USE CASE: WELL COLLAPSE RISK
Using Machine Learning to Predict Well Collapse Risk
According to Digital Refining, over the last few years, approximately 92% of refinery shutdowns were due to unplanned maintenance, costing the oil and gas companies an average of and up to $88 million a year in the worst-case scenarios.
With such staggering numbers, it鈥檚 no wonder why reducing unplanned downtime in the Oil & Gas industry is an immediate priority for operators across the ecosystem, particularly when it comes to unplanned maintenance.
With over 50% of the world鈥檚 oil and gas production coming from assets beyond the midpoint of their asset lifecycle, Oil & Gas companies are turning to new advancements in technology鈥攏amely AI鈥攖o significantly reduce downtime and associated unplanned shutdown costs as their assets age.
Learn how one of the world's largest energy companies seeks to optimize asset utilization, lower energy costs, and improve resiliency with the 不良研究所 AI Platform.
