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Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory
Due to the technical, environmental and economic problems caused by asphaltene precipitation, such as oil production reduction, well shut-ins and the necessity of EOR usage, the prediction of asphaltene precipitation seems to be vital. Considering the larger size of asphaltene molecules compared to...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643540/ https://www.ncbi.nlm.nih.gov/pubmed/36347921 http://dx.doi.org/10.1038/s41598-022-23596-w |
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author | Eskini, Farzaneh Dehaghani, Amirhossein Saeedi Shadman, Mohammad Mahdi |
author_facet | Eskini, Farzaneh Dehaghani, Amirhossein Saeedi Shadman, Mohammad Mahdi |
author_sort | Eskini, Farzaneh |
collection | PubMed |
description | Due to the technical, environmental and economic problems caused by asphaltene precipitation, such as oil production reduction, well shut-ins and the necessity of EOR usage, the prediction of asphaltene precipitation seems to be vital. Considering the larger size of asphaltene molecules compared to the other hydrocarbon, it is reasonable to predict the precipitation using the Flory–Huggins theory. In this study, Flory–Huggins solution theory has been modified regarding the solvent molar volume. The modified model was used to predict the asphaltene precipitation of four oil samples in the absence and presence of the inhibitors. Then, the modeling data given by the Flory–Huggins theory was validated with the experimental data obtained by ASTM D-6560 standard method. The mean error at this modeling was 2–13%, which seems acceptable. The proposed model for the cases where an inhibitor is not involved has higher accuracy. The modified Flory–Huggins theory confirmed that the addition of inhibitors at all concentrations postpones the onset point. The average error of the modified model was found to be 4.5–9.8%, which is in a good range. Also, the model accuracy is less for situations where the asphaltene content of the crude oil is higher. Based on this study, the modification of Flory–Huggins theory, regarding the solvent molar volume leads to a lower error. |
format | Online Article Text |
id | pubmed-9643540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96435402022-11-15 Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory Eskini, Farzaneh Dehaghani, Amirhossein Saeedi Shadman, Mohammad Mahdi Sci Rep Article Due to the technical, environmental and economic problems caused by asphaltene precipitation, such as oil production reduction, well shut-ins and the necessity of EOR usage, the prediction of asphaltene precipitation seems to be vital. Considering the larger size of asphaltene molecules compared to the other hydrocarbon, it is reasonable to predict the precipitation using the Flory–Huggins theory. In this study, Flory–Huggins solution theory has been modified regarding the solvent molar volume. The modified model was used to predict the asphaltene precipitation of four oil samples in the absence and presence of the inhibitors. Then, the modeling data given by the Flory–Huggins theory was validated with the experimental data obtained by ASTM D-6560 standard method. The mean error at this modeling was 2–13%, which seems acceptable. The proposed model for the cases where an inhibitor is not involved has higher accuracy. The modified Flory–Huggins theory confirmed that the addition of inhibitors at all concentrations postpones the onset point. The average error of the modified model was found to be 4.5–9.8%, which is in a good range. Also, the model accuracy is less for situations where the asphaltene content of the crude oil is higher. Based on this study, the modification of Flory–Huggins theory, regarding the solvent molar volume leads to a lower error. Nature Publishing Group UK 2022-11-08 /pmc/articles/PMC9643540/ /pubmed/36347921 http://dx.doi.org/10.1038/s41598-022-23596-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Eskini, Farzaneh Dehaghani, Amirhossein Saeedi Shadman, Mohammad Mahdi Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory |
title | Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory |
title_full | Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory |
title_fullStr | Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory |
title_full_unstemmed | Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory |
title_short | Modelling the effect of the inhibitors on asphaltene precipitation using Flory–Huggins theory |
title_sort | modelling the effect of the inhibitors on asphaltene precipitation using flory–huggins theory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9643540/ https://www.ncbi.nlm.nih.gov/pubmed/36347921 http://dx.doi.org/10.1038/s41598-022-23596-w |
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