Estimation of minimum miscibility pressure (MMP) in enhanced oil recovery (EOR) process by N2 flooding using different computational schemes

Abstract

Nitrogen is an effective agent to be considered in gas injection processes as a part of enhanced oil recovery (EOR) process. Successful design and implementation of nitrogen flooding scenarios greatly depend on accurate prediction of minimum miscibility pressure (MMP). This work highlights the application of three models namely GA-RBF, PSO-ANFIS and MLP for estimation of pure and impure MMP value in nitrogen-crude oil systems based on reliable and valid experimental data covering a wide range of operational parameters gathered from literature. Various statistical and graphical methods were utilized to evaluate the performance of the developed models. The results of the developed models are also compared with reported literature methods for estimation of nitrogen MMP. Results show that the proposed GA-RBF, CHPSO-ANFIS and MLP models are accurate for estimation of experimental data with overall average absolute relative errors of 1.9%, 2.92% and 3.59% and overall R2 values of 0.9847, 0.9686 and 0.9485, respectively. Moreover, the proposed models successfully outperform other literature methods and present more accurate and reliable results.