LARGE-SIGNAL MODELING OF GAN HEMTS USING HYBRID GA-ANN, PSO-SVR, AND GPR-BASED APPROACHES

Abstract

The capacitance-resistance model (CRM) has been widely implemented to model and optimise waterflooding and enhanced oil recovery (EOR) techniques. However, there is a gap in the application of CRM to analyse physical phenomena in porous media as well as the performance of EOR methods, such as low-salinity water (LSW) flooding. The main purposes of this study were to investigate how changes in time constant, as a CRM parameter, can represent physical phenomena in porous media such as wettability alteration. Moreover, to show CRM is a reliable tool to use for interpretation of LSWprocess as an EOR method. The results of different experimental/modelling studies in this research showed that in CRM model time constant increases when the wettability alters to a water wetness state, whereby the smallest time constant value is observed for the oil wet medium and the highest is observed for the water wet medium. The cases with a gradual alteration in wettability show an increasing trend with the dilution of the injection water. The core flooding data confirms the observed results of the simulation approach. The increment in time constant values indicates the resistance against displacing fluid, which is due to the wettability alteration of the porous medium, resulting in additional oil production. The observations made during this research illustrate that the time constant parameter can be a powerful tool for comparing different EOR techniques, since it is a good indication of the speed of impact of a particular injection fluid on production.