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AI-Driven Workflows Advance Upstream Digitalization
SLB and Shell begin strategic collaboration to develop shared data and AI infrastructure for subsurface and production workflows.
www.slb.com
As oil and gas operators look for practical ways to improve the efficiency of subsurface evaluation, well construction, and production management, digital infrastructures capable of integrating large volumes of technical data have become a priority. In this context, SLB has entered a strategic collaboration with Shell to jointly develop digital and AI solutions designed to improve measurable performance across upstream operations, both within Shell’s assets and potentially across the wider industry.
The cooperation focuses on building agentic AI-powered applications—systems designed to support and augment the work of geoscientists, drilling engineers, production specialists, and asset teams. The objective is to standardize and automate parts of technical workflows while ensuring that experts remain central to the interpretation and validation of results.
Why This Collaboration Represents a New Step in Upstream Digitalization
The initiative aims to create an open data and AI infrastructure using SLB’s Lumi platform. The project intends to unify currently fragmented datasets and workflows across subsurface modeling, well engineering, and production optimization. For operators, these areas often rely on highly specialized software environments that can limit cross-domain integration.
By focusing on a shared infrastructure, the collaboration seeks to reduce manual data handling, streamline planning cycles, and strengthen operational decision-making. The work embeds security and data governance measures to allow the controlled use of sensitive subsurface and operational information.
Applications Across Subsurface, Drilling, and Production
The solutions planned under the agreement target workflows commonly used in:
- Subsurface characterization—including seismic interpretation, reservoir modeling, and uncertainty assessment.
- Well construction—from trajectory design and drilling parameter optimization to real-time operational decision support.
- Production operations—such as monitoring, forecasting, and optimization of well and field performance.
Agentic AI systems developed on a unified data platform can help reduce repetitive tasks, surface operational risks earlier, and improve the consistency of technical evaluations. For large enterprises with global portfolios, standardization also enables reproducible workflows across assets and regions.
Connection to Earlier Digital Standardization Efforts
This collaboration builds on the companies’ long-standing relationship. Earlier this year, SLB and Shell established a technical partnership to deploy SLB’s Petrel subsurface software across Shell’s global operations. That initiative focused on standardizing digital infrastructure, enabling scalable workflows, and reducing operational complexity in subsurface interpretation and modeling.
The new agreement extends this strategy by linking subsurface, well construction, and production domains into a more unified digital environment. It also includes mutual learning on digital transformation approaches and contributes to developing digital solutions that are technically and commercially viable for broader industry adoption.
Connection to Earlier Digital Standardization Efforts
This collaboration builds on the companies’ long-standing relationship. Earlier this year, SLB and Shell established a technical partnership to deploy SLB’s Petrel subsurface software across Shell’s global operations. That initiative focused on standardizing digital infrastructure, enabling scalable workflows, and reducing operational complexity in subsurface interpretation and modeling.
The new agreement extends this strategy by linking subsurface, well construction, and production domains into a more unified digital environment. It also includes mutual learning on digital transformation approaches and contributes to developing digital solutions that are technically and commercially viable for broader industry adoption.
