METHODS AND SYSTEMS FOR MACHINE-LEARNING BASED SIMULATION OF FLOW

摘要

There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model comprising a plurality of coarse grid cells. The method includes generating a fine grid model corresponding to one of the coarse grid cells and simulating the fine grid model using a training simulation to generate a set of training parameters comprising boundary conditions of the coarse grid cell. A machine learning algorithm may be used to generate, based on the set of training parameters, a coarse scale approximation of a phase permeability of the coarse grid cell. The hydrocarbon reservoir can be simulated using the coarse scale approximation of the effective phase permeability generated for the coarse grid cell. The method also includes generating a data representation of a physical hydrocarbon reservoir in a non-transitory, computer-readable, medium based at least in part on the results of the simulation.