Viscoelastic Polymer Modelling for Accurate Predictions of In-Situ Rheology

点击翻译按钮获取中文摘要

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.