Automated lithology instance segmentation model evaluation and update

Abstract

Aspects provide a method of automated lithology at a wellbore. The method includes imaging cuttings collected while drilling the wellbore. The method includes one or more processors: obtaining, from an instance segmentation machine learning model, one or more lithology predictions associated with the wellbore based on the images; determining one or more performance metric scores for the instance segmentation machine learning model based on the one or more lithology predictions and reference data; and comparing the one or more performance metrics scores to one or more performance metric score thresholds and/or one or more performance metrics scores of a second model. The method includes based on the comparison: labeling the images; and (i) retraining the model using the labeled images; or (ii) replacing the model with the second model. The method includes obtaining, from the retrained or second instance segmentation machine learning model, one or more second lithology predictions.