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Hybrid connectionist model determines CO-oil swelling factor.

作者信息

Ahmadi Mohammad Ali, Zendehboudi Sohrab, James Lesley A

机构信息

Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1C 5S7 Canada.

出版信息

Pet Sci. 2018;15(3):591-604. doi: 10.1007/s12182-018-0230-5. Epub 2018 Apr 26.

Abstract

In-depth understanding of interactions between crude oil and CO provides insight into the CO-based enhanced oil recovery (EOR) process design and simulation. When CO contacts crude oil, the dissolution process takes place. This phenomenon results in the oil swelling, which depends on the temperature, pressure, and composition of the oil. The residual oil saturation in a CO-based EOR process is inversely proportional to the oil swelling factor. Hence, it is important to estimate this influential parameter with high precision. The current study suggests the predictive model based on the least-squares support vector machine (LS-SVM) to calculate the CO-oil swelling factor. A genetic algorithm is used to optimize hyperparameters ( and ) of the LS-SVM model. This model showed a high coefficient of determination (  = 0.9953) and a low value for the mean-squared error (MSE = 0.0003) based on the available experimental data while estimating the CO-oil swelling factor. It was found that LS-SVM is a straightforward and accurate method to determine the CO-oil swelling factor with negligible uncertainty. This method can be incorporated in commercial reservoir simulators to include the effect of the CO-oil swelling factor when adequate experimental data are not available.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f137/6417373/c36293ccb393/12182_2018_230_Fig1_HTML.jpg

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