AiPSO integrates real-time data streams from thousands of wells and hundreds of processing facilities with SLB’s Lumi data and AI infrastructure and Cognite Data Fusion. ADNOC’s Upstream chief executive, Musabbeh Al Kaabi, stated the platform will allow engineers to identify and act on production issues in a matter of minutes rather than days, thus freeing staff to focus on higher-value tasks. He described the initiative as a “transformative step” in upstream productivity.
SLB’s chief executive, Olivier Le Peuch, commented that AiPSO exemplifies how artificial intelligence combined with domain-specific expertise can drive long-term value and operational resilience. The platform is part of ADNOC’s broader push to become the most AI-enabled energy company, complementing its existing agentic AI system, ENERGYai, developed with AIQ.
Analysts say the partnership reflects a global trend among oil-and-gas majors to adopt digital-twin, machine-learning and real-time analytics systems in order to reduce downtime, improve production efficiency and lower cost per barrel. Oilfield digitalisation strategist Dr Maria Kovalev of London-based consultancy Energy-Tech Insights noted: “What distinguishes this rollout is the intention to scale across the full upstream asset base, not merely a pilot for one field.”
While the immediate benefit is described in workforce efficiency and faster well-diagnosis, the strategic angle involves capitalising on lower-cost barrels and extending asset life. For ADNOC, which has previously reported that AI initiatives added US $500 million in value in a single year, this is a further extension of its digital-transformation agenda.
The phased deployment envisages eight fields in the first stage, followed by full coverage of all 25 upstream fields by 2027. That means offshore platforms, onshore reservoirs, processing installations and field-control systems will all be integrated under AiPSO’s smart-workflow framework. Engineers across control rooms and field sites will be linked in real-time, using predictive-maintenance algorithms, performance-monitoring dashboards and machine-learning models trained on both sensor data and operational data sets.
Potential operational gains include reduced unplanned shutdowns, faster response to subsurface issues, and increased production from existing wells. Equally, the shift raises questions: data-integration complexity, cybersecurity risks, and the challenge of retraining field personnel for an AI-centric workflow. One industry executive, requesting anonymity, cautioned that “the success of these platforms often sits as much in change-management and culture as in the software itself.”
Another factor is sustainability: by improving efficiency and reducing waste, such platforms may link to lower emissions or less energy intensity per barrel. ADNOC’s corporate strategy emphasises “maximum energy, minimum emissions” and features large-scale AI and automation investments. The rollout of AiPSO aligns with that messaging, though critics say the scale of digital-investment and ROI timelines remain opaque.
Some observers highlight that the commercial oil-and-gas environment is evolving: with production growth under pressure and regulatory attention on carbon footprints increasing, improvements in digital productivity may become a distinguishing factor among energy companies. Vijaya Menon, an analyst at Gulf-based energy research house PetroFin, commented: “When margins are tight, getting more from current assets is just as important as new-field development. AI gives an edge — but it is only as good as the data and the human workflows behind it.”
For SLB, the deal with ADNOC offers a showcase customer in one of the world’s major oil-producing nations. It strengthens its digital-services credentials in an age when oil-field services companies are under pressure to move beyond traditional drilling and completion to high-end tech and digital-analytics offerings.
Topics
Live News