Fuel Innovation in Energy

Accelerating the Transition to a Sustainable Future

Leading energy companies are using NVIDIA technologies to transform the industry and improve quality of life around the world. By pursuing renewable energy sources, building smarter, more resilient grid operations, expediting energy exploration and production, and ensuring safe conditions for workers and communities, they’re helping us move toward a brighter, more sustainable future.

Extract Value from Data

Turn massive amounts of data from routine upstream  operations, pipeline and refinery sensors, and maintenance processes into actionable insights using NVIDIA AI tools.

Supercharge Your Compute

Speed up geophysical and engineering applications with high-performance computing, whether on-prem in your data center or in the cloud.

Protect Health and Environment

Ensure that proper personal protective equipment (PPE) protocols are followed and safety hazards are identified by using AI to observe equipment, predict and detect failures, and save lives.

Streamline Industry Segment Processes

  • Upstream

  • Midstream

  • Downstream

  • Utilities

Exploration and Production

NVIDIA GPU-accelerated computing platforms have been instrumental in supporting Eni’s exploration activity, improving our ability to turn around advanced seismic imaging tasks in a shorter time and with a higher accuracy.

Seismic Data Processing

Whether you’re using reverse time migration (RTM), Kirchhoff, or full-waveform inversion (FWI) algorithms, seismic processing on NVIDIA GPUs can reduce the time to oil by processing seismic data up to 5X faster than using CPUs alone. By using NVIDIA GPUs, geophysicists processing seismic surveys can apply advanced filters and interpret results on the most complex datasets.

Read how to reduce costs with one-pass reverse time migration >

Geoscience Visualization

Whether you’re using a local workstation or a virtual desktop, NVIDIA professional solutions boost throughput for visualization and heavy computation.

High-performance computing (HPC) and AI improve the calculation of 3D seismic trace attributes and visual analysis of regional basins right at the interpreter’s desk.

Explore GPU-accelerated scientific visualization >

Learn about remote work solutions for geoscience >

Reservoir Simulation

Maximize reservoir performance with the most sophisticated modeling and simulation technology available. NVIDIA GPUs running on CUDA® software speed up and reduce model processing cycle times, allowing researchers to get the most value in the least amount of time.

Watch webinar on advancing the future of energy with high-performance AI  >

Learn how Stone Ridge Technology and Eni developed the world’s fastest reservoir simulation software on NVIDIA GPUs >

Health, Safety, and Environment

Protecting employees, contractors, and the environment is the most important job of energy companies today.  Leveraging NVIDIA Metropolis, businesses can make their wellsites safer and smarter by applying deep learning to video streams for applications such as employee safety, traffic management, and resource optimization.

Read how Netherlands-based Rolloos uses AI to make oil rigs safer for workers >

Pipeline Optimization

Leverage big data and AI systems to optimize how you fill a pipeline, detect corrosion to identify potential leaks, and automate ultrasonic flow meters to increase throughput. These technologies can also be used to monitor the locations of transports and verify their security.

Other areas include demand forecasting to optimize commodity trading and  shipping and pipeline capacity optimization.

Using deep learning and machine learning algorithms, oil and gas companies can determine the best way to optimize their operations as conditions change.

— “NVIDIA and Baker Hughes, a GE Company, Pump AI Into Oil and Gas Industry,” NVIDIA Blog

Predictive Maintenance

Avoid blackouts, downtimes, and unnecessary maintenance costs by identifying discrepancies in machinery in real time and predicting the remaining useful life of equipment. With GPU-based deep learning servers like NVIDIA® DGX A100, well operators can visualize and analyze massive volumes of production and sensor data such as pump pressures, flow rates, and temperatures.

And with NVIDIA Omniverse and NVIDIA Modulus, global energy giant Siemens Energy is building a digital twin that could help save $1.7 billion per year in predictive maintenance of heat recovery steam generators.

Other areas of focus include capacity optimization, economic forecasting, and site surveillance.

Customer interacting with a speech-enabled food kiosk.

Performance Optimization

Increase the reliability and performance of your refining assets by identifying the root cause of underperformance, virtual testing operational or asset changes, and minimizing unanticipated risks of proposed changes.  

Power Generation and Distribution

Accelerate the transition to a more sustainable future with smart, resilient grids that can forecast demand, generate power, and manage energy resources.

Hydrocarbon

Explore new energy deposits and discover available hydrocarbon reserves with seismic processing. Build accurate models of the subsurface in less time on NVIDIA GPUs.

Renewable

Optimize renewable energy production and cut operational costs, such as wind turbine inspection and maintenance, with AI.

Electricity Retail

Predict future load demand by using advanced metering infrastructure (AMI) data in machine learning models running on NVIDIA GPUs.

Power Grids

Improve the performance of complex grid operations optimization and modeling techniques run on NVIDIA GPUs.

Watch Webinar on Optimizing Power Grids with Dynamic Modeling on NVIDIA GPUs >

Our Partners

Baker Hughes
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Conundrum
CPFD
Emerson
GeoComputing Group
Halluburton Landmark
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IHS Markit
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Ridgeway Kite
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Schlumberger
Seismic City
Spark Cognition
Stone Ridge Technology

The NVIDIA A100 80GB PCIE allows our customers to immediately double their reservoir model size within the same hardware footprint. In addition, the 25% increase in memory bandwidth will allow these models to run faster than ever.

- Vincent Natoli, CEO, Stone Ridge Technology

We were proud to be involved with NVIDIA's prerelease testing campaign for the NVIDIA A100 80GB PCIE card. It delivered a step change in raw performance for our research and production GPU solutions while its robust tooling aligns perfectly with our agile, responsive approach to emerging client needs.

- Stuart Midgley, Chief Information Officer, DUG Technology

NVIDIA Solutions for Energy Industries

Real-Time AI at the Edge

Computing at the Edge

By collecting and analyzing data at the network’s edge, companies can predict mechanical problems in areas like oil pumps more quickly. Today's industrial edge computing requires GPU-powered compute capabilities for industrial inspection and robotics in factories and predictive maintenance for equipment in the field.  The NVIDIA EGX platform provides a single, unifying foundation for industry-leading edge AI applications and frameworks.

Powerful Computing for Data Centers

Computing in Data Centers

Create efficiencies through high-performance computing, data processing, and data management that support the unique requirements of the industry’s key segments and processes. NVIDIA GPU-accelerated solutions dramatically speed up training of deep learning and machine learning models to deliver insights that were previously not possible. From edge to data center, NVIDIA GPUs are available from every major computer system and server manufacturer. They’re also available in NVIDIA DGX Systems, which are equipped with the DGX software stack for rapid deployment, to meet the demands of deep learning and machine learning developers.

Real-Time AI at the Edge

Democratize the Data Center with the Cloud

Deliver power from suppliers to consumers using cloud computing to save energy, reduce costs, and increase reliability. NVIDIA GPUs are available on-demand in all major cloud platforms worldwide, and the NGC catalog provides GPU-accelerated containers for easy deployment, including deep learning frameworks such as TensorFlow, PyTorch, MXNet, and more. NVIDIA Metropolis, the application framework for smart cities, is fully integrated with Azure IoT Edge and will soon be integrated with AWS IoT Greengrass.

Powerful Computing for Data Centers

Accelerate Your Workflows with Software

NVIDIA software libraries and SDKs create a scalable solution that enables customers to deploy inference and AI in the cloud, on their servers, or at the edge. This software investment is designed to accelerate customer time to deployment and reduce overall development costs. NVIDIA software and SDK resources include NVIDIA JetPack for embedded applications, DeepStream for intelligent video analytics (IVA), NVIDIA Isaac and NVIDIA TensorRT for inference, TAO Toolkit for tuning deep neural networks (DNNs), NGC catalog for containers and AI software, and much more.

Learn more about the latest innovations in energy.