Oil and Gas Operations Powered by AI

Accelerate subsurface workloads with AI, high-performance computing (HPC) and visualization.

    Reduce Emissions and Environmental Impact From Oil and Gas Operations

    Oil and gas enterprises are becoming integrated energy companies, using improved processes to better explore, produce, transport, and distribute fuels to consumers around the world. Global initiatives for decarbonization are accelerating the transition from fossil fuels to alternative fuels with a smaller carbon footprint and scaling renewable energy, such as wind, solar, nuclear, hydroelectric, green hydrogen and geothermal.

    Industry Panel: Building a Lower-Carbon Future With HPC and AI in Energy

    Learn how ExxonMobil, Shell, SLB, and Petrobras are using AI and HPC to enhance energy exploration and production, reduce operational emissions, and accelerate carbon capture, utilization, and storage (CCUS) development.

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    Stone Ridge Technology Reduces Compositional Model Runtimes With NVIDIA GPUs

    See how Stone Ridge Technology accelerated simulations of multi-million-cell deep-water reservoirs, offshore oil fields, and deep-water gas fields with ECHELON 2.0 running on Eni's HPC5 cluster.

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    Use Cases

    Discover How Energy Companies Are Using AI and HPC

    Success Stories

    See the Real-World Impact for AI in Energy Exploration

    Learn from energy companies using AI to improve energy production and reduce operating costs.

    Saudi Aramco Pioneers AI Assistant for Seismic Data Processing Workflows

    Learn how Saudi Aramco built an AI assistant to enhance seismic data processing—compiled with NVIDIA® TensorRT™-LLM, deployed using NVIDIA Triton™ Inference Server, and fine-tuned with NVIDIA NeMo™ Guardrails.

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    Saudi Aramco

    Petrobras and NVIDIA Accelerate Linear Solvers on NVIDIA Grace CPU

    Learn how Petrobras built SolverBR—a specialized linear solver powered by the Arm®-based NVIDIA Grace™ CPU—and achieved up to a 60 percent speedup in reservoir simulations.

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    Using AI and HPC to Improve Efficiency, Safety, and Sustainability

    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.

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    Shell

    Powering Energy’s Top Supercomputers

    Powering Energy’s Top Supercomputers

    As the world moves toward a more sustainable future, global leaders in energy are accelerating their key HPC and AI workloads with NVIDIA’s full-stack platform. The result? Some of the most powerful, efficient supercomputers in the industry—including those from Eni, ExxonMobil, Petrobras, Saudi Aramco, Total, and the U.S. Department of Energy—are built on NVIDIA technology and continually rank near the top of the TOP500 and Green500 lists.

    Our collaboration with NVIDIA provides great value because NVIDIA brings expertise in AI and a powerful HPC platform to conduct these studies. Conversely, Shell injects realism and provides the energy experience that provides great value to NVIDIA.

    – Detlef Hohl, Chief Scientist of Computation and Data Science, Shell

    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 FNO-based networks dealing larger input datasets and providing acceptable predictions over longer time windows (hundreds of years), and next-generation digital twin models of deep earth for carbon capture and storage (CCS) applications in real time with uncertainty assessment.

    – Pandu Devarakota, Principal Science Expert, Shell

    In 2022, over 70 percent of computing resources at BP’s Center for High-Performance Computing were used by reverse time migration (RTM)-related applications. In RTM benchmarking and validation tests, we found that one NVIDIA HGX A100 with no compression achieved up to a 35X peak shot runtime speedup compared to our in-house CLXAP cluster.

    – Muhong Zhou, Senior HPC Software Developer, BP

    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

    The exploration and production (E&P) industry generates a vast amount of data, including well logs, seismic data, production data, drilling data, and other sources. Natural language processing (NLP) and large language models (LLMs) have provided the ability to integrate sources with descriptive, diagnostic, prescriptive, and predictive insights that enhance return on investment. In reservoir modeling, NLP and LLMs improve integrating sources from well logs, seismic data, and production data—bringing critical understanding to the subsurface that’s significant to our operations.

    – Saud Zakwani, Head of Data Science, Petroleum Development Oman

    AI can help in site selection and allocation by studying the physics, geology, and metrology of different locations to optimize solar plants or wind farms and make them more cost-effective and productive. Once facilities are deployed, we can look at AI to balance the grid and identify production capacity predicted from renewable energy. AI can help optimize a large installation of batteries, such as charging and discharging or maintenance issues.

    – Yehia Khoja, Ministry of Energy, Head of AI and Business Development, Kingdom of Saudi Arabia

    News and Events

    Accelerating SLB INTERSECT up to 11X With NVIDIA GPUs

    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.

    Read Tech Brief

    Shearwater GeoServices Collaborates With NVIDIA to Optimize Reveal for GPUs

    Shearwater GeoServices is optimizing their Reveal seismic processing software for NVIDIA GPUs to help energy companies enhance seismic data and efficiently run compute-intensive imaging algorithms.

    Read Shearwater Press Release
    Bringing AI to Every Industry

    Image courtesy of AWS and MATLAB.

    Building Deep Learning Models for Geoscience Using MATLAB and NVIDIA GPUs on Amazon EC2

    Understand how geoscientists can use shallow deep learning-based algorithms with MATLAB on AWS and AI models to automatically recognize distinct geologic features in seismic images.

    Read AWS Blog: Part 1

    Learn how to develop and deploy AI-based seismic facies classification by leveraging cloud-based HPC resources for faster prototyping and development with large 3D seismic datasets.

    Read AWS Blog: Part 2

    Technology

    Solutions for the Oil and Gas Industry—From Data Center to Edge to Cloud

    Learn about the AI and HPC hardware and software for oil and gas.

    NVIDIA DGX H100

    NVIDIA DGX H100 expands the frontiers of business innovation and optimization. The latest iteration of NVIDIA’s legendary 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.

    Explore DGX H100

    NVIDIA DGX SuperPOD

    NVIDIA DGX SuperPOD is an AI data center infrastructure platform that enables IT to deliver performance without compromise for every user and workload. DGX SuperPOD offers leadership-class accelerated infrastructure and agile, scalable performance for the most challenging AI and HPC workloads, with industry-proven results.

    Explore SuperPOD

    NVIDIA DGX Cloud

    NVIDIA DGX Cloud is a multi-node AI-training-as-a-service solution optimized for the unique demands of enterprise AI. Access NVIDIA DGX Cloud to experience a combined software and infrastructure solution for AI training that includes a full-stack AI developer suite, leadership-class infrastructure, and concierge support.

    Explore DGX Cloud

    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 delivers 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.

    Explore Superchip

    NVIDIA HPC SDK

    The NVIDIA HPC Software Development Kit (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.

    Explore HPC SDK

    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 access to NVIDIA AI Enterprise with free curated labs to start testing.

    Get Started

    NVIDIA Virtual GPU (vGPU)

    NVIDIA vGPU software enables powerful GPU performance for workloads ranging from graphics-rich virtual workstations to data science and AI, enabling IT to leverage the management and security benefits of virtualization, as well as the performance of NVIDIA GPUs required for modern workloads.

    Explore vGPU

    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. Energy companies are exploring large language models in sentiment analysis for oil price prediction, as well as integrating sources from well logs, seismic data, and production data to generate real-time insights.

    Explore Nemo Framework

    NVIDIA Metropolis

    NVIDIA Metropolis features GPU-accelerated SDKs and developer tools that help developers optimally build, deploy, and scale AI-enabled video analytics and IoT applications—from the edge to the cloud.

    Explore Metropolis

    Resources

    Take a Deeper Dive Into AI for Oil and Gas Exploration

    On-Demand Sessions

    Accelerating End-to-End Data Science Workflows

    Use NVIDIA RAPIDS™ to apply a wide variety of GPU-accelerated machine learning algorithms, including XGBoost, cuGRAPH’s single-source shortest path, cuML’s k-nearest neighbor (KNN), DBSCAN, and logistic regression, for data analysis at scale.

    Learn How to Speed up Data Science Pipelines

    Physics-Informed Machine Learning With Modulus

    Gain an understanding of the various building blocks of NVIDIA Modulus, the basics of physics-informed deep learning, and how the framework integrates with the overall NVIDIA Omniverse™ platform.

    Learn How to Build Physics-Informed Neural Networks With Modulus

    High-Performance Computing With Containers

    Learn how to reduce complexity and improve portability and efficiency of your code by using a containerized environment for HPC application development.

    See How Containers Enable Portable, Bare-Metal Performance in HPC

    Build an AI Center of Excellence

    Learn how to use NVIDIA Base Command™ Platform to accelerate containerized AI training workloads, identify the tools necessary to build an AI center of excellence, and get the basics of working with, modifying, and running Docker containers from NVIDIA NGC™.

    Learn how to use NVIDIA Base Command™ Platform

    Tuning and Deploying a Language Model on NVIDIA H100

    Transform your AI workloads with the NVIDIA H100 Tensor Core GPU, featuring Multi-Instance GPU (MIG), the Transformer Engine, and NVIDIA AI Enterprise.

    Get Experience Running a Transformer Model Using an H100 Dynamic MIG Instance

    NVIDIA Inception Program

    Explore NVIDIA Inception, the free program designed to help startups evolve faster through access to cutting-edge technology and NVIDIA experts, connections with venture capitalists, and co-marketing support to raise visibility.

    Join Inception

    NVIDIA Developer Program

    Connect with millions of like-minded developers in the NVIDIA Developer Program to do your life’s work, and gain access to free containers, pretrained models, SDKs, technical documentation, and peer and domain expert help.

    Join the Developer Program

    NVIDIA VC Alliance

    Expand and support your portfolio with NVIDIA’s Venture Capital (VC) Alliance, an initiative between NVIDIA and investors around the world who are focused on startups building cutting-edge technology with AI, data science, and HPC.

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    NVIDIA Partners for Energy

    NVIDIA solutions for the energy industry go beyond products. Our partners are here to assist your organization at every level to build and execute transformative AI strategies, products, and services.

    Meet Our Partners

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