Viscosity study of salt tolerant polymers

Rashidi, Masoud; Blokhus, Anne Marit; Skauge, Arne

doi:10.1002/app.32011

Cited by 87 publications

(99 citation statements)

References 36 publications

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“…These findings were consistent with those of other studies (AitKadi et al 1987;Chagas et al 2004;Rashidi et al 2010). The addition of NaCl to the polymer solution shielded the charges on the polymer chain.…”

Section: Effect Of the Nacl Concentration And Shear Rate On The Polymsupporting

confidence: 94%

“…For all polymers, a higher polymer concentration gives a solution with a higher viscosity. This is because the polymer concentration changes the interaction among the polymer molecules (Rashidi et al 2010;Sorbie 1991).…”

Section: Resultsmentioning

confidence: 99%

“…The addition of NaCl to the polymer solution shielded the charges on the polymer chain. The molecules then coiled up and resulted in a lower polymer solution viscosity (Ait-Kadi et al 1987;Chagas et al 2004;Rashidi et al 2010). The rate of the decrease in the viscosity began to level off after a particular salinity as all charges on the polymer chain had been screened by the NaCl ions.…”

Section: Effect Of the Nacl Concentration And Shear Rate On The Polymmentioning

confidence: 99%

See 2 more Smart Citations

Experimental investigation of the effect of different process variables on the viscosity of sulfonated polyacrylamide copolymers

Akbari

Mahmood

Tan

et al. 2016

J Petrol Explor Prod Technol

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Increasing the viscosity of injected water by the addition of polymer improves the displacement efficiency during the water flooding process. In this study, a sulfonated polyacrylamide copolymer has been added to salt water. Several parameters, such as polymer concentration, shear rate, NaCl concentration, molecular weight and sulfonation degree, have a significant effect on the polymer solution viscosity. The main objective of this paper is to investigate how the polymer solution viscosity varies with changes in the input parameters so as to identify the relative importance of these parameters. This paper incorporates the Design of Experiments technique using Taguchi's method and the Analysis of Variance (ANOVA) to investigate the effect of process variables on the viscosity of a polymer solution. Five input parameters and six possible interactions have been investigated. The analysis of the experimental results revealed that two input parameters, namely, polymer concentration and shear rate, have the most significant impact on polymer viscosity. Two strong interactions were observed in the (1) NaCl concentration and sulfonation degree and (2) molecular weight and NaCl concentration studies. The results show that the Taguchi method was successful in identifying the main effects and interaction effects. ANOVA further buttresses the results from Taguchi's method by showing a strong similarity in its results.

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Section: Effect Of the Nacl Concentration And Shear Rate On The Polymsupporting

confidence: 94%

Section: Resultsmentioning

confidence: 99%

Section: Effect Of the Nacl Concentration And Shear Rate On The Polymmentioning

confidence: 99%

See 1 more Smart Citation

Experimental investigation of the effect of different process variables on the viscosity of sulfonated polyacrylamide copolymers

Akbari

Mahmood

Tan

et al. 2016

J Petrol Explor Prod Technol

View full text Add to dashboard Cite

show abstract

“…Polymers act as viscosifying agents, where the inherent viscoelasticity of the polymer flood generates localized non-Newtonian shear stress that pulls oil threads [8,9]. A modification of the relative difference in phase viscosities, known as mobility, is known to enhance oil displacement [10,11]. A combination of chemical methods has been proposed as an effective method for enhancing oil recovery [12].…”

Section: Introductionmentioning

confidence: 99%

Waterflooding of Surfactant and Polymer Solutions in a Porous Media Micromodel

Yeh

Juárez

2018

Colloids and Interfaces

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Abstract:In this study, we examine microscale waterflooding in a randomly close-packed porous medium. Three different porosities were prepared in a microfluidic platform and saturated with silicone oil. Optical video fluorescence microscopy was used to track the water front as it flowed through the porous packed bed. The degree of water saturation was compared to water containing two different types of chemical modifiers, sodium dodecyl sulfate (SDS) and polyvinylpyrrolidone (PVP), with water in the absence of a surfactant used as a control. Image analysis of our video data yielded saturation curves and calculated fractal dimension, which we used to identify how morphology changed the way in which an invading water phase moved through the porous media. An inverse analysis based on the implicit pressure explicit saturation (IMPES) simulation technique used mobility ratio as an adjustable parameter to fit our experimental saturation curves. The results from our inverse analysis combined with our image analysis show that this platform can be used to evaluate the effectiveness of surfactants or polymers as additives for enhancing the transport of water through an oil-saturated porous medium.

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“…Overall, a higher solution viscosity will be attained by providing a higher polymer concentration for almost all polymers. This is due to the fact that interaction among the polymer molecules will be increased by adding more polymer into the solution (Rashidi et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Comparison of neuro-fuzzy network and response surface methodology pertaining to the viscosity of polymer solutions

Akbari

Mahmood

Tan

et al. 2017

J Petrol Explor Prod Technol

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This study has utilized the response surface methodology (RSM) and adaptive neuro-fuzzy inference system (ANFIS) approaches for the modeling of polymer solution viscosity. In the absence of reports in the previous study on applying these two approaches, the main objective of this study has been to compare the performance of these methods toward the viscosity modeling of a polymer solution. By utilizing RSM technique, the effects of three independent parameters including shear rate, polymer concentration, and sodium chloride concentration on viscosity of polymer solution were examined. The RSM results showed that all the parameters were not equally important in the polymer solution viscosity. Moreover, analysis of variance (ANOVA) was also carried out and indicated that there was no evidence of lack of fit in the RSM model. As a second approach for polymer solution viscosity modeling, ANFIS was utilized with two rules constructed based on the first-order Sugeno fuzzy approach and trained by back propagation neural networks algorithm. High coefficient of determination (R 2 ) values ( [99%) showed that the prediction ability of both the ANFIS and RSM models was good enough for the response when the interpolation ability of the models was considered. In order to evaluate the extrapolation abilities of the two developed models, two data sets lying beyond the originally considered data were also taken into account. The results showed that their extrapolation predictive ability was poor. The reason could simply be the inherent behavior of the polymeric solution, i.e., the correlational structure seen in the sample used in the training step did not continue outside the sample space.

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Viscosity study of salt tolerant polymers

Cited by 87 publications

References 36 publications

Experimental investigation of the effect of different process variables on the viscosity of sulfonated polyacrylamide copolymers

Experimental investigation of the effect of different process variables on the viscosity of sulfonated polyacrylamide copolymers

Waterflooding of Surfactant and Polymer Solutions in a Porous Media Micromodel

Comparison of neuro-fuzzy network and response surface methodology pertaining to the viscosity of polymer solutions

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