Simulation Study of Salinity Effect on Polymer Flooding in Core Scale

Abstract

In this study, simulation of low salinity polymer flooding in the core scale is investigated using Eclipse-100 simulator. For this purpose, two sets of data are used. The first set of data were adopted from the results of experimental studies conducted at the University of Bergen, performed using Berea sandstone and intermediate oil. The second data set, related to sand pack and heavy oil system, was obtained from experiments performed at Sahand Oil and Gas Research Institute. To obtain relative permeability and capillary pressure curves, automatic history matching is implemented by coupling Eclipse-100 and MATLAB software. Three different correlations are used for relative permeability. The parameters of each model are calculated using four different optimization algorithms, including Levenberg-Marquardt, Trust-region, Fminsearch, and Pattern search. The results showed that regardless of the optimization algorithm being used, applying relative permeability model of Lomeland et al., known as LET model, best matches the experimental oil recovery data in comparison with those of Corey and Skjeaveland et al.’s relative permeability correlations. The LET model and the Trust-region algorithm were selected for simulation of low salinity polymer flooding process. Simulation of the first set of data showed that using low salinity water flooding before polymer flooding, oil recovery was increased about 16%. In addition, using the second set of data, simulation of low salinity polymer flooding scenario is investigated in a long core model, taken from one of the southwestern fields of Iran. Simulation results show an increase of about 34% in the recovery of low salinity polymer flooding compared to the water flooding scenario.

Keywords

• eclipse-100 simulator
• history matching
• low salinity polymer injection
• matlab software
• optimization algorithm
• relative permeability