Multiobjective design and optimization of polymer flood performance

Ekkawong, Peerapong; Han, Jian; Olalotiti-Lawal, Feyi; Datta‐Gupta, Akhil

doi:10.1016/j.petrol.2017.03.026

Cited by 12 publications

(6 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lei et al [148] propose a hybrid GA that uses the position displacement method of particle swarm to solve a mixed integer optimization problem, which seeks to find optimal slug size and polymer concentration. Ekkawong [149] implements a multi-objective GA to optimize oil production and polymer utility function.…”

Section: Optimization Of Chemical Floodingmentioning

confidence: 99%

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

et al. 2017

View full text Add to dashboard Cite

This paper presents a review of history matching and oil field development optimization techniques with a focus on optimization algorithms. History matching algorithms are reviewed as a precursor to production optimization algorithms. Techniques for history matching and production optimization are reviewed including global and local methods. Well placement, well control, and combined well placement-control optimization using both secondary and tertiary oil production techniques are considered. Secondary and tertiary recovery techniques are commonly referred to as waterflooding and enhanced oil recovery (EOR), respectively. Benchmark models for comparison of methods are summarized while other applications of methods are discussed throughout. No single optimization method is found to be universally superior. Key areas of future work are combining optimization methods and integrating multiple optimization processes. Current challenges and future research opportunities for improved model validation and large scale optimization algorithms are also discussed.

show abstract

Section: Optimization Of Chemical Floodingmentioning

confidence: 99%

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

et al. 2017

View full text Add to dashboard Cite

show abstract

“…It is mainly affected by many factors, such as polymer type, concentration, temperature, water mineralization, shear degradation, etc. 37,38 (2) Rheological properties. Polymer solutions will exhibit shear dilution in a certain range of shear rates, and deterioration of the viscoelasticity.…”

Section: Introductionmentioning

confidence: 99%

Simulated evaluation of the degradation of hydrophobically associative polymers in the formation

Qi,

Shu,

Luo

2023

J of Applied Polymer Sci

View full text Add to dashboard Cite

In this work, indoor physical simulation experiments were used to examine the effects of shear, thermal, chemical, and microbial degradation on the properties of the hydrophobic associative polymer AP‐P4. It was discovered that the viscosity of the polymer solution generally decreased as the shear time was extended. The larger the shear strength, the lower the solution viscosity. Fitting of the nonlinear equation of solution viscosity with shear time, η = 12,988 t−1.08. When thermal degradation started, the solution viscosity first started to rise, however, this phase was just a short one. The viscosity of the solution gradually started to decrease as the thermal degradation period grew. In addition, the trends of properties like hydrokinetic radius, hydrophobic connectivity, and hydrolysis essentially followed the same patterns as those of solution viscosity. At the beginning of the degradation process, the viscosity retention of the polymer solution without oxygen is significantly higher than that of the aerobic environment. However, the difference between the two becomes smaller as the degradation time increases. In addition, the AP‐P4 had good temperature resistance and aging resistance capabilities when iron ions were present. Finally, it was discovered that AP‐P4 had a strong antibacterial effect, which decreased the viscosity brought on by microbial action.

show abstract

“…Decision variables related to oil field design such as well selection and operation mode are not considered in that work. Ekkawong et al 15 presented a new multiobjective optimization framework based on genetic algorithms in order to address optimal concentrations, slug sizes, and injection rate allocation for polymer flooding. They showed interesting results in terms of solving the trade-off between cumulative oil production and polymer efficiency.…”

Section: Introductionmentioning

confidence: 99%

“…Although space–time reservoir behavior is captured by simplified correlations and geometric abstractions in this work, our assessment tool can significantly reduce the domain over which decision-makers might develop more in-depth studies, pointing out a reduced number of candidate wells and the reservoir volume to be simulated, as well as tighter bounds on operating variables. Table S1 in the Supporting Information presents a brief comparison among the most relevant optimization models proposed in the literature, ,,,, highlighting the novel features of the current work.…”

Section: Introductionmentioning

confidence: 99%

Optimal Production Strategies for the Development of Mature Oil Fields through Polymer Flooding

Presser

Cafaro

2021

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

Polymer flooding is one of the most extensively applied techniques for enhanced oil recovery (EOR) that relies on increasing the injected fluid viscosity by adding polymers in different concentrations. The aim is to improve the mobility ratio between the oil and the displacing fluid, reducing channeling effects and boosting sweep efficiency. In this work, a mixed-integer nonlinear optimization approach is developed in order to address production planning decisions, also assessing the convenience of polymer flooding in EOR projects on screening stages. This decision-making tool allows establishing optimal polymer injection strategies, setting fluid injection rates and polymer concentrations, selecting wells, and scheduling slug change operations over the planning horizon, with the aim of maximizing the net present value of the project. We propose a novel formulation combining transport phenomenon models, well productivity forecast, and geometric abstraction of the reservoir in order to address both technical and economic decisions with low computational effort. Results show that optimized strategies may outperform typical operations by up to 17% and can be found in shorter central processing unit times in comparison to traditional reservoir simulation approaches. The model has been used to tackle problems with up to 7 wells and can be tuned to different reservoir conditions.

show abstract

Multiobjective design and optimization of polymer flood performance

Cited by 12 publications

References 45 publications

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

Review of Field Development Optimization of Waterflooding, EOR, and Well Placement Focusing on History Matching and Optimization Algorithms

Simulated evaluation of the degradation of hydrophobically associative polymers in the formation

Optimal Production Strategies for the Development of Mature Oil Fields through Polymer Flooding

Contact Info

Product

Resources

About