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A Skoltech AI Center researcher has developed an approach for identifying more efficient drilling regimes in heterogeneous carbonate reservoirs, TechXplore reports.
Why it mattersThe approach predicts drilling-process characteristics, estimates how individual parameters affect them and identifies efficient operating regimes. For one studied well, the model estimated that the rate of penetration could rise by up to 68.4%. That is a modelled potential, not a reported improvement achieved in the field. Still, it shows how AI tools can be applied to a specific industrial problem: finding better operating conditions for drilling.
Discuss: For industrial AI, should a large modelled gain be enough to justify a field trial, or should operators wait for results from real-world deployment?
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