System for generating bit wear model predictions and related methods

A method for obtaining a bit wear model, the method comprising:

• receiving first drilling data from an earth-boring tool system, the first drilling data including field drilling data, logging while drilling (LWD) data and data indicative of wear of at least part of the at least one drilling tool;
• training at least one predictive bit wear model for predicting one or more dull states of the at least one drilling tool based, at least in part, on the first drilling data, the predictive bit wear model configured to encode the first drilling data into a latent space representation of the first drilling data;
• generating one or more similarity scores responsive to comparing the latent space representation of the first drilling data to target drilling data;
• and
• filtering the first drilling data or the latent space representation of the first drilling data responsive to the one or more similarity scores.

A non-transitory computer-readable medium storing instructions thereon that, when executed by the at least one processor, cause the at least one processor to perform the steps comprising:

• receiving first drilling data including field drilling data, logging while drilling (LWD) data and data indicative of wear of at least part of the at least one drilling tool;
• training at least one predictive bit wear model for predicting one or more dull states of the at least one drilling tool based, at least in part, on the first drilling data, the predictive bit wear model configured to encode the first drilling data into a latent space representation of the first drilling data;
• generating one or more similarity scores responsive to comparing the latent space representation of the first drilling data to target drilling data;
• filtering the first drilling data or the latent space representation of the first drilling data responsive to the one or more similarity scores,
• fitting a wear trajectory regression curve to the filtered latent space representation of the first drilling data;
• and
• generating one or more predicted dull states of the at least one drilling tool based, at least in part, on the predictive bit wear model and the wear trajectory regression curve.