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Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery

Polymer flooding is one of the most effective processes to improve crude oil recovery. However, the capacity of natural polymers to displace crude oil is determined by their rheological behaviour in the face of prevailing reservoir conditions. Poor rheological stability of water-soluble polymers cha...

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Autores principales: Sowunmi, Akinleye, Orodu, Oyinkepreye, Efeovbokhan, Vincent, Ogundare, Solomon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683321/
https://www.ncbi.nlm.nih.gov/pubmed/33294507
http://dx.doi.org/10.1016/j.dib.2020.106506
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author Sowunmi, Akinleye
Orodu, Oyinkepreye
Efeovbokhan, Vincent
Ogundare, Solomon
author_facet Sowunmi, Akinleye
Orodu, Oyinkepreye
Efeovbokhan, Vincent
Ogundare, Solomon
author_sort Sowunmi, Akinleye
collection PubMed
description Polymer flooding is one of the most effective processes to improve crude oil recovery. However, the capacity of natural polymers to displace crude oil is determined by their rheological behaviour in the face of prevailing reservoir conditions. Poor rheological stability of water-soluble polymers challenges their application in harsh reservoir conditions, making it important to investigate the characteristics of polymers and their corresponding nanocomposites for use in enhanced oil recovery (EOR). The main objective of this work is to conduct characterization tests for three polymers (Gum Arabic, Xanthan Gum and Guar Gum) and three nanoparticles (silica, alumina and cupric), and to investigate the viscosity profile of the polymers under different conditions of temperature, salinity, nanoparticle weight percentage and polymer weight percentage. SEM was used to characterize the nanoparticles while FTIR and TGA were used to characterize the polymers. All viscosity measurements were conducted using an OFITE Viscometer. The SEM, FTIR and TGA results are presented in figures while the viscosity results are presented as raw data in tables. The data should be used to support oil recovery experiments, economic analysis of the use of polymers and nanocomposites in EOR and the study of adsorption and permeability impairment in core flooding tests.
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spelling pubmed-76833212020-12-07 Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery Sowunmi, Akinleye Orodu, Oyinkepreye Efeovbokhan, Vincent Ogundare, Solomon Data Brief Data Article Polymer flooding is one of the most effective processes to improve crude oil recovery. However, the capacity of natural polymers to displace crude oil is determined by their rheological behaviour in the face of prevailing reservoir conditions. Poor rheological stability of water-soluble polymers challenges their application in harsh reservoir conditions, making it important to investigate the characteristics of polymers and their corresponding nanocomposites for use in enhanced oil recovery (EOR). The main objective of this work is to conduct characterization tests for three polymers (Gum Arabic, Xanthan Gum and Guar Gum) and three nanoparticles (silica, alumina and cupric), and to investigate the viscosity profile of the polymers under different conditions of temperature, salinity, nanoparticle weight percentage and polymer weight percentage. SEM was used to characterize the nanoparticles while FTIR and TGA were used to characterize the polymers. All viscosity measurements were conducted using an OFITE Viscometer. The SEM, FTIR and TGA results are presented in figures while the viscosity results are presented as raw data in tables. The data should be used to support oil recovery experiments, economic analysis of the use of polymers and nanocomposites in EOR and the study of adsorption and permeability impairment in core flooding tests. Elsevier 2020-11-06 /pmc/articles/PMC7683321/ /pubmed/33294507 http://dx.doi.org/10.1016/j.dib.2020.106506 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Sowunmi, Akinleye
Orodu, Oyinkepreye
Efeovbokhan, Vincent
Ogundare, Solomon
Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
title Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
title_full Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
title_fullStr Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
title_full_unstemmed Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
title_short Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
title_sort comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7683321/
https://www.ncbi.nlm.nih.gov/pubmed/33294507
http://dx.doi.org/10.1016/j.dib.2020.106506
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