Ionic liquids as novel surfactants for potential use in enhanced oil recovery

“…A new anionic surfactant, named Ammoeng, has been used in chemical flooding, and it has been declared that it would decrease IFT between oil and surfactant solution. Furthermore, a combination solution of two surfactant is introduced, which have a great impact on IFT; finally, it has been suggested that using these surfactant solutions would be proper for enhancing the oil recovery [9]. Another liquid-base anionic surfactant was also introduced by researchers, which could tolerate in presence of high saline liquids.…”

Section: Introductionmentioning

confidence: 99%

Investigating Effect of SiO2 Nanoparticle and Sodium-Dodecyl-Sulfate Surfactant on Surface Properties: Wettability Alteration and IFT Reduction

S¹,

Kazemzadeh²,

Qahramanpour³

et al. 2017

J Pet Environ Biotechnol

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“…Chemical oil recovery is applied to reservoirs as a tertiary method when waterflooding has reached its recovery efficiency limit, which is estimated to be approximately 30-50% of the original oil in place (OOIP) [3,4]. It is an effective method to recover the residual oil trapped by capillary forces after waterflooding.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Polymer Flooding Performance with an Artificial Neural Network: A Two-Polymer-Slug Case

Ebaga-Ololo

Chon

2017

Energies

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Many previous contributions to methods of forecasting the performance of polymer flooding using artificial neural networks (ANNs) have been made by numerous researchers previously. In most of those forecasting cases, only a single polymer slug was employed to meet the objective of the study. The intent of this manuscript is to propose an efficient recovery factor prediction tool at different injection stages of two polymer slugs during polymer flooding using an ANN. In this regard, a back-propagation algorithm was coupled with six input parameters to predict three output parameters via a hidden layer composed of 10 neurons. Evaluation of the ANN model performance was made with multiple linear regression. With an acceptable correlation coefficient, the proposed ANN tool was able to predict the recovery factor with errors of <1%. In addition, to understand the influence of each parameter on the output parameters, a sensitivity analysis was applied to the input parameters. The results showed less impact from the second polymer concentration, owing to changes in permeability after the injection of the first polymer slug.

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Ionic liquids as novel surfactants for potential use in enhanced oil recovery

Cited by 87 publications

References 69 publications

Ionic Liquids as Surfactants – Applications as Demulsifiers of Petroleum Emulsions

Ionic Liquids as Surfactants – Applications as Demulsifiers of Petroleum Emulsions

Investigating Effect of SiO2 Nanoparticle and Sodium-Dodecyl-Sulfate Surfactant on Surface Properties: Wettability Alteration and IFT Reduction

Prediction of Polymer Flooding Performance with an Artificial Neural Network: A Two-Polymer-Slug Case

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