Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles

In this study, the effect of silica nanoparticles (NS) and temperature on the rheological properties with ultimate shear stress and weight loss of the oil well cement (class H) modified with NS were investigated. The NS content was varied up to 1% by the weight of the cement. The total weight loss a...

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Main Author: Ahmed S. Mohammed
Format: Article
Language:English
Published: Elsevier 2018-12-01
Series:Egyptian Journal of Petroleum
Online Access:http://www.sciencedirect.com/science/article/pii/S1110062118300783
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spelling doaj-6e4fd572d8334972b43fa0e35cea6ccd2020-11-24T22:18:13ZengElsevierEgyptian Journal of Petroleum1110-06212018-12-0127412651273Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticlesAhmed S. Mohammed0Department of Engineering, The American University of Iraq, Kurdistan Region, Sulaimani, IraqIn this study, the effect of silica nanoparticles (NS) and temperature on the rheological properties with ultimate shear stress and weight loss of the oil well cement (class H) modified with NS were investigated. The NS content was varied up to 1% by the weight of the cement. The total weight loss at 800 °C for the oil well cement decreased from 6.10% to 1.05%, a 83% reduction when the cement was mixed with 1% of NS. The results also showed that 1% of NS increased the rheological properties of the cement slurry. The NS modification increased the yield stress (τo) and by 5% to 65% based on the NS content and the temperature of the cement slurry. The addition of 0.5% and 1% NanoSiO2 increased the initial electrical resistivity of the cement by 17% and 35% respectively. The shear thinning behavior of the cement slurry with and without NS has been quantified using the Vipulanandan rheological model and compared with the Herschel-Bulkley model. Based on the Vipulanandan rheological model the maximum shear stress produced by the cement slurry modified with 0% and 1% of NS at the temperature of 25 °C were 148 Pa and 179 Pa respectively hence an increase of 21% in the ultimate shear stress due to the addition of NS. The addition of 1% of NS increased the compressive strength of the cement by 14% and 42% after 1 day and 28 days of curing respectively. Effects of NS content and the temperature on the model parameters have been quantified using a nonlinear model (NLM). The NLM quantified the effect of NS treatment on all the model parameters. Keywords: Electrical resistivity, Nanosilica (NS), Temperature, Rheological properties, Shear stress limit, Modelinghttp://www.sciencedirect.com/science/article/pii/S1110062118300783
collection DOAJ
language English
format Article
sources DOAJ
author Ahmed S. Mohammed
spellingShingle Ahmed S. Mohammed
Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
Egyptian Journal of Petroleum
author_facet Ahmed S. Mohammed
author_sort Ahmed S. Mohammed
title Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
title_short Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
title_full Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
title_fullStr Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
title_full_unstemmed Vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
title_sort vipulanandan models to predict the electrical resistivity, rheological properties and compressive stress-strain behavior of oil well cement modified with silica nanoparticles
publisher Elsevier
series Egyptian Journal of Petroleum
issn 1110-0621
publishDate 2018-12-01
description In this study, the effect of silica nanoparticles (NS) and temperature on the rheological properties with ultimate shear stress and weight loss of the oil well cement (class H) modified with NS were investigated. The NS content was varied up to 1% by the weight of the cement. The total weight loss at 800 °C for the oil well cement decreased from 6.10% to 1.05%, a 83% reduction when the cement was mixed with 1% of NS. The results also showed that 1% of NS increased the rheological properties of the cement slurry. The NS modification increased the yield stress (τo) and by 5% to 65% based on the NS content and the temperature of the cement slurry. The addition of 0.5% and 1% NanoSiO2 increased the initial electrical resistivity of the cement by 17% and 35% respectively. The shear thinning behavior of the cement slurry with and without NS has been quantified using the Vipulanandan rheological model and compared with the Herschel-Bulkley model. Based on the Vipulanandan rheological model the maximum shear stress produced by the cement slurry modified with 0% and 1% of NS at the temperature of 25 °C were 148 Pa and 179 Pa respectively hence an increase of 21% in the ultimate shear stress due to the addition of NS. The addition of 1% of NS increased the compressive strength of the cement by 14% and 42% after 1 day and 28 days of curing respectively. Effects of NS content and the temperature on the model parameters have been quantified using a nonlinear model (NLM). The NLM quantified the effect of NS treatment on all the model parameters. Keywords: Electrical resistivity, Nanosilica (NS), Temperature, Rheological properties, Shear stress limit, Modeling
url http://www.sciencedirect.com/science/article/pii/S1110062118300783
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