Physical based kr3 relations

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To predict recovery and to design and optimize gas based EOR processes, accurate estimate of constitutive relations, such as relative permeability, are needed as input to the reservoir simulation model. In this project we suggest to use predictive pore-sc ale modeling, combined with X-ray microtomography (mCT) imaging and an improved model for wettability alteration at the pore level, to compute three-phase relative permeabilities for different rock types, wetting conditions, and displacement sequences. Th is offers an exciting alternative to empirical models and time consuming laboratory experiments to obtain three-phase relative permeabilities. Direct measurements of the microstructure of reservoir rocks are obtained via mCT imaging. The mCT data are pro cessed and segmented to obtain an accurate digital representation of the pore structure. Using novel image processing techniques, the imaged pore space is next transformed into a topological and geometrical equivalent pore network where pore bodies and po re throats locations as well as pore shapes are defined accurately. Mineral composition and pore shape information, especially the pore wall curvature, will be used to develop an improved pore level model for wettability alteration by explicitly accountin g for the stability thin brine films coating the pore walls. The extracted pore network is directly incorporated into a network model simulator that has implemented the fundamental physics of three-phase flow. We will validate our predicted results agains t a combination of three-phase micromodel experiments and measurements of three-phase relative permeabilities in different reservoir rocks.