Methods and systems for subsurface modeling employing ensemble machine learning prediction trained with data derived from at least one external model

Abstract

Method and systems are provided that create one or more models of a subsurface geological formation (such as a reservoir characterization model of a hydrocarbon reservoir or a model of some other subsurface geological formation). The method and systems are configured to extend a machine learning ensemble (such as an ensemble tree-based machine learning model such as a random forest learning model) to use or embed data derived from one or more secondary models as part of the training operations of the machine learning ensemble and online use of the trained machine learning ensemble. Such data can provide information that supplements the information contained in the training data/input data.

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