How energy companies are using AI to capture and store carbon, even underground

During a time of both rapid transformation and intense scrutiny, today's energy industry leaders are increasingly turning to advanced solutions in AI and data management to drive sustainability and efficiency as the global community works to combat climate change. This is a time-sensitive effort, as increased energy demand and the continued role of fossil fuels mean emissions could keep rising through 2035.¹ As energy leaders look to reduce greenhouse gas emissions, the carbon capture and storage (CCS) industry has become a key component in the approach. Industrial carbon management (ICM) encompasses a range of technologies designed to capture, transport, and store carbon dioxide (CO₂) underground to prevent it from entering the atmosphere. Microsoft is actively collaborating with energy companies on industrial carbon management solutions. One example of this collaboration is Northern Lights, a partnership between the Norwegian government and energy companies Equinor, Shell, and TotalEnergies, which is now fully operational. This groundbreaking initiative was established to accelerate decarbonization and address emissions as we all work towards a more sustainable future.

Transforming the global energy industry is not a small feat, nor one that happens without the collective work of dedicated partnerships and innovative technology. The standardized data model and secure data sharing in Microsoft Azure Data Manager for Energy along with operations data management powered by Azure AI and Microsoft Copilot can accelerate innovation across the end-to-end CCS value chain. Copilot and Azure Data Manager for Energy put data and AI to work, integrating industry datasets, applications, and other cloud services-managing intensive workloads at global scale, and quickly ingesting data for analytics and decision-making. These are high-impact capabilities that ultimately help energy companies accelerate their transition to more sustainable practices by reducing time, costs, and risks associated with their complex operational requirements.

Enhancing energy operations with modern data management

Data modernization is a critical component in advancing sustainability and CCS efforts within the energy sector. By leveraging Azure Data Manager for Energy, energy companies can efficiently manage and analyze vast amounts of data-enabling more accurate and comprehensive simulations of subsurface reservoirs. This capability is essential for identifying optimal CO₂ storage locations and ensuring the safe and efficient injection and storage of carbon dioxide.

The platform's robust, scalable, and secure data management solutions allow for real-time data integration and continuous model refinement, which are crucial for making informed decisions and mitigating risks. Additionally, Azure Data Manager for Energy's high-performance computing capabilities enable rapid simulations, which significantly reduce the time required for planning studies and optimizing reservoir performance. These high-impact capabilities ultimately help energy companies accelerate their transition to more sustainable practices by reducing time, costs, and risks associated with their complex operational requirements.

Harnessing the power of AI with Copilot

Along with data modernization and robust data analytics, Azure Data Manager for Energy users will have the option to take advantage of Copilot to interact with well data. Azure Data Manager for Energy helps ingest and organize domain-specific data from across the enterprise data landscape to enhance data access, analysis, and application interoperability. Developed in alignment with OSDU® standards, Azure Data Manager for Energy helps get the right data organized within the right domain workflow while providing trustworthy data delivery that sets the stage for improved and timely analysis.

However, the enterprise data landscape for any analysis may extend beyond domain-specific data types and require reports with different file types, as well as images, data and records stored in other databases, spreadsheets, and shared folders. Further, the entire value chain extends into data from operations, supply chain, health, safety and environment (HSE), enterprise resource planning (ERP), legal and compliance, and even social media-some of which may be hosted on external platforms.

In these scenarios, generative AI capabilities can help users optimize data for enhanced insights-faster. One example of how to approach this is with Microsoft Fabric, an end-to-end analytics and data platform. Fabric can help integrate the data in Azure Data Manager for Energy with other adjacent data sources, ultimately preparing it for analysis and other interactions through AI and Copilot. This means users can potentially run traditional AI-powered workflows such as automated interpretation of data or event prediction through machine learning-driven algorithms. They can also leverage Copilot to chat with the data or implement intelligent search, domain-based intelligent assistants, or cross-domain intelligent advisors.

In doing so, end users-people in roles across geoscience or petrophysics-have an easier and faster way to interact with and query their data, both within and outside Azure Data Manager for Energy. Plus, data engineers and data scientists have a foundation from which to build similar solutions for their end users. The Copilot capabilities also mean simplified research processes and the generation of valuable data insights, enabling enterprise and business unit leaders, as well as data scientists and geophysicists, to make more informed decisions and take advantage of greater efficiencies in reservoir management.

Optimize carbon capture and storage and enhance reservoir management

Building on the capabilities of Copilot and Azure Data Manager for Energy, we can further optimize CCS to work towards a more sustainable future. Reservoir modeling is a critical aspect of modern energy management, playing a vital role in the underground storage of CO₂. This multidisciplinary field involves the integration of geological, geophysical, thermal, and engineering data to create detailed models of subsurface reservoirs. Reservoir engineers create models that simulate the behavior of fluids within the reservoir to predict future performance and optimize injection and production strategies. With global energy demand projected to increase 47% by 2050,² the need for sustainable energy solutions and CCS is paramount.

Microsoft is working with partners to provide the efficiency, predictive power, and speed of reservoir simulations and optimizations. Built on top of Azure Data Manager for Energy, customers can now leverage Azure's robust enterprise capabilities in security, scalability, and reliability, while accessing its domain-specific solutions and maintaining full control over their data.

Traditionally, identifying optimal CO₂ storage locations requires lengthy studies, sometimes spanning months or even years. The work Microsoft is doing with partners transforms this process by enabling scalable and efficient simulations. This will enable engineers to run numerous models in parallel, leveraging high-performance computing to quickly analyze vast datasets and identify the best storage locations. The ability to perform rapid simulations at scale significantly reduces the time required for planning studies.

Explore more energy solutions and resources

At Microsoft, our dedication and commitment to accelerating the energy transition to carbon-free resources is matched only by the power of our partner ecosystem and the knowledge-sharing that makes it all possible. With Azure Data Manager for Energy, industry leaders can connect to an open ecosystem of interoperable applications from independent software vendors (ISVs) and the Microsoft ecosystem of productivity tools. By harnessing capabilities and features from across Microsoft and partner solutions, energy leaders can optimize value across their entire enterprise while working towards sustainability goals.

Ready to dive deeper? Check out additional resources to learn more.

¹McKinsey & Company, Global Energy Perspective 2024, September 2024.

²S&P Global, Global energy demand to grow 47% by 2050, with oil still top source: US EIA, October 2021.

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