On the Evaluation of Interfacial Tension (IFT) of CO 2 –Paraffin System for Enhanced Oil Recovery Process: Comparison of Empirical Correlations, Soft Computing Approaches, and Parachor Model

Farzaneh Rezaei, Amin Rezaei, Saeed Jafari, Abdolhossein Hemmati-Sarapardeh, Amir H. Mohammadi and Sohrab Zendehboudi
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Farzaneh Rezaei: Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman 76169-13439, Iran
Amin Rezaei: Department of Petroleum Engineering, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz 71557-13876, Iran
Saeed Jafari: Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman 76169-13439, Iran
Abdolhossein Hemmati-Sarapardeh: Department of Petroleum Engineering, Shahid Bahonar University of Kerman, Kerman 76169-13439, Iran
Amir H. Mohammadi: Discipline of Chemical Engineering, School of Engineering, University of KwaZulu-Natal, Howard College Campus, King George V Avenue, Durban 4041, South Africa
Sohrab Zendehboudi: Faculty of Engineering and Applied Science, Memorial University, St. John’s, NL A1B 3X5, Canada

Energies, 2021, vol. 14, issue 11, 1-25

Abstract: Carbon dioxide-based enhanced oil-recovery (CO 2 -EOR) processes have gained considerable interest among other EOR methods. In this paper, based on the molecular weight of paraffins (n-alkanes), pressure, and temperature, the magnitude of CO 2 –n-alkanes interfacial tension (IFT) was determined by utilizing soft computing and mathematical modeling approaches, namely: (i) radial basis function (RBF) neural network (optimized by genetic algorithm (GA), gravitational search algorithm (GSA), imperialist competitive algorithm (ICA), particle swarm optimization (PSO), and ant colony optimization (ACO)), (ii) multilayer perception (MLP) neural network (optimized by Levenberg-Marquardt (LM)), and (iii) group method of data handling (GMDH). To do so, a broad range of laboratory data consisting of 879 data points collected from the literature was employed to develop the models. The proposed RBF-ICA model, with an average absolute percent relative error (AAPRE) of 4.42%, led to the most reliable predictions. Furthermore, the Parachor approach with different scaling exponents (n) in combination with seven equations of state (EOSs) was applied for IFT predictions of the CO 2 –n-heptane and CO 2 –n-decane systems. It was found that n = 4 was the optimum value to obtain precise IFT estimations; and combinations of the Parachor model with three-parameter Peng–Robinson and Soave–Redlich–Kwong EOSs could better estimate the IFT of the CO 2 –n-alkane systems, compared to other used EOSs.

Keywords: soft computing tools; equations of state; n-alkanes; interfacial tension; enhanced oil recovery; CO 2 flooding (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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