Fuel Innovation in Energy

Deliver a reliable supply of lower-cost fuels and power, while optimizing energy efficiency.

Powering the Future of Energy With AI and High-Performance Computing

To meet global demands, energy companies are turning to a software-defined approach to explore, produce, transport, and deliver lower-cost energy while pursuing net-zero emission goals. They’re leveraging AI and high-performance computing (HPC) to reduce environmental impact from subsurface operations, automate manually intensive surface operations, and bring real-time intelligence to the grid edge.

Shell Uses AI and HPC to Improve Efficiency, Safety, and Sustainability in Energy

Learn how Shell used NVIDIA DGX™ systems to determine salt boundaries in reservoir modeling, enable 4K iterative image reconstruction, test new designs for industrial plants, and drive advancements in sustainable new materials.

Siemens Gamesa Maximizes Wind Energy Using Wake Optimization

Siemens Gamesa is optimizing their offshore wind farms for maximum power output at minimal cost using NVIDIA Omniverse™ and NVIDIA Modulus. Find out how neural super-resolution accelerates simulation times from 40 days to 15 minutes.

Use Cases

Discover How the Energy Industry Is Using AI and HPC

Oil and Gas Operations

Accelerate reservoir simulation and seismic processing for fuel production.

Learn how AI is accelerating reservoir simulation and seismic processing, enhancing pipeline monitoring, and protecting worker health and safety, while reducing emissions and environmental impact.

Surface Operations

Build industrial and scientific digital twins for sustainability and safety.

Find out how AI is being used to develop physically accurate industrial digital twins, scale renewable energy generation, simulate climate and weather, speed up computational fluid dynamics (CFD) workloads, and optimize industrial site efficiency.

Power and Utilities

Enhance power generation, transmission, and distribution for grid resiliency.

Explore the future of software-defined smart grids, including predictive maintenance of grid infrastructure, management of distributed energy resources, synthetic data generation of grid assets, outage scheduling, truck roll optimization, and utility contact center virtual assistants.

Success Stories

See the Real-World Impact of AI in Energy

Learn from industry leaders using AI to optimize processes, reduce risk, and trim costs.

News and Events

Technology

Energy Solutions—From Data Center to Edge to Cloud

Learn about the AI and HPC hardware, software, and networking solutions for energy companies.

NVIDIA Grace Hopper Superchip

The NVIDIA Grace Hopper™ Superchip is a breakthrough accelerated CPU designed from the ground up for giant-scale AI and HPC applications. The superchip will deliver up to 10X higher performance for applications running terabytes of data, enabling scientists and researchers to reach unprecedented solutions for the world’s most complex problems.

NVIDIA DGX H100

The latest iteration of NVIDIA DGX™ systems and the foundation of NVIDIA DGX SuperPOD™, DGX H100 is the AI powerhouse that’s accelerated by the groundbreaking performance of the NVIDIA H100 Tensor Core GPU.

NVIDIA DGX Cloud

NVIDIA DGX Cloud is a multi-node AI-training-as-a-service solution optimized for the unique demands of enterprise AI. It’s a combined software and infrastructure solution for AI training that includes a full-stack developer suite, leadership-class infrastructure, and concierge support, allowing businesses to get started immediately with predictable, all-in-one pricing.

NVIDIA AI Enterprise

With NVIDIA AI Enterprise, energy companies can speed up development of use case applications, such as reservoir simulation, seismic processing, and predictive maintenance. Learn how to get free, short-term access to NVIDIA AI Enterprise in curated labs through NVIDIA LaunchPad.

NVIDIA HPC SDK

The NVIDIA HPC SDK includes the proven compilers, libraries and software tools essential to maximizing developer productivity and the performance and portability of HPC modeling and simulation applications.

NVIDIA Modulus

NVIDIA Modulus is an open-source framework for building, training, and fine-tuning physics-informed machine learning (physics-ML) models with a simple Python interface. With Modulus, you can build models for enterprise-scale digital twin applications across multiple physics domains, from CFD to structural analysis to electromagnetics to climate science.

NVIDIA Omniverse Enterprise

NVIDIA Omniverse is an extensible, open platform built for 3D virtual collaboration and real-time physically accurate simulation. Omniverse combined with NVIDIA Modulus, a framework for developing physics machine learning neural network models, enables digital twins for wind farms, power plants, electric grids, and someday Earth itself.

NVIDIA Jetson Edge AI Platform

NVIDIA Jetson brings accelerated AI performance to the edge in a power-efficient and compact form factor. Together with the NVIDIA JetPack™ SDK and NVIDIA Isaac™ software for Robotics Operating System, these Jetson modules, including NVIDIA Jetson Orin Nano™, support a full range of edge AI and robotics applications.

NVIDIA Nemo Framework

NVIDIA NeMo™, part of the NVIDIA AI platform, is an end-to-end, cloud-native enterprise framework for building, customizing, and deploying generative AI models with billions of parameters. The NeMo framework provides an accelerated workflow for training with 3D parallelism techniques, several customization techniques, and optimized at-scale inference of large-scale models for language and image applications.

Resources

Take a Deeper Dive Into AI in Energy

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Powering the Future of Clean Energy | I Am AI

To manage renewable energy at scale, NVIDIA and its ecosystem of partners are using AI to optimize solar and wind farms, simulate climate and weather, maintain power grids, advance carbon capture, and power fusion breakthroughs.

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