ADNOC has deployed an AI-enabled Real-Time Operations Center across its fleet of more than 120 rigs, giving drilling teams a single platform to monitor and manage onshore and offshore operations. Built with SLB's DrillOps technology, the system replaces multiple tools, reduces engineering effort by 30-40%, and lets each engineer support two to three times more rigs.
What the platform does
The RTOC turns drilling data into automated dashboards and AI-driven performance insights. Reporting cycles that once took days now complete in hours. The system also flags potential issues before they escalate, reducing incident response times by 4-12 hours and helping avoid one to two days of rig downtime.
Live rig data flows into a single environment, giving business, asset, and drilling teams a real-time view across the fleet. Tasks that previously required a full day of analysis can now be done in minutes. The platform is deployed across ADNOC Drilling's rig fleet, with ADNOC Onshore and ADNOC Offshore using it to make faster decisions and reduce operational risk.
Built for scale and security
The system is built on SLB's DrillOps intelligent well delivery and insights solutions. It's hosted in ADNOC's sovereign cloud environment in the UAE, keeping critical operational data within the country's jurisdiction. That setup strengthens data security, operational resilience, and digital independence.
Musabbeh Al Kaabi, ADNOC Upstream CEO, said: "The Real-Time Operations Center creates value across ADNOC's drilling operations every minute by embedding AI into the heart of our drilling operations, helping our teams make faster, smarter decisions at scale. Built securely here in the UAE, it is further proof that ADNOC is moving from AI ambition to real-world impact as we become the world's most AI-enabled energy company."
Rakesh Jaggi, President, Digital, at SLB, said: "DrillOps transforms real-time drilling data into operational intelligence that helps teams make faster, more informed decisions. Deployed within ADNOC's sovereign cloud environment, the technology provides the scalable digital foundation for AI-enabled workflows across one of the industry's largest rig fleets and supports the continued progression toward more autonomous operations."
Why this matters for operations professionals
The deployment shows what AI looks like in operational settings: fewer manual checks, faster response to anomalies, and broader oversight per engineer. Operations teams in other industries can apply the same pattern by centralizing data, automating routine analysis, and using AI to surface risks before they become downtime. Training options like AI for Operations and the AI Learning Path for Operations Managers cover these skills for professionals who want to build them.
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