Grant: Discovery Grants Program - Individual
University of Regina
$22,000.00
Improving the efficiency of solvent-based recovery technologies for thin net pay heavy oil reservoirs
EF 2012-13
Résumé
Thin net pay heavy oil reservoirs are less attractive for SAGD because of the reduced economics and increased environmental footprints. VAPEX, similar to SAGD, but using solvent to reduce the oil viscosity, has been proposed to produce thin net pay heavy oil reservoirs in an environmentally sustainable way.
This study will integrate 1-D, 2-D and 3-D physical and mathematical modeling studies to intensively present and model the mechanisms of solvent injection in heavy oil reservoirs, to optimize solvent injection processes, and eventually to enhance the oil production efficiency. Experimental study will be conducted to measure the three main mechanisms involved in solvent injection processes: molecular diffusion/dispersion, viscosity fingering and non-equilibrium phase behavior. A novel semi-analytical approach developed by the applicant will be applied to improve the mathematical modeling in order to more accurately predict the performance of solvent injection in heavy oil reservoirs and reduce the uncertainty of heavy oil reservoir development plan. With the improved simulation and 3-D physical modeling studies, the following technologies will be developed and validated to improve the efficiency of solvent injection process in thin net pay heavy oil reservoirs: (1) Approaches, e.g. electrical heating, to improve horizontal well conformance; (2) Optimized well pattern, e.g. Tee-well pattern or multi-lateral wellbores, and optimized solvent injection strategy; (3) solvent trapping technologies to reduce solvent oil ratio. The upscaling approaches will also be developed to scale up the laboratory results to field scale.
This work is an important step to achieve our long-term objective, which is to develop ""green"" technologies for the next generations as well as train them on how to generate knowledge and be creative. To meet the objective, a reservoir physical and mathematical modeling group will be established. This group will have the capacity to train six undergraduate students, six master students and three PhD students simultaneously. This will help Canada remain the leadership in sustainable energy technology development and education.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Saskatchewan, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
372047-2009
Name nom
Zeng, Fanhua
Department département
Engineering, Faculty of
Organization id
17
Institution établissement
University of Regina
Province en
Saskatchewan
Province fr
Saskatchewan
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2012
Competition year année de concours
2009
Award amount
22000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
4
Committee name en
Chem. & Metallurgical Eng.
Committee name fr
Génies chimique et métal.
Area of application code
301
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Oil, gas and coal
Area of application fr
Pétrole, gaz et charbon
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
Partie
4
Nb partie
5
Application title
Improving the efficiency of solvent-based recovery technologies for thin net pay heavy oil reservoirs
Keyword
NSERC
Application summary
Thin net pay heavy oil reservoirs are less attractive for SAGD because of the reduced economics and increased environmental footprints. VAPEX, similar to SAGD, but using solvent to reduce the oil viscosity, has been proposed to produce thin net pay heavy oil reservoirs in an environmentally sustainable way.
This study will integrate 1-D, 2-D and 3-D physical and mathematical modeling studies to intensively present and model the mechanisms of solvent injection in heavy oil reservoirs, to optimize solvent injection processes, and eventually to enhance the oil production efficiency. Experimental study will be conducted to measure the three main mechanisms involved in solvent injection processes: molecular diffusion/dispersion, viscosity fingering and non-equilibrium phase behavior. A novel semi-analytical approach developed by the applicant will be applied to improve the mathematical modeling in order to more accurately predict the performance of solvent injection in heavy oil reservoirs and reduce the uncertainty of heavy oil reservoir development plan. With the improved simulation and 3-D physical modeling studies, the following technologies will be developed and validated to improve the efficiency of solvent injection process in thin net pay heavy oil reservoirs: (1) Approaches, e.g. electrical heating, to improve horizontal well conformance; (2) Optimized well pattern, e.g. Tee-well pattern or multi-lateral wellbores, and optimized solvent injection strategy; (3) solvent trapping technologies to reduce solvent oil ratio. The upscaling approaches will also be developed to scale up the laboratory results to field scale.
This work is an important step to achieve our long-term objective, which is to develop ""green"" technologies for the next generations as well as train them on how to generate knowledge and be creative. To meet the objective, a reservoir physical and mathematical modeling group will be established. This group will have the capacity to train six undergraduate students, six master students and three PhD students simultaneously. This will help Canada remain the leadership in sustainable energy technology development and education.