Schlumberger Technology Corporation

Laura Su

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.

Growing community of inventors

Clamart, France

Laura Su