Oil-recovery predictions for surfactant polymer flooding

• Published in: Journal of petroleum science & engineering 2013-12, Vol.112, p.341-350
• Main Authors: Rai, Khyati, Johns, Russell T., Delshad, Mojdeh, Lake, Larry W., Goudarzi, Ali
• Format: Article
• Language: English
• Subjects: Applied sciences; Crude oil; Crude oil, natural gas and petroleum products; Depletion; Energy; Exact sciences and technology; Flooding; Floods; Fuels; Mathematical models; Oil recovery; reservoir simulation; Reservoirs; response surfaces; screening model; Spreadsheets; surfactant–polymer flooding
• ISSN: 0920-4105; 1873-4715
• DOI: 10.1016/j.petrol.2013.11.028

There is increasing interest in surfactant–polymer (SP) flooding because of the need to increase oil production from depleted and water flooded reservoirs. Prediction of oil recovery from SP flooding, however, is complex and time consuming. Thus, a quick and easy method is needed to screen reservoirs for potential SP floods. This paper presents a scaling model that is capable of producing reasonable estimates of oil recovery for a SP flood using a simple spreadsheet calculation. The model is also useful for initial SP design. We present key dimensionless groups that control recovery for a SP flood. The proper physics for SP floods including the optimal salinity in the three-phase region and the trapping number for residual oil saturation determination has been incorporated. Based on these groups, a Box–Behnken experimental design is performed to generate response surface fits for oil recovery prediction at key dimensionless times. The response surfaces derived can be used to estimate the oil recovery potential for any given reservoir and are ideal for screening large databases of reservoirs to identify the most attractive chemical flooding candidates. The response function can also be used for proper design of key parameters for SP flooding. Our model will aid engineers to understand how key parameters affect oil recovery without performing time consuming chemical simulations. This is the first time that dimensionless groups for SP flooding have been derived comprehensively to obtain a response function of oil recovery as a function of dimensionless groups. •Surfactant–polymer (SP) has been scaled for the first time.•The effect of heterogeneity was included in the set of dimensionless groups.•The most important dimensionless groups were determined using t statistics.•The screening model is ideal in quickly screening for surfactant–polymer flooding.