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Hybrid connectionist model determines CO(2)–oil swelling factor
In-depth understanding of interactions between crude oil and CO(2) provides insight into the CO(2)-based enhanced oil recovery (EOR) process design and simulation. When CO(2) contacts crude oil, the dissolution process takes place. This phenomenon results in the oil swelling, which depends on the te...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
China University of Petroleum (Beijing)
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417373/ https://www.ncbi.nlm.nih.gov/pubmed/30956651 http://dx.doi.org/10.1007/s12182-018-0230-5 |
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author | Ahmadi, Mohammad Ali Zendehboudi, Sohrab James, Lesley A. |
author_facet | Ahmadi, Mohammad Ali Zendehboudi, Sohrab James, Lesley A. |
author_sort | Ahmadi, Mohammad Ali |
collection | PubMed |
description | In-depth understanding of interactions between crude oil and CO(2) provides insight into the CO(2)-based enhanced oil recovery (EOR) process design and simulation. When CO(2) 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(2)-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(2)–oil swelling factor. A genetic algorithm is used to optimize hyperparameters (γ and σ(2)) of the LS-SVM model. This model showed a high coefficient of determination (R(2) = 0.9953) and a low value for the mean-squared error (MSE = 0.0003) based on the available experimental data while estimating the CO(2)–oil swelling factor. It was found that LS-SVM is a straightforward and accurate method to determine the CO(2)–oil swelling factor with negligible uncertainty. This method can be incorporated in commercial reservoir simulators to include the effect of the CO(2)–oil swelling factor when adequate experimental data are not available. |
format | Online Article Text |
id | pubmed-6417373 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | China University of Petroleum (Beijing) |
record_format | MEDLINE/PubMed |
spelling | pubmed-64173732019-04-03 Hybrid connectionist model determines CO(2)–oil swelling factor Ahmadi, Mohammad Ali Zendehboudi, Sohrab James, Lesley A. Pet Sci Original Paper In-depth understanding of interactions between crude oil and CO(2) provides insight into the CO(2)-based enhanced oil recovery (EOR) process design and simulation. When CO(2) 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(2)-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(2)–oil swelling factor. A genetic algorithm is used to optimize hyperparameters (γ and σ(2)) of the LS-SVM model. This model showed a high coefficient of determination (R(2) = 0.9953) and a low value for the mean-squared error (MSE = 0.0003) based on the available experimental data while estimating the CO(2)–oil swelling factor. It was found that LS-SVM is a straightforward and accurate method to determine the CO(2)–oil swelling factor with negligible uncertainty. This method can be incorporated in commercial reservoir simulators to include the effect of the CO(2)–oil swelling factor when adequate experimental data are not available. China University of Petroleum (Beijing) 2018-04-26 2018 /pmc/articles/PMC6417373/ /pubmed/30956651 http://dx.doi.org/10.1007/s12182-018-0230-5 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Paper Ahmadi, Mohammad Ali Zendehboudi, Sohrab James, Lesley A. Hybrid connectionist model determines CO(2)–oil swelling factor |
title | Hybrid connectionist model determines CO(2)–oil swelling factor |
title_full | Hybrid connectionist model determines CO(2)–oil swelling factor |
title_fullStr | Hybrid connectionist model determines CO(2)–oil swelling factor |
title_full_unstemmed | Hybrid connectionist model determines CO(2)–oil swelling factor |
title_short | Hybrid connectionist model determines CO(2)–oil swelling factor |
title_sort | hybrid connectionist model determines co(2)–oil swelling factor |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417373/ https://www.ncbi.nlm.nih.gov/pubmed/30956651 http://dx.doi.org/10.1007/s12182-018-0230-5 |
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