Sharpen your subsurface understanding
Our Assisted Lithology Interpretation cloud application uses supervised machine learning technology to predict lithology from well data in minutes.
Manually interpreting hundreds of wells is time-consuming and introduces inconsistencies through human bias. Now you can speed up the process and obtain consistent lithological prediction across your enterprise with the help of a supervised machine learning (ML) technique offered by Assisted Lithology Interpretation, a DecisionSpace® 365 cloud application.
Reduce interpreter bias by using trained models for consistent data interpretation across your enterprise.
Connected and informed
Enhance collaboration with immediate shared access to consistent lithology interpretations for thousands of wells and the most current subsurface understanding.
Use a standardized process for consistent data interpretation across the enterprise with trained models to reduce interpreter bias.
Our innovative ML technology predicts lithology from wireline responses using trained models that runs hundreds of interpretations via advanced cloud computing. Taking minutes rather than days, this process allows you to rapidly test different interpretations while also integrating interpretation data into your workflows, providing automated updates and changes.
Process thousands of wells in minutes for effective evaluation operations, improved efficiency, and reduced costs.
Access your data and save back to OpenWorks® seamlessly to easily incorporate Assisted Lithology Interpretation into your workflows.
Perform algorithm-driven interpretation via advanced computing in the cloud, taking minutes rather than days.
Gain a more precise and reliable subsurface understanding for informed decision making and smart investments.
Quantifiable confidence limits
Capture and track uncertainty of lithology predictions throughout the interpretation workflow on a well-by-well basis with numerical measures of confidence down each well section.
Reduce subsurface uncertainty
Rapidly test multiple scenarios on the same data to aid lithology prediction and reduce subsurface uncertainty.
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