Runtime parameter selection in simulations
Abstract:
A method for performing a field operation of a field. The method includes obtaining historical parameter values of a runtime parameter and historical core datasets, where the historical parameter values and the historical core datasets are used for a first simulation of the field, and where each historical parameter value results in a simulation convergence during the first simulation, generating a machine learning model based at least on the historical core datasets and the historical parameter values, obtaining, during a second simulation of the field, a current core dataset, generating, using the machine learning model and based on the current core dataset, a predicted parameter value of the runtime parameter for achieving the simulation convergence during the second simulation, and completing, using at least the predicted parameter value, the second simulation to generate a modeling result of the field.
Public/Granted literature
Information query
Patent Agency Ranking
0/0