Patent ID: 11914680
Assignee: THE HARTFORD STEAM BOILER INSPECTION AND INSURANCE COMPANY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. The method of claim 6, further comprising:
selecting, by the at least one processor, at least one extreme well drilling condition machine learning model based at least in part on the well drilling performance model request;
determining, by the at least one processor, a set of extreme well drilling condition model parameters for the at least one extreme well drilling condition machine learning model comprising:
(7) applying, by the at least one processor, the at least one extreme well drilling condition machine learning model having a set of initial model parameters to the well drilling training data set to determine a set of extreme well drilling condition model predicted values; and
(8) generating, by the at least one processor, an extreme well drilling condition error set of extreme well drilling condition data element errors by comparing the set of extreme well drilling condition model predicted values to corresponding actual values of the well drilling training data set;
(9) repeating, by the at least one processor, steps (7)-(8) as a part of the at least one iteration until the termination criterion is satisfied for the at least one well drilling performance machine learning model; and

transmitting, by the at least one processor, the extreme well drilling condition machine learning model to the at least one computing device for use in at least one production environment to predict a likelihood of extreme well drilling condition.