Data & Analytics
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.
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.
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. -
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.
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In Part 1 of this three-part series, we use long short-term memory (LSTM), a machine learning technique, to predict oil, gas, and water production using real field data.
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Register today for the SPE AI Hackathon taking place 7–9 May in Dubai.
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The Unmanned Technical Section has updated its name to the Robotics and Autonomous Systems Technical Section.
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The oil and gas industry’s sustainability and success depend on its ability to cultivate and nurture a skilled and knowledgeable workforce.
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This article provides a mirror between the past and the present of well intervention technologies, including R&D to advance to downhole robots and autonomous intervention methods.
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Registration is open for the SPE Europe Energy GeoHackathon, which will be held in October and November. It will be preceded by 4-week online bootcamp sessions on data science and geothermal energy, which will begin on 2 October.
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Explore the challenges associated with fiber-optics data analysis and how recent advances in technology can be leveraged to maximize the value of the data.
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