulations of Low-Salinity Waterflooding and Their Reduction by Flow Upscaling

SPE Journal ◽  
2021 ◽  
pp. 1-21
Author(s):  
Hasan Al-Ibadi ◽  
Karl D. Stephen ◽  
Eric Mackay
Keyword(s):  
Oil Recovery ◽  
Flow Behavior ◽  
Scale Up ◽  
Numerical Dispersion ◽  
Salinity Range ◽  
Fractional Flow ◽  
Numerical Errors ◽  
Low Salinity ◽  
Effective Manner ◽  
Courant Condition

Summary Numerical fidelity is required when using simulations to predict enhanced-oil-recovery (EOR) processes. In this paper, we investigate the conditions that lead to numerical errors when simulating low-salinity (LS) waterflooding (LSWF). We also examine how to achieve more accurate simulation results by scaling up the flow behavior in an effective manner. An implicit finite-difference numerical solver was used to simulate LSWF. The accuracy of the numerical solution has been examined as a function of changing the length of the grid cell and the timestep. Previously we have shown that numerical dispersion induces a physical retardation such that the LS front slows down while the formation water front speeds up. We also report for the first time that pulses can be generated as numerical artifacts in coarsely gridded simulations of LSWF. These effects reflect the interaction of dispersion, the effective-salinity range, and the use of upstream weighting during calculation, and can corrupt predictions of flow behavior. The effect of the size of the timestep was analyzed with respect to the Courant condition, traditionally related to explicit numerical schemes and also numerical stability conditions. We also investigated some of the nonlinear elements of the simulation model, such as the differences between the concentrations of connate water salinity and the injected brine, effective-salinity-concentration range, and the net mobility change on fluids through changing the salinity. We report that to avoid pulses it is necessary, but not sufficient, to meet the Courant condition relating timestep size to cell size. We have also developed two approaches that can be used to scale up simulations of LSWF and tackle the numerical problems. The first method is dependent on a mathematical relationship between the fractional flow, effective-salinity range, and the Péclet number and treats the effective-salinity range as a pseudofunction. The second method establishes an unconventional proxy method equivalent to pseudorelative permeabilities. A single table of pseudorelative permeability data can be used for a waterflood instead of two tables, as is usual for LSWF. This is a novel approach that removes the need for relative permeability interpolation during the simulation. Overall, by avoiding numerical errors, we help engineers to more efficiently and accurately assess the potential for improving oil recovery using LSWF and thus optimize field development. We also avoid the numerical pulses inherent in the traditional LSWF model.

Two-Stage Upscaling of Two-Phase Flow: From Core to Simulation Scale

SPE Journal ◽  
2006 ◽  
Vol 11 (03) ◽  
pp. 304-316 ◽  
Author(s):  
Arild Lohne ◽  
George A. Virnovsky ◽  
Louis J. Durlofsky
Keyword(s):  
Capillary Pressure ◽  
Effective Properties ◽  
Absolute Permeability ◽  
Scale Model ◽  
Phase Flow ◽  
Fine Scale ◽  
Coarse Scale ◽  
Two Stage ◽  
Two Phase ◽  
Rate Dependent

Summary In the coarse-scale simulation of heterogeneous reservoirs, effective or upscaled flow functions (e.g., oil and water relative permeability and capillary pressure) can be used to represent heterogeneities at subgrid scales. The effective relative permeability is typically upscaled along with absolute permeability from a geocellular model. However, if no subgeocellular-scale information is included, the potentially important effects of smaller-scale heterogeneities (on the centimeter to meter scale) in both capillarity and absolute permeability will not be captured by this approach. In this paper, we present a two-stage upscaling procedure for two-phase flow. In the first stage, we upscale from the core (fine) scale to the geocellular (intermediate) scale, while in the second stage we upscale from the geocellular scale to the simulation (coarse) scale. The computational procedure includes numerical solution of the finite-difference equations describing steady-state flow over the local region to be upscaled, using either constant pressure or periodic boundary conditions. In contrast to most of the earlier investigations in this area, we first apply an iterative rate-dependent upscaling (iteration ensures that the properties are computed at the appropriate pressure gradient) rather than assume viscous or capillary dominance and, second, assess the accuracy of the two-stage upscaling procedure through comparison of flow results for the coarsened models against those of the finest-scale model. The two-stage method is applied to synthetic 2D reservoir models with strong variation in capillarity on the fine scale. Accurate reproduction of the fine-grid solutions (simulated on 500'500 grids) is achieved on coarse grids of 10'10 for different flow scenarios. It is shown that, although capillary forces are important on the fine scale, the assumption of capillary dominance in the first stage of upscaling is not always appropriate, and that the computation of rate-dependent effective properties in the upscaling can significantly improve the accuracy of the coarse-scale model. The assumption of viscous dominance in the second upscaling stage is found to be appropriate in all of the cases considered. Introduction Because of computational costs, field-simulation models may have very coarse cells with sizes up to 100 to 200 m in horizontal directions. The cells are typically populated with effective properties (porosity, absolute permeability, relative permeabilities, and capillary pressure) upscaled from a geocellular (or geostatistical) model. In this way, the effects of heterogeneity on the geocellular scale will be included in the large-scale flow calculations. The cell sizes in geocellular models may be on the order of 20 to 50 m in horizontal directions. However, heterogeneities on much smaller scales (cm- to m- scale) may have a significant influence on the reservoir flow (Coll et al. 2001; Honarpour et al. 1994), and this potential effect cannot be captured if the upscaling starts at the geocellular scale.

Pore-Scale Simulation of the Interplay between Wettability, Capillary Number, and Salt Dispersion on the Efficiency of Oil Mobilization by Low-Salinity Waterflooding

SPE Journal ◽  
2021 ◽  
pp. 1-22
Author(s):  
Arman Namaee-Ghasemi ◽  
Shahab Ayatollahi ◽  
Hassan Mahani
Keyword(s):  
Capillary Pressure ◽  
Oil Recovery ◽  
Capillary Number ◽  
Salinity Range ◽  
Pore Geometry ◽  
Side Channel ◽  
Dispersion Pattern ◽  
Pore Scale ◽  
Low Salinity ◽  
Low Salinity Waterflooding

Summary Nonuniform mixing during low-salinity waterflooding (LSWF) is a function of the pore geometry and flow patterns within the porous system. Salinity-dependent wettability alteration (WA) changes the entry capillary pressure, which may mobilize the trapped oil depending on the flow regime and salt dispersion pattern. The complex interplay between the wettability, capillary number (NCa), and salt dispersion caused by pore-scale heterogeneity on the efficiency of LSWF is not well understood. In this paper, direct numerical simulations in a pore-doublet model (PDM) were carried out with OpenFOAM® (OpenCFD, Berkshire, UK) using the volume-of-fluid (VOF) method. Oil trapping and remobilization were studied at relevant NCa as low as 10−6 under different initial wettability states. Depending on the effective salinity ranges (ESRs) for the low-salinity effect (LSE), three WA models were implemented, and the effects of WA degree and salinity distribution on LSWF flow dynamics were investigated. The slow process of WA by means of thin film phenomena was captured by considering a diffuse interface at the three-phase contact line. Because of the pore structure of the pore doublet, only in nonwater-wet cases, oil is trapped in the narrower side channel (NSC) after high-salinity waterflooding (HSWF) and may be remobilized by LSWF. In strongly oil-wet cases, oil is recovered gradually by LSWF by means of a film-flow mechanism near the outlet. In moderately oil-wet cases, however, the entire trapped oil ganglion can be mobilized, provided that the entry capillary pressure is sufficiently reduced. The degree of WA, ESR, kinetics of WA, and the wettability of pore surface at the outlet are determining factors in the drainage of the trapped oil. The salt dispersion pattern in the flowing region [i.e., wider side channel (WSC)] controls the wettability distribution and the rate and magnitude of oil recovery from the stagnant region (i.e., NSC). The difference between the WA models is more apparent near the outlet, where the salinity profile is more dispersed. The ESR in which WA occurs determines the speed of the entry capillary pressure reduction and, thus, the recovery factor. In cases where WA occurs at a salinity threshold (ST), the highest recovery is obtained, whereas with the full-salinity-range WA model, the oil recovery performance is lowest. From the capillary desaturation perspective, it is found that the LSE becomes more pronounced when NCa is less than 10−5, and the dispersion regime is in the power-law interval. Because the adverse effect of salt dispersion in the flowing region is delayed, the LSE is intensified. For the simulations to be representative of the actual conditions in the porous medium, much lower NCa than currently used in many research works must be studied. Otherwise, the simulations may lead to over- or underestimation of the LSE. The synergetic or antagonistic effects caused by the interplay between viscous and capillary forces and dispersion may lead to total recovery or entrapment of oil, regardless of WA. Based on the pore geometry, initial wettability state, and balance of forces, the mobilized oil may flow past the conjunction (favorable) or in the backward direction (unfavorable) to the WSC and get retrapped. Successful drainage of oil from the pore system after WA is essential for observing incremental oil recovery by LSWF.

scholarly journals Improvement of Relative Permeability and Wetting Condition of Sandstone by Low Salinity Waterflooding

2019 ◽  
Vol 221 ◽  
pp. 012044
Author(s):  
Falan Srisuriyachai ◽  
Monrawee Pancharoen ◽  
Rapheepan Laochamroonvoraponse ◽  
Pattraporn Juckthong ◽  
Arisara Kukiattikoon ◽  
...  
Keyword(s):  
Relative Permeability ◽  
Low Salinity ◽  
Low Salinity Waterflooding
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