Industries Energy

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.

Discover How the Energy Industry Is Using AI and HPC

Accelerate reservoir simulation and seismic processing for fuel production.

Oil and Gas Operations

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.

Build industrial and scientific digital twins for sustainability and safety.

Surface Operations

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.

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

Power and Utilities

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.

HGX H100 80GB*8

Accelerating Pseudo-Spectral-Based Reverse Time Migration Applications

See how BP achieved 35X runtime speedups by porting their production reverse time migration (RTM) code onto NVIDIA HGX™ A100 and leveraging the cuFFT library.


Visualizing Large-Scale, Super-Resolution Core Samples

Explore how Chevron utilized NVIDIA IndeX®, a 3D volumetric interactive visualization SDK, in Microsoft Azure to streamline analysis of core samples—in larger volumes and at higher resolution. ​

H100-NVL, and H100-PCIe NVIDIA GPUs

Stone Ridge Technology Boosts ECHELON by 3.8x on NVIDIA GPUs

Stone Ridge Technology benchmarked their ECHELON reservoir simulation software on the NVIDIA Hopper GPU architecture, including the NVIDIA Grace Hopper Superchip, H100-NVL, and H100-PCIe. Learn how the company achieved up to 3.8x faster simulations with up to 25-million cell models.

global energy companies

Developing Power Plant Digital Twins to Save Billions Annually

Learn how global energy companies such as Siemens Energy are building industrial digital twins to support predictive maintenance at power plants and how that could save the energy industry an estimated $1.7 billion a year.

NVIDIA® Jetson™ edge AI platform

Edge Computing Monitors Millions of Utility Poles for Needed Repairs

Take a look at FirstEnergy’s onboard smart camera system—developed by Noteworthy AI and powered by the NVIDIA® Jetson™ edge AI platform—which automatically monitors millions of utility poles and tens of millions of grid devices for maintenance.

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.

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 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.

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.