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Parameter calibration of the stochastic bubble population balance model for predicting NP-stabilized foam flow characteristics in porous media

Release time:2023-10-19 Hits:

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Abstract:Stochastic Bubble Population (SBP) balance model has been widely applied on investigation of surfactant foam flow characteristics in porous media, while its application on predict nanoparticle (NP)-stabilized foam behavior has not been well refined. There are two empirical parameters in the SBP model, namely, the bubble generation rate K-g and the maximum bubble density n(max). To qualify the SBP model on prediction of the transient NPstabilized foam propagation behavior, we make the efforts to calibrate the parameters of K-g and n(max) based on the literature reported systematic experimental results. Through five sets of simulations in correspondence to the experimental works, it is found K-g has little effect on the pressure drop along the core, while the n(max) increases from 200 mm(-3) to 8000 mm(-3) with the addition of NPs and the increment of NP concentration. Larger nmax values at higher NP concentrations indicates the foam stabilized by NPs has stronger foam structure and therefore leads to a better displacement result. It is concluded that based on the simple but carefully calibrated parameters, SBP model could provide accurate predictions of NP-stabilized foam flow characteristic in porous media.
Volume:614
Issue:126180
Translation or Not:no