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

Claim 10:
11. A system comprising:
at least one processor configured to:
receive, from at least one computing device, a well drilling performance model request comprising a well drilling training data set of well drilling data records;
wherein each well drilling data record comprises:
at least one independent variable associated with well drilling parameters of at least one drilling run, and
a target variable representing at least one non-productive time performance metric associated with the at least one drilling run, wherein the target variable is indicative of the at least one non-productive time performance metric being below a non-productive time performance threshold; and

determine at least one bias criteria;
select at least one well drilling performance machine learning model based at least in part on the well drilling performance model request;
iteratively refine a set of model parameters of the at least one well drilling performance machine learning model until a termination criterion is met, wherein the iterative refining comprises iteratively repeating steps comprising:
determining a plurality of model predicted values using the set of model parameters of the at least one machine learning based on the at least one independent variable of the well drilling training data set,
determining an outlier data set and a non-outlier data set associated with the well drilling training data set based at least in part on:
an error calculation between each model predicted value relative to each target value of the well drilling training data set, and
the at least one bias criteria;

training the at least one well drilling performance machine learning model using the non-outlier data set to update the set of model parameters;

output a production-ready well drilling performance machine learning model of the at least one well drilling performance machine learning model comprising the set of model parameters.