Grant: Idea to Innovation
University of Alberta
$125,000.00
Viscoelastic Polymer Modelling for Accurate Predictions of In-Situ Rheology
FY 2019-20
Summary
The synthetic polymer solutions used for chemically enhanced oil recovery (cEOR) processes exhibit apparent viscosity much higher than expected from the shear viscosity. Injectivity will be overestimated with the usage of steady shear rheology. Viscoelastic polymers developed so far relied on the core flood experiments to predict the injectivity of EOR polymers. Performing core flooding with respect to various parameters such as salinity, concentration is a cumbersome process. Quantifying the thickening ability of the polymer solutions may get rid of core flood dependency. Moreoever, the oscillatory rheology used to characterize the viscoelastic properties of the EOR polymers under-predicts the residual oil saturation (Sor) reduction potential. Therefore, the capillary number calculated using the shear viscosity and apparent viscosity does not explain the various residual oil recovery shown by the viscoelastic polymer solutions. Employing the extensional viscosity in the place of shear or apparent viscosity may improve the predictions of capillary number. Thus, it has become a critical issue to investigate the extensional properties of EOR polymers. Azad and Trivedi recently developed a viscoelastic model named a viscoelastic model that can predict the viscoelastic behavior of the synthetic polymer in porous media without core flood experiments. The model has been validated for predicting the viscoelastic onset and the shear thickening regime for varying range of reservoir permeability (200 mD to 37 D), porosity (0.22 to 0.395), brine salinity (0 ppm to 25,200 ppm), concentration (200 ppm to 2500 ppm) and polymer molecular weight (6 MDa to 26 MDa). Since the model validation is performed at room temperature, it is imperative to expand this technology to a wider range temperature that represents in-situ reservoir conditions and thereby creating a database for implementation into commercial tool. Moreover, the model needs to be tested and implemented in a commercial simulator for injectivity and oil recovery predictions.
Program
Idea to Innovation
Recipient
Location
Alberta, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
544482-2019
Name nom
Trivedi, Japan
Department département
Civil and Environmental Engineering
Organization id
9
Institution établissement
University of Alberta
Province en
Alberta
Province fr
Alberta
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2019
Competition year année de concours
2019
Award amount
125000
Program id
I2IPJ
Program name en
Idea to Innovation
Program name fr
De l'idée à l'innovation
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
300
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Energy resources (including production, exploration, processing, distribution and use)
Area of application fr
Ressources d'énergie (production, exploration, traitement, distribution et utilisation de l'énergie)
Research subject code
2302
Research subject group en
Fuel and energy technology
Research subject group fr
Combustibles et technologie de l'énergie
Research subject en
Petroleum engineering, oil and gas recovery
Research subject fr
Génie du pétrole, récupération du pétrole et du gaz
Installment
inst:1 - 1
Partie
1
Nb partie
1
Application title
Viscoelastic Polymer Modelling for Accurate Predictions of In-Situ Rheology
Keyword
NSERC
Application summary
The synthetic polymer solutions used for chemically enhanced oil recovery (cEOR) processes exhibit apparent viscosity much higher than expected from the shear viscosity. Injectivity will be overestimated with the usage of steady shear rheology. Viscoelastic polymers developed so far relied on the core flood experiments to predict the injectivity of EOR polymers. Performing core flooding with respect to various parameters such as salinity, concentration is a cumbersome process. Quantifying the thickening ability of the polymer solutions may get rid of core flood dependency. Moreoever, the oscillatory rheology used to characterize the viscoelastic properties of the EOR polymers under-predicts the residual oil saturation (Sor) reduction potential. Therefore, the capillary number calculated using the shear viscosity and apparent viscosity does not explain the various residual oil recovery shown by the viscoelastic polymer solutions. Employing the extensional viscosity in the place of shear or apparent viscosity may improve the predictions of capillary number. Thus, it has become a critical issue to investigate the extensional properties of EOR polymers. Azad and Trivedi recently developed a viscoelastic model named a viscoelastic model that can predict the viscoelastic behavior of the synthetic polymer in porous media without core flood experiments. The model has been validated for predicting the viscoelastic onset and the shear thickening regime for varying range of reservoir permeability (200 mD to 37 D), porosity (0.22 to 0.395), brine salinity (0 ppm to 25,200 ppm), concentration (200 ppm to 2500 ppm) and polymer molecular weight (6 MDa to 26 MDa). Since the model validation is performed at room temperature, it is imperative to expand this technology to a wider range temperature that represents in-situ reservoir conditions and thereby creating a database for implementation into commercial tool. Moreover, the model needs to be tested and implemented in a commercial simulator for injectivity and oil recovery predictions.
