MACHINE-LEARNING BASED DRILLING MODELS FOR A NEW WELL

摘要

The disclosure relates to a method for performing a drilling operation in a subterranean formation of a field. The method includes obtaining, prior to the drilling operation, a target well data set specifying a target well to be drilled, selecting, from a set of existing wells, a number of analog wells that satisfy a pre-determined similarity criterion with respect to the target well, generating, from a number of analog well data sets of the analog wells, a training data set for the target well, where the training data set includes a rate-of-penetration (ROP) profile for each analog well, generating, using a machine-learning algorithm and based on the training data set, a drilling model that predicts the ROP profile of the target well, and performing, based on the drilling model, modeling of the drilling operation to generate a predicted ROP profile of the target well.