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.
Deliver a reliable supply of lower-cost fuels and power, while optimizing energy efficiency.
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.
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.
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.
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.
Learn from industry leaders using AI to optimize processes, reduce risk, and trim costs.
Image courtesy of BP.
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.
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Image courtesy of BP.
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.
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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.
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.
Image courtesy of Noteworthy AI.
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.
Image courtesy of Noteworthy AI.
Shell has ongoing work with NVIDIA: more realistic 3D reservoir models (e.g., dipping reservoir) for CO2 storage, layered geology with horizontal and vertical heterogeneity, computationally efficient Fourier neural operator (FNO)-based networks dealing with larger input datasets and providing acceptable predictions over longer time windows (hundreds of years), and the capability to build next-generation digital twin models of deep earth for climate change scenario (CCS) applications in real time with uncertainty assessment.
— Pandu Devarakota, Principal Science Expert, Shell
We can examine the contribution of AI to the energy sector from three dimensions: energy forecasting, carbon capture, and predictive maintenance... AI algorithms are being used for energy forecasting, to predict energy demand, and to optimize economic value... AI can be used to reduce carbon emissions by analyzing data from multiple sources regarding weather, soil, and crop yield... to optimize our supply chain logistics and reduce our carbon footprint... AI can also help energy companies monitor the performance of their assets and equipment.
— Nayef Otaibi, Vice President and Chief Digital Officer, Saudi Aramco
We will continue to collect data, not just on how our wind turbines operate, but also for weather forecasting, site planning, and other areas to optimize wind turbine sites. We're exploring augmented reality and extended reality as wind turbines are complicated machines with many types of failure modes. It's imperative to make sure the wind turbines operate safely and service technicians know how to do service repairs in the right way.
— Lasse Lundberg Nowack, Vice President, Engineering Development Power Solutions, Vestas
By using synthetic data generation in NVIDIA Omniverse, our goal was to automatically create thousands of labeled photorealistic examples of various defects in grid assets. We are in the process of using real images and these synthetic images to train inspection models.
— Ankush Agarwal, Director of Advanced Analytics, Exelon
In Oregon, we are experiencing the impacts of climate change firsthand and recognize the urgent need for innovation at the grid edge as we transition to a clean energy future. Investing in new technologies for the grid is a key strategy for PGE to achieve its climate goals and provide customers with clean, affordable, and resilient energy.
— Ananth Sundaram, Senior Manager of Integrated Grid, Portland General Electric (PGE)
A new blueprint for interactive virtual wind tunnels enables unprecedented computer-aided engineering exploration for Altair, Ansys, Cadence, Siemens, and more.
Systems powered by NVIDIA A100 80GB Tensor Core GPUs demonstrate superb performance uplifts compared to CPU performance running SLB’s INTERSECT high-resolution reservoir simulator.
Shearwater is expanding its collaboration with NVIDIA to innovate subsurface processing and imaging with higher performance-per-watt, energy efficiency, and fewer emissions with the NVIDIA Grace Hopper™ Superchip.
Aclara will be the first company to embed Utilidata’s distributed AI platform, Karman, in a smart meter to enable a connected grid that delivers clean and reliable energy. Built on a custom NVIDIA module that leverages AI, Karman captures robust, high-quality data to improve grid operations and manage distributed energy resources.
NVIDIA Project DIGITS brings the power of Grace Blackwell to developer desktops. The GB10 Superchip, combined with 128GB of unified system memory, lets AI researchers, data scientists, and students work with AI models locally with up to 200 billion parameters.
Learn about the AI and HPC hardware, software, and networking solutions for energy companies.
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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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