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      Low salinity water flooding: estimating relative permeability and capillary pressure using coupling of particle swarm optimization and machine learning technique

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          Abstract

          The reservoir’s properties are required for proper reservoir simulation, which also involves uncertainties. Experimental methods to estimate the relative permeability and capillary pressure data are expensive and time-consuming. This study aims to determine the relative permeability and capillary pressure functions of a sandstone core in the presence and absence of clay during low-salinity water floods. The data were provided by automatic history matching the results from previously lab-reported studies through coupling a simulator with the particle swarm optimization algorithm. Correlations were proposed using multiple-linear regression for relative permeability and capillary pressure parameters at low-salinity conditions. They were validated against experimental results of no clay and clayey formation with regression of 95% and 97%. To assign one curve of relative permeability and capillary pressure to the grid cells of the simulator, averaging techniques were implemented. The effect of salinity and clay content on the obtained curves was investigated. Changing salinity from 42000 to 4000 ppm, the reduction in water relative permeability appeared to be higher than the oil relative permeability increment. Moreover, a noticeable shift in the relative permeability curves toward the highest saturations related to the clay content was observed. The proposed hybrid method could be a suitable tool to estimate the relative permeability and capillary pressure functions of the water-based EOR methods.

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          Most cited references33

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          Heavy oil polymer flooding from laboratory core floods to pilot tests and field applications: Half-century studies

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            Enhanced Oil Recovery (EOR) by Combined Low Salinity Water/Polymer Flooding

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              Low salinity polymer flooding: Lower polymer retention and improved injectivity

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                Author and article information

                Contributors
                simjoo@sut.ac.ir
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 June 2024
                8 June 2024
                2024
                : 14
                : 13213
                Affiliations
                Faculty of Petroleum and Natural Gas Engineering, Sahand University of Technology, ( https://ror.org/03wdrmh81) Tabriz, Iran
                Article
                61168
                10.1038/s41598-024-61168-2
                11162489
                38851823
                063cc9b4-4833-44c3-a221-963ec7cd55cf
                © The Author(s) 2024

                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/.

                History
                : 25 January 2024
                : 2 May 2024
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                © Springer Nature Limited 2024

                Uncategorized
                chemical engineering,mechanical engineering
                Uncategorized
                chemical engineering, mechanical engineering

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