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Artificial Neural Network Model to Estimate the Viscosity of Polymer Solutions for Enhanced Oil Recovery

1
Department of Energy and Resources Engineering, Korea Maritime and Ocean University, Yeongdo-Gu, Busan 49112, Korea
2
Department of Petroleum and Geosystems Engineering, The University of Texas at Austin, Austin, TX 78712-1585, USA
*
Author to whom correspondence should be addressed.
This paper is an extended version of a paper presented at the 23rd International Offshore and Polar Engineering Conference (ISOPE-2013), Anchorage, AK, USA, 30 June–5 July 2013.
Academic Editor: Christian Dawson
Appl. Sci. 2016, 6(7), 188; https://doi.org/10.3390/app6070188
Received: 24 May 2016 / Revised: 21 June 2016 / Accepted: 22 June 2016 / Published: 29 June 2016
Polymer flooding is now considered a technically- and commercially-proven method for enhanced oil recovery (EOR). The viscosity of the injected polymer solution is the key property for successful polymer flooding. Given that the viscosity of a polymer solution has a non-linear relationship with various influential parameters (molecular weight, degree of hydrolysis, polymer concentration, cation concentration of polymer solution, shear rate, temperature) and that measurement of viscosity based on these parameters is a time-consuming process, the range of solution samples and the measurement conditions need to be limited and precise. Viscosity estimation of the polymer solution is effective for these purposes. An artificial neural network (ANN) was applied to the viscosity estimation of FlopaamTM 3330S, FlopaamTM 3630S and AN-125 solutions, three commonly-used EOR polymers. The viscosities measured and estimated by ANN and the Carreau model using Lee’s correlation, the only method for estimating the viscosity of an EOR polymer solution in unmeasured conditions, were compared. Estimation accuracy was evaluated by the average absolute relative deviation, which has been widely used for accuracy evaluation of the results of ANN models. In all conditions, the accuracy of the ANN model is higher than that of the Carreau model using Lee’s correlation. View Full-Text
Keywords: enhanced oil recovery; polymer flood; artificial neural network; viscosity enhanced oil recovery; polymer flood; artificial neural network; viscosity
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MDPI and ACS Style

Kang, P.-S.; Lim, J.-S.; Huh, C. Artificial Neural Network Model to Estimate the Viscosity of Polymer Solutions for Enhanced Oil Recovery. Appl. Sci. 2016, 6, 188.

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