When AI Meets Oil: SLB and Nvidia’s Big Energy Bet

SLB and Nvidia deepen their AI partnership to modernize oilfield operations worldwide

4 Nov 2025

SLB and Nvidia are expanding their partnership to deploy artificial intelligence more deeply across oilfield operations, in a move aimed at improving efficiency and supporting the sector’s shift towards digital and sustainable practices.

Announced on September 19, 2024, the agreement will see both companies extend the global rollout of their joint technologies over the coming months. The collaboration builds on SLB’s experience in subsurface engineering and Nvidia’s capabilities in AI computing to help energy producers analyse complex geological and production data.

The partners are developing generative AI models to interpret field information and guide engineering decisions. By combining Nvidia’s AI software with SLB’s Delfi and Lumi platforms, the initiative seeks to deliver near real-time analysis that can identify potential operational issues and suggest corrective actions, reducing downtime and improving productivity.

“This collaboration bridges the gap between data and decision-making,” said SLB chief executive Olivier Le Peuch. Nvidia executives described the effort as a step toward “intelligent energy systems” that merge human expertise with computational power.

The initiative reflects a broader industry trend of using automation and digital tools to manage cost pressures and environmental challenges. Analysts say such alliances could accelerate the adoption of advanced analytics across the energy value chain, enabling more efficient production with a lower carbon footprint.

However, the expansion of AI in oilfield operations brings risks around data security, reliability and the need for human oversight. Companies are under pressure to ensure transparency and resilience as machine learning tools become more central to core operations.

Even so, executives and observers view the SLB and Nvidia collaboration as a significant step in the industry’s digital evolution. If widely adopted, the technology could help redefine operational decision-making in oil and gas, where data, rather than hydrocarbons alone, increasingly drives performance.