A proposed capillary number dependent model for prediction of relative permeability in gas condensate reservoirs: a robust non-linear regression analysis

Abstract

Well deliverability reduction as a result of liquid (condensate) build up in near well regions is an important deal in the development of gas condensate reservoirs. The relative permeability is an imperative factor for characterization of the aforementioned problem. The dependence of relative permeability on the coupled effects of Interfacial Tension (IFT) and flow velocity (capillary number) together with phase saturation is well established in the literature. In gas condensate reservoirs, however, the influence of IFT and velocity on this parameter becomes more evident. The current paper aims to establish a new model for predicting the relative permeability of gas condensate reservoirs by employing the direct interpolation technique. To this end, the regression analysis was carried out using seven sets of literature published experimental data. The validity analysis was executed by utilizing statistical parameters integrated with graphical descriptions. Furthermore, a comparison was carried out between the proposed model and some literature published empirical models. The results of the examination demonstrated that the new model outperformed other correlations from the standpoints of accuracy and reliability.

Experimental and modeling studies of density and viscosity behavior of a live fluid due to CO2injection at reservoir condition

“…For instance, for reservoir simulation, it is essential to predict the viscosity of each phase as a function of temperature and pressure to model the fluid flow [1][2][3][4][5][6][7]. Oil recovery is predominantly influenced by the capillary number, which characterizes the ratio of viscous forces to surface or interfacial tension forces [8,9]. Carbon dioxide (CO 2 ) miscible flooding is among the most effective nonthermal EOR methods.…”