Abstract
In-depth understanding of interactions between crude oil and CO2 provides insight into the CO2-based enhanced oil recovery (EOR) process design and simulation. When CO2 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 CO2-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 CO2–oil swelling factor. A genetic algorithm is used to optimize hyperparameters (γ and σ2) of the LS-SVM model. This model showed a high coefficient of determination (R2 = 0.9953) and a low value for the mean-squared error (MSE = 0.0003) based on the available experimental data while estimating the CO2–oil swelling factor. It was found that LS-SVM is a straightforward and accurate method to determine the CO2–oil swelling factor with negligible uncertainty. This method can be incorporated in commercial reservoir simulators to include the effect of the CO2–oil swelling factor when adequate experimental data are not available.
Highlights
Due to the growing concern about global warming and the ongoing demand for energy resources, CO2-based enhanced oil recovery (EOR) methods have been attracting both the scientific and industrial interests
The current study suggests the predictive model based on the least-squares support vector machine (LS-SVM) to calculate the CO2–oil swelling factor
This study presents a new deterministic approach to obtain the swelling factor with higher accuracy
Summary
Due to the growing concern about global warming and the ongoing demand for energy resources, CO2-based enhanced oil recovery (EOR) methods have been attracting both the scientific and industrial interests. Thomas and Monger-McClure (1991) studied the effect of the CO2–oil swelling factor on oil recovery from light oil reservoirs using cyclic CO2 injection. The CO2-oil swelling factor in their study was defined as ‘‘the volume of the oil after CO2 injection divided by the volume of the oil before CO2 injection into the cell.’’ In their experiments, increasing CO2 concentration from 48.4% to 71.1% resulted in an increase in the CO2–oil swelling factor from 1.21 to 1.39, respectively According to their experimental data, the oil swelling and expansion, CO2 dissolution into the oil, and CO2 diffusion into core samples are the main mechanisms contributing to the oil production (Habibi et al 2017). Through the comprehensive literature review, extensive experimental data are used for model development and validation
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