Multi-Objective Optimization of Microemulsion Flooding for Chemical Enhanced Oil Recovery

Abstract

Microemulsion flooding is one of the most effective methods of Chemical Enhanced Oil Recovery (CEOR), particularly for the production of residual oil trapped in unconventional reservoirs. A critical step for successful application of this technique is to achieve a suitable formulation. Previous studies have almost focused on the technical aspects while considering both practical and economic matters as conflicting objectives has been neglected. In the present paper, the formulation of microemulsion is optimized based on the trade-off between scientific and financial responses using a hybrid workflow in which experimental design and artificial intelligence methodologies are composed. To appraise the efficiency of developed algorithm, a challenge case study is first evaluated and compared to previous approaches. Thereafter, the second case is examined in which a newly developed formulation of microemulsion for high temperature carbonate reservoirs is optimized. The outcomes of this multi-attribute workflow are compared to a single-objective algorithm. The results indicate the outstanding performance of the proposed approach for multi-objective optimization of microemulsion formulation. Eventually, the possible concerns regarding the application of microemulsion flooding in unconventional reservoirs are discussed.