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  DOI Prefix   10.20431


 

International Journal of Petroleum and Petrochemical Engineering
Volume 5, Issue 2, 2019, Page No: 20-41
DOI: http://dx.doi.org/10.20431/2454-7980.0502003


Multi-Objective Function Approach of Optimizing AlkalineSurfactant Polymer Flooding Performance using Particle Swamp Algorithm

Ejeh Chukwugozie Jekwu*, Idoniboye-Obu Boma, Ebong Hanson, Akhabue Gbemisola

Oil and Gas Engineering Department, School of Engineering All Nations University College, Koforidua, Ghana.

Citation :Ejeh Chukwugozie Jekwu, Multi-Objective Function Approach of Optimizing AlkalineSurfactant Polymer Flooding Performance using Particle Swamp Algorithm International Journal of Petroleum and Petrochemical Engineering 2019, 5(2) : 20-41.

Abstract

The combination of alkaline, surfactant and polymer as a chemical enhanced oil recovery known as ASP flooding has been proved by both laboratory experiments and field applications to be the most promising chemical enhanced oil recovery method. Its promising nature is due to the various synergies that exist between the injected chemicals which reduce both interfacial tension and mobility ratio (that is ensuring stable displacement) to increase recovery. It is also known to be cost effective due to economic surfactant generated by the injection of alkaline and the reduction of adsorptions of both the artificial surfactant and polymer also caused by the presence of the alkaline thereby reducing the total amount of chemical injected. Nevertheless, ASP flooding is not without limitations. Its limitations include scale formation caused by the alkaline injected which gives various operational problems. Also, it has economic limitation mainly based on the cost of high volumes of chemicals injected. The technical and economic feasibility of implementation of ASP flooding therefore depends on the effective use of the chemicals injected and a slug formulation which mitigates scale formation. This study is on optimization of ASP flooding as a multi-objective problem using particle swarm optimization based on Pareto dominance. The objectives of this optimization process is to obtain a set of optimum ASP flooding designs (known as non-dominated set or Pareto set) that maximize recovery efficiency (FOE) and minimize total chemical utilized and the final pH of the system. Analysis on the results of the optimization process revealed the optimum recovery efficiency 44.19% achievable by efficient use of the chemical injected and designs that mitigate scale formation by reducing the concentration of alkaline in the ASP slug formulation. Economic analysis on the Pareto set also confirmed the inference from the results of the optimization process and showed that with favourable oil price situation, recovering higher incremental oil by ASP flooding will be economically viable.


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