Artificial Neural Network Model to Estimate the Viscosity of Polymer Solutions for Enhanced Oil Recovery

Kang, Pan-Sang; Lim, Jong‐Se; Huh, Chun

doi:10.3390/app6070188

Cited by 25 publications

(15 citation statements)

References 43 publications

(50 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Soft computation technique such as Artificial Neural Network (ANN) and neuro-fuzzy, as a combination of artificial neural networks and fuzzy logic, also have been successfully used to model polymer solution viscosity [39,40]. The main problem for this type of modelling is its black box nature, which makes it difficult (if not impossible) to incorporate them into the polymer flooding simulator.…”

Section: Suitable Viscosity Model For Polymer Flooding Simulationmentioning

confidence: 99%

A New Empirical Model for Viscosity of Sulfonated Polyacrylamide Polymers

et al. 2019

View full text Add to dashboard Cite

Copolymers of acrylamide with the sodium salt of 2-acrylamido-2-methylpropane sulfonic acid—known as sulfonated polyacrylamide polymers—had been shown to produce very promising results in the enhancement of oil recovery, particularly in polymer flooding. The aim of this work is to develop an empirical model through the use of a design of experiments (DOE) approach for bulk viscosity of these copolymers as a function of polymer characteristics (i.e., sulfonation degree and molecular weight), oil reservoir conditions (i.e., temperature, formation brine salinity and hardness) and field operational variables (i.e., polymer concentration, shear rate and aging time). The data required for the non-linear regression analysis were generated from 120 planned experimental runs, which had used the Box-Behnken construct from the typical Response Surface Methodology (RSM) design. The data were collected during rheological experiments and the model that was constructed had been proven to be acceptable with the Adjusted R-Squared value of 0.9624. Apart from showing the polymer concentration as being the most important factor in the determination of polymer solution viscosity, the evaluation of the model terms as well as the Sobol sensitivity analysis had also shown a considerable interaction between the process parameters. As such, the proposed viscosity model can be suitably applied to the optimization of the polymer solution properties for the polymer flooding process and the prediction of the rheological data required for polymer flood simulators.

show abstract

Section: Suitable Viscosity Model For Polymer Flooding Simulationmentioning

confidence: 99%

A New Empirical Model for Viscosity of Sulfonated Polyacrylamide Polymers

et al. 2019

View full text Add to dashboard Cite

show abstract

“…In addition to the promising applications of artificial intelligence and genetic programming in estimating important parameters for reservoir engineering and process improvement, these methods can also be applied to estimate and optimize polymer flooding processes in enhanced oil recovery, through estimating values of viscosity of polymeric solutions and the prediction of the performance of these injection fluids in reservoirs. In this context, several authors have developed researches focused on this area (Rezaian et al, 2010;Kang et al, 2016;Amirian et al, 2018;Corredor-Rojas et al, 2018;Rostami et al, 2018b). Rezaian et al (2010) applied the artificial neural network model to estimate the minimum amount of Polyvinyl Acetate (PVA) needed to increase water viscosity and simultaneously promote a decrease in oil viscosity, and thus improve the polymer flooding process.…”

Section: Artificial Intelligence Applicationmentioning

confidence: 99%

Polymer viscosifier systems with potential application for enhanced oil recovery: a review

Aguiar

Palermo

Mansur

2021

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

View full text Add to dashboard Cite

Due to the growing demand for oil and the large number of mature oil fields, Enhanced Oil Recovery (EOR) techniques are increasingly used to increase the oil recovery factor. Among the chemical methods, the use of polymers stands out to increase the viscosity of the injection fluid and harmonize the advance of this fluid in the reservoir to provide greater sweep efficiency. Synthetic polymers based on acrylamide are widely used for EOR, with Partially Hydrolyzed Polyacrylamide (PHPA) being used the most. However, this polymer has low stability under harsh reservoir conditions (High Temperature and Salinity – HTHS). In order to improve the sweep efficiency of polymeric fluids under these conditions, Hydrophobically Modified Associative Polymers (HMAPs) and Thermo-Viscosifying Polymers (TVPs) are being developed. HMAPs contain small amounts of hydrophobic groups in their water-soluble polymeric chains, and above the Critical Association Concentration (CAC), form hydrophobic microdomains that increase the viscosity of the polymer solution. TVPs contain blocks or thermosensitive grafts that self-assemble and form microdomains, substantially increasing the solution’s viscosity. The performance of these systems is strongly influenced by the chemical group inserted in their structures, polymer concentration, salinity and temperature, among other factors. Furthermore, the application of nanoparticles is being investigated to improve the performance of injection polymers applied in EOR. In general, these systems have excellent thermal stability and salinity tolerance along with high viscosity, and therefore increase the oil recovery factor. Thus, these systems can be considered promising agents for enhanced oil recovery applications under harsh conditions, such as high salinity and temperature. Moreover, stands out the use of genetic programming and artificial intelligence to estimate important parameters for reservoir engineering, process improvement, and optimize polymer flooding in enhanced oil recovery.

show abstract

“…A low IFT system is better able to strip crude oil from rock surfaces by improving the fluidity of the crude oil [12,13]. Therefore, reducing the IFT of the displacement phase is an effective method to improve the flooding effect [14]. In addition, stability is an important indicator of the foam's performance [15,16]; an ideal foam system maintains high stability while adjustments are made to its IFT.…”

Section: Introductionmentioning

confidence: 99%

Ultra-Low Interfacial Tension Foam System for Enhanced Oil Recovery

Liu

Luo

et al. 2019

Applied Sciences

View full text Add to dashboard Cite

The liquid phase of foam systems plays a major role in improving the fluidity of oil, by reducing oil viscosity and stripping oil from rock surfaces during foam-flooding processes. Improving the oil displacement capacity of the foam’s liquid phase could lead to significant improvement in foam-flooding effects. Oil-liquid interfacial tension (IFT) is an important indicator of the oil displacement capacity of a liquid. In this study, several surfactants were used as foaming agents, and polymers were used as foam stabilizers. Foaming was induced using a Waring blender stirring method. Foam with an oil-liquid IFT of less than 10–3 mN/m was prepared after a series of adjustments to the liquid composition. This study verified the possibility of a foam system with both an ultra-low oil-liquid IFT and high foaming properties. Our results provide insight into a means of optimizing foam fluids for enhanced oil recovery.

show abstract

Artificial Neural Network Model to Estimate the Viscosity of Polymer Solutions for Enhanced Oil Recovery

Cited by 25 publications

References 43 publications

A New Empirical Model for Viscosity of Sulfonated Polyacrylamide Polymers

A New Empirical Model for Viscosity of Sulfonated Polyacrylamide Polymers

Polymer viscosifier systems with potential application for enhanced oil recovery: a review

Ultra-Low Interfacial Tension Foam System for Enhanced Oil Recovery

Contact Info

Product

Resources

About