Surfactant floods can attain high oil recovery if optimal conditions with ultralow interfacial tensions (IFT) are achieved in the reservoir. A recently developed equation-of-state (EoS) phase-behavior net-average-curvature (NAC) model based on the hydrophilic-lipophilic difference (HLD-NAC) has been shown to fit and predict phase-behavior data continuously throughout the Winsor I, II, III, and IV regions. The state-of-the-art for viscosity estimation, however, uses empirical nonpredictive based on of fits to salinity scans, even though other parameters change, such as the phase number and compositions. In this paper, we develop the first-of-its-kind microemulsion viscosity model that gives continuous viscosity estimates in composition space. This model is coupled to our existing HLD-NAC phase-behavior EoS. The results show that experimentally measured viscosities in all Winsor regions (two- and three-phase) are a function of phase composition, temperature, pressure, salinity, and the equivalent alkane carbon number (EACN). More specifically, microemulsion viscosities associated with the three-phase invariant point have an M shape as formulation variables change, such as from a salinity scan. The location and magnitude of viscosity peaks in the M are predicted from two percolation thresholds after tuning to viscosity data. These percolation thresholds as well as other model parameters change linearly with EACN and brine salinity. We also show that the minimum viscosity in the M shape correlates linearly with EACN or the viscosity ratio. Other key parameters in the model are also shown to linearly correlate with the EACN and brine salinity. On the basis of these correlations, two- and three-phase microemulsion viscosities are determined in five-component space (surfactant, two brine components, and two oil components) independent of flash calculations. Phase compositions from the EoS flash calculations are entered into the viscosity model. Fits to experimental data are excellent, as well as viscosity predictions for salinity scans not used in the fitting process.
All Science Journal Classification (ASJC) codes
- Energy Engineering and Power Technology
- Geotechnical Engineering and Engineering Geology