Predictive Pore-Scale Modelling of Multiphase Flow | The use of geologically realistic networks to predict the flow properties for a variety of porous media. Este artículo no está disponible.Predictive Pore-Scale Modelling of Multiphase Flow | The use of geologically realistic networks to predict the flow properties for a variety of porous media

Flow properties for a variety of porous media can be predicted using pore-scale modelling with geologically realistic networks. A state of the art pore-scale network model is developed for this purpose. It combines topologically disordered networks that represent real systems with detailed displacement mechanisms for any sequence of water and oil flooding, and any wettability. The model is verified by successfully predicting experimental relative permeability from a well described water-wet Berea sandstone. More complex experimental data are subsequently investigated. By developing a methodology combining realistic network topology with network properties tuned to easily obtainable experimental data such as mercury injection capillary pressures, the flow properties for several porous media can successfully be predicted. This is initially applied to a water-wet sand pack. The aim of this work is not simply to match experiments, but to use easily acquired data to predict difficult-to-measure properties. Furthermore, the variation of these properties in the field, due to wettability trends and different pore structures, can now be predicted reliably.

Flow properties for a variety of porous media can be predicted using pore-scale modelling with geologically realistic networks. A state of the art pore-scale network model is developed for this purpose. It combines topologically disordered networks that represent real systems with detailed displacement mechanisms for any sequence of water and oil flooding, and any wettability. The model is verified by successfully predicting experimental relative permeability from a well described water-wet Berea sandstone. More complex experimental data are subsequently investigated. By developing a methodology combining realistic network topology with network properties tuned to easily obtainable experimental data such as mercury injection capillary pressures, the flow properties for several porous media can successfully be predicted. This is initially applied to a water-wet sand pack. The aim of this work is not simply to match experiments, but to use easily acquired data to predict difficult-to-measure properties. Furthermore, the variation of these properties in the field, due to wettability trends and different pore structures, can now be predicted reliably.