Estimation of the rheological curve of HPAM solutions from measurements using the Brookfield viscometer

In recent studies, Jouenne and Levache (2020) proposed a rheological model for polymeric solutions used in enhanced oil recovery, based essentially on a variable obtained as the product of the intrinsic viscosity of the solution and the concentration of the polymer. Using this variable, the authors propose expressions in which is possible to predict the coefficients of Carreau-Yasuda's law that are of interest: the viscosity under zero shear regime eta(0), the power index eta, and the relaxation time lambda. In this work, the robustness of this model is improved using a machine learning technique and a larger database than the one previously considered. Based on this enhanced model, a technique is proposed to estimate the intrinsic viscosity of the solutions and the parameters of Carreau-Yasuda's law using only the measurement of viscosity at a shear rate of 7.3 s(-1). The results obtained with this approach are compared to those issued from experimental data finding satisfactory results. The use of this strategy is of particular interest for field studies or laboratories that only have as available instruments the Brookfield viscometer.