Data & Analytics
Researchers at the University of Houston have developed a new ultrathin, carbon-based film that could make AI chips run faster, cooler, and more energy-efficient.
The energy sector is rapidly transforming toward a data-driven, decentralized future where combining human expertise with AI and machine learning unlocks new efficiencies, solves complex challenges, and creates a decisive competitive advantage.
Jim Clark, a reservoir engineer with more than 4 decades of experience, reflects on the evolution of subsurface engineering and CCS, emphasizing the growing importance of analytics, cross-disciplinary skills, and technical curiosity for the next generation of engineers.
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The SPE Europe Energy GeoHackathon aims at educating and disseminating knowledge to all the participants on how data science applications can support geothermal energy developments and drive the energy transition. Boot camps begin 21 October. -
Experts at SPE’s Annual Technical Conference and Exhibition say that despite AI’s great potential, it’s important to be realistic about AI’s capabilities and to remember that successful projects solve specific business problems.
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Collaboration and technology will help the industry meet its toughest challenges, experts said during the opening session at ATCE.
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Prajakta Kulkarni, SPE, has spearheaded the development of a global digital platform to optimize pricing, strategy, and sales in the industry. With a background in petroleum engineering, she identified a digital gap in the industry, leading her to create a platform that enhances data-driven decision-making, streamlines operations, and integrates AI technologies to imp…
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SPE is excited to livestream these thought-provoking and informative Tech Talks from the SPE Energy Stream studio at the SPE Annual Technology Conference and Exhibition, 23–25 September, in New Orleans.
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As AI continues to evolve, the need for energy-powered data centers is on the rise. Data center developers who can make this transition toward a more efficient and greener system will anchor themselves as key players in this growing industry.
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The industry is balancing brains and bots as it squeezes out barrels of oil production.
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Explore how data science has become essential across diverse sectors, how people can learn about data science, and how engineers can transition into this field.
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In the final part of this three-part series, we extend our learning of Part 2 to the multivariate model and train a single model to predict three outcomes: oil, gas, and water.
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In Part 2 of this three-part series, we dive into a practical example using the production data of Equinor’s Volve field data set.
