Innovation”.SLB Signs Collaboration Deal to Accelerate Digital Innovation

.

SLB and Shell announced a strategic partnership to co‑develop agentic‑AI and digital solutions for upstream oil and gas operations. Using SLB’s cloud‑native Lumi platform, the collaboration will integrate subsurface, well‑construction and production data to create autonomous decision‑engines that can recommend optimal drilling paths and predict equipment failures in real time. Building on a prior partnership that deployed SLB’s Petrel software across Shell’s assets, the joint effort aims to improve efficiency, lower costs, and potentially offer the platform to other operators, setting a new benchmark for AI‑driven workflow automation in the energy sector.

Key Terms

agentic AI
technical

Agentic AI refers to computer systems that can make their own decisions and take autonomous actions without human prompting for each step. This capability could reshape workflows across industries by giving technology a degree of independence to solve problems and achieve objectives on its own.

HOUSTON – Global energy‑technology leader SLB (NYSE: SLB) announced a strategic collaboration with Shell to co‑develop digital and AI solutions aimed at delivering measurable performance and efficiency gains throughout upstream operations.

Illustration of the collaboration’s focus on agentic AI–powered solutions for the energy sector.

The partnership targets the creation of agentic‑AI solutions that amplify the capabilities of technical experts and decision‑makers, while establishing an open data and AI infrastructure that unifies subsurface, well‑construction and production workflows in a secure digital environment.

The joint effort will leverage SLB’s Lumi™ data and AI platform, a cloud‑native environment that fuses petabytes of geological, engineering and production data with advanced analytics. By integrating Lumi with Shell’s existing digital assets, the two companies intend to accelerate the deployment of autonomous decision engines that can, for example, recommend optimal drilling trajectories in real time or predict equipment failures before they occur.

“The energy sector is undergoing a digital transformation driven by AI and automation,” said Rakesh Jaggi, president of SLB’s digital business. “Partnering with an industry heavyweight like Shell enables us to move faster, bringing agentic‑AI capabilities from prototype to production and unlocking value across the entire upstream value chain—from field planning to day‑to‑day operations.”

Earlier this year, SLB and Shell entered a technical partnership to roll out SLB’s Petrel™ subsurface software across Shell’s global assets. That initiative standardized data models and workflows, laying the groundwork for scalable digital solutions and delivering early cost‑efficiency gains. The new collaboration builds on that foundation, expanding the scope to include well‑construction and production data, and aligning with Shell’s broader digital‑transformation roadmap.

Industry analysts see this move as a bellwether for the sector. By combining SLB’s expertise in high‑performance computing, geoscience analytics, and AI‑driven workflow automation with Shell’s extensive field data and operational scale, the partnership could set a new benchmark for how oil and gas companies extract value from data. The joint platform may also become a commercial offering for other operators, potentially creating a new revenue stream for both firms and accelerating industry‑wide adoption of autonomous decision‑making tools.

SLB (NYSE: SLB) is a global technology company focused on energy innovation for a balanced planet. Operating in more than 100 countries and employing a workforce that spans nearly twice as many nationalities as there are companies, SLB concentrates on three core pillars: advancing oil and gas production, delivering digital solutions at scale, and decarbonizing industry through new energy systems and technologies.

Forward‑looking statements in this release are subject to risks and uncertainties, including the ability to achieve projected efficiency gains, regulatory approvals, market adoption of AI‑driven solutions, and broader macro‑economic conditions. Actual results may differ materially from those expressed in these statements. SLB disclaims any obligation to update these statements, except as required by law.

Source: SLB

Original article, Author: Jam. If you wish to reprint this article, please indicate the source:https://aicnbc.com/14390.html

Like (0)
Previous 7 hours ago
Next 6 hours ago

Related News