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

Al-Ibadi, Hasan; Stephen, Karl Dunbar; Mackay, Eric James

doi:10.2118/192074-pa

Cited by 8 publications

(12 citation statements)

References 37 publications

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“…For each cell we show (a) water saturation, (b) surfactant concentration (c) water relative permeability, (d) oil relative permeability, (e) The logarithm of the capillary number and for flow from cell i to i+1, (f) fractional flow. This analysis follows that presented in [28] and [30] for low salinity waterflooding with a similar hypothesis.…”

Section: Numerical Computation Of the Mobility And Weighting Functionsupporting

confidence: 90%

“…9) was observed to have pulses which grew progressively as each cell transitioned from immiscible to miscible behavior and also as the viscosity changed. Similar effects have been reported previously albeit for low salinity waterflooding [28][29][30] where the change in relative permeability (wettability) as a function of salinity appeared to generate equivalent pulses. We adopt a similar analysis and interpretation here.…”

Section: Numerical Computation Of the Mobility And Weighting Functionsupporting

confidence: 87%

“…As mentioned above, Al Idadi et al [28][29][30] have shown similar such pulses for low salinity waterflooding. In that case relative permeability is changed rapidly due to the reduction of salinity as injected water arrives.…”

Section: Numerical Computation Of the Mobility And Weighting Functionsupporting

confidence: 56%

“…Key mechanisms influencing the surfactant flood model may be used to further understand the origin and the spread of the pulses. The switch in relative permeability seems to have been important as has been reported for low salinity waterflooding by Al-Ibadi et al [28][29][30]. The numerical solution of the base case model with the modified Courant condition was tested according to various adsorption values derived using the Langmuir-type isotherm variable.…”

Section: Discussionmentioning

confidence: 99%

“…Meanwhile, instability occurs when numerical effects result in a divergence of the numerical solution as a function of small perturbations. The numerical effects, also known as numerical dispersion, may also result in pulses and convergence problems [28][29][30]. They may be imprecise but stable, nonetheless.…”

Section: Simulations Of Surfactant Floodingmentioning

confidence: 99%

See 4 more Smart Citations

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Akinyele¹,

Stephen²

2021

Preprint

Self Cite

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Numerical simulation of surfactant flooding using conventional reservoir simulation models can lead to unreliable forecasts and bad decisions due to the appearance of numerical effects. The simulations give approximate solutions to systems of nonlinear partial differential equations describing the physical behavior of surfactant flooding by combining multiphase flow in porous media with surfactant transport. The approximations are made by discretization of time and space which can lead to spurious pulses or deviations in the model outcome. In this work, the black oil model was simulated using the decoupled implicit method for various conditions of reservoir scale models to investigate behaviour in comparison with the analytical solution obtained from fractional flow theory. We investigated changes to cell size and time step as well as the properties of the surfactant and how it affects miscibility and flow. The main aim of this study was to understand pulse like behavior that has been observed in the water bank to identify cause and associated conditions. We report for the first time that the pulses occur in association with the simulated surfactant water flood front and are induced by a sharp change in relative permeability as the interfacial tension changes. Pulses are diminished when the adsorption rate was within the value of 0.0002kg/kg to 0.0005kg/kg. The pulses are absent for high resolution model of 5000 cells in x direction with a typical cell size as used in well-scale models. The growth or damping of these pulses may vary from case to case but in this instance was a result of the combined impact of relative mobility, numerical dispersion, interfacial tension and miscibility. Oil recovery under the numerical problems reduced the performance of the flood, due to large amounts of pulses produced. Thus, it is important to improve existing models and use appropriate guidelines to stop oscillations and remove errors.

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Section: Numerical Computation Of the Mobility And Weighting Functionsupporting

confidence: 90%

Section: Numerical Computation Of the Mobility And Weighting Functionsupporting

confidence: 87%

Section: Numerical Computation Of the Mobility And Weighting Functionsupporting

confidence: 56%

Section: Discussionmentioning

confidence: 99%

Section: Simulations Of Surfactant Floodingmentioning

confidence: 99%

See 3 more Smart Citations

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Akinyele¹,

Stephen²

2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Akinyele

Stephen

2022

Comput Geosci

View full text Add to dashboard Cite

Numerical simulation of surfactant flooding using conventional reservoir simulation models can lead to unreliable forecasts and bad decisions due to the appearance of numerical effects. The simulations give approximate solutions to systems of nonlinear partial differential equations describing the physical behavior of surfactant flooding by combining multiphase flow in porous media with surfactant transport. The approximations are made by discretization of time and space which can lead to spurious pulses or deviations in the model outcome. In this work, the black oil model was simulated using the decoupled implicit method for various conditions of reservoir scale models to investigate behavior in comparison with the analytical solution obtained from fractional flow theory. We investigated changes to cell size and time step as well as the properties of the surfactant and how it affects miscibility and flow. The main aim of this study was to understand pulse like behavior in the water bank, which we report for the first time, Our aim was to identify their cause and associated conditions. The pulses are induced by a sharp change in relative permeability as the interfacial tension changes. Pulses are diminished when adsorption is modeled, and ranged from 0.0002 kg/kg to 0.0005 kg/kg. The pulses are absent for high-resolution model of 5000 cells in x direction with a typical cell size as used in well-scale models. The growth or dampening of these pulses may vary from case to case but in this instance was a result of the combined impact of relative mobility, numerical dispersion, interfacial tension and miscibility. Oil recovery under the numerical problems reduced the performance of the flood, due to large amounts of pulses produced. Thus, it is important to improve existing models and use appropriate guidelines to stop oscillations and remove errors.

show abstract

Experimental study of the low salinity water injection process in the presence of scale inhibitor and various nanoparticles

Khormali

Koochi

Varfolomeev

et al. 2022

J Petrol Explor Prod Technol

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In this work, the process of low salinity water injection (LSWI) into reservoirs at various salt concentrations was simulated in order to study the change in the oil recovery factor during oil production. The simulation results of the recovery factor were compared with the experimental data. The results demonstrated that the simulation data were in good agreement with the experimental results. In addition, the formation damage (rock permeability reduction) in carbonate core samples was evaluated through coreflood experiments during LSWI in the range of salt concentration and temperature of 1500–4000 ppm and 25–100 °C, respectively. In the worst scenario of LSWI, the rock permeability has reached about 83% of the initial value. Our previous correlation was used to predict the formation damage in LSWI. In this case, the R-squared value between predicted and experimental data of rock permeability ratios was more than 0.97. Furthermore, the recovery factor during LSWI was analyzed with and without the use of DTPMP scale inhibitor (diethylenetriamine penta (methylene phosphonic acid)), and various nanoparticles (TiO2, SiO2, Al2O3). The results of the coreflood experiments showed that the use of scale inhibitor provides an increase in the recovery factor by more than 8%. In addition, the highest recovery factor was observed in the presence of SiO2 nanoparticles at 0.05 wt.%. The oil displacement during LSWI in the porous media with SiO2 particles was better than TiO2 and Al2O3. The recovery factor in the presence of SiO2, TiO2, and Al2O3 with DTPMP was 72.2, 62.4, and 59.8%, respectively. Among the studied nanoparticles, the lowest values of the oil viscosity and interfacial tension (IFT) between oil and water were observed when using SiO2. Moreover, the contact angle was increased by increasing the brine concentration. The contact angle with the use of SiO2, TiO2, and Al2O3 at 0.05 wt.% was reduced by 11.2, 10.6, and 9.9%, respectively.

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

Cited by 8 publications

References 37 publications

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Experimental study of the low salinity water injection process in the presence of scale inhibitor and various nanoparticles

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