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

SOWUNMI, AKINLEYE OLAMILEKAN and Orodu, O. D. and Efeovbokhan, Vincent Enon and Ogundare, Solomon (2020) Comparative dataset on the characterization of natural polymers and nanocomposites for enhanced oil recovery. Data in Brief. ISSN 2352-3409

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Abstract

Polymer flooding is one of the most effective processes to improve crude oil recovery. However, the capacity of nat- ural polymers to displace crude oil is determined by their rheological behaviour in the face of prevailing reservoir con- ditions. Poor rheological stability of water-soluble polymers challenges their application in harsh reservoir conditions, making it important to investigate the characteristics of poly- mers and their corresponding nanocomposites for use in en- hanced 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 tem- perature, salinity, nanoparticle weight percentage and poly- mer weight percentage. SEM was used to characterize the nanoparticles while FTIR and TGA were used to character- ize 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 pre- sented 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.

Item Type: Article
Uncontrolled Keywords: Polymer Viscosity Nanoparticles Nanocomposites Enhanced oil recovery Rheology
Subjects: T Technology > T Technology (General)
T Technology > TP Chemical technology
Divisions: Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User: nwokealisi
Date Deposited: 28 Oct 2022 11:19
Last Modified: 28 Oct 2022 11:19
URI: http://eprints.covenantuniversity.edu.ng/id/eprint/16392

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