چكيده به لاتين
The surface active agents (surfactants) as the most important chemical compounds in chemical EOR process, can release significant amounts of residual oil trapped in porous media as well as changing the wettability of reservoir rock by reducing the interfacial tension (IFT) between injected water and reservoir oil. During surfactant passing through the porous space, some amounts of this compound absorb on reservoir rock.
Due to the role of surfactants in enhanced oil recovery, it is necessary to provide methods to predict their performances in this process. In this study, a seri of five data-based mathematical models including a model for IFT of brine/ crude oil system, a model for IFT of brine/ crude oil/ non-ionic surfactant system, two models for IFT of brine/ crude oil/ anionic surfactant system and a model for equilibrium adsorption concentration of surfactants on rock have been produced. In developing these models, QSPR method was used to express the effects of surfactant molecular structure on objective functions and genetic programming (GP), as one of the most powerful modeling tools, has been used to correlate between independent variables and the objective function. Applications of these models in reservoir simulators can provide appropriate predictions for recovery factor of surfactant flooding as well as other factors and parameters associated with interfacial tension and surfactant absorption in the reservoir. The correlation coefficients (R2) of the new developed models are 0.9745, 0.9683, 0.946, 0.9387 and 0.9874, respectively and root-mean-squaire deviations (RMSD) of these models are 1.861 mN/m, 2.1201 mN/m, 3.4439 mN/m, 3.3261 mN/m and 0.5624 mmol/L, respectively.
