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SLB and NVIDIA Team Up to Enhance Energy Sector with Generative AI

September 19, 2024
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Joerg Hiller
Sep 19, 2024 18:00

SLB and NVIDIA collaborate to develop generative AI solutions for the energy industry, leveraging NVIDIA NeMo and AI Enterprise platforms.





Global energy technology company SLB has announced a significant milestone in its ongoing collaboration with NVIDIA. The two companies are set to develop and scale generative AI solutions tailored for the energy industry, according to NVIDIA Technical Blog.

Advancing AI Solutions for Energy

SLB and NVIDIA’s partnership aims to accelerate the development and deployment of energy-specific generative AI foundation models. These models will be integrated across SLB’s global platforms, including the Delfi digital platform and the new Lumi data and AI platform. The initiative leverages NVIDIA NeMo, part of the NVIDIA AI Enterprise software platform, to create custom generative AI that can operate in data centers, cloud environments, or at the edge.

The collaboration focuses on building and optimizing AI models to meet the unique requirements of the data-intensive energy sector. This includes applications in field planning, development, production operations, and data management. By doing so, the partnership aims to unlock the full potential of generative AI for energy domain experts—researchers, scientists, engineers, and IT teams—enabling them to engage with complex technical processes in innovative ways to achieve higher value and lower carbon outcomes across the energy value chain.

Extending a 15-Year Partnership

SLB and NVIDIA’s collaboration dates back to 2008, when they first utilized NVIDIA GPUs for subsurface imaging and reservoir simulation. Over the years, the companies have optimized each generation of SLB’s high-performance computing technologies, currently available on its Delfi platform with the latest NVIDIA accelerated computing platform.

In addition to their bilateral efforts, SLB and NVIDIA have partnered with Dell Technologies to deliver HPC and AI solutions to energy customers. These solutions include offerings for SLB Intersect, Omega, and Delfi.

Seismic Foundation Models and AI Copilots

Energy companies are increasingly turning to generative AI to enhance current and future energy systems, balancing energy production with decarbonization goals. Industry-specific generative AI solutions provide new insights from enterprise data, helping to solve complex challenges swiftly.

NVIDIA’s accelerated computing and software provide a comprehensive platform for developing and deploying generative AI capabilities. SLB recognizes the benefits of using NVIDIA NIM microservices to optimize performance and efficiency for enterprise-scale AI deployments. This allows SLB customers to seamlessly integrate NeMo into their technical workflows, improving performance, optimizing processes, and driving innovation.

At the recent SLB Digital Forum 2024, SLB showcased its ongoing projects, including:

  • A seismic vision transformer foundation model designed to accelerate seismic data processing and enhance productivity for researchers and scientists in exploration geophysics.
  • A coding copilot utilizing a fine-tuned large language model (LLM) trained on SLB internal data to significantly improve the customer experience of software tools.

These developments aim to facilitate ease of use for reservoir engineers and geoscientists, accelerating decision-making processes with real-time insights from concurrent AI models.

Conclusion

Generative AI offers energy companies the potential to enhance exploration, production, and delivery of energy resources through sustainable operations. SLB’s custom generative AI models, developed using NVIDIA NeMo and NIM, aim to assist scientists and engineers in leveraging enterprise data for subsurface understanding. This AI-driven approach promises breakthroughs in customer engagement, operational efficiency, and revenue growth.

For more details on the SLB and NVIDIA collaboration, visit the NVIDIA Technical Blog.

Image source: Shutterstock


Credit: Source link

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