AI/machine learning
This research focuses on combining physics-based expert rules with machine learning to improve the detection of failure-related events in electrical submersible pumps.
A combination of physics principles and machine-learning techniques is used in this work to develop a virtual flowmeter for oil-production optimization in electrical-submersible-pump-lifted oil wells, resulting in reliable generalization.
This paper presents the deployment of an artificial intelligence-enabled autonomous gas lift optimization system, integrating real-time centralized advanced process control with cloud-based analytics to enhance artificial gas lift performance in producer wells.
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The artificial intelligence technology is expected to increase understanding of subsurface structures. -
While the industry is adopting the technology, one expert highlights areas where the oil and gas sector could speed up the adoption of artificial intelligence.
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SponsoredThis Q&A highlights the benefits of AI and ML to automate work flows and analyze data at a much faster rate—within minutes. These capabilities deliver a fit-for-basin approach designed specifically for US-centric work flows.
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Highlighting news on the recent SPE Board of Directors meeting in Saudi Arabia and SPE’s utilization of artificial intelligence now and its plans for the future.
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Researchers with the Energy & Environmental Research Center highlight the key use cases ChatGPT holds today for petrotechnicals.
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ChatGPT and its derivative artificial intelligence chatbots are fulfilling the needs and satisfying the curiosity of novices and more experienced AI users. Have you gotten your feet wet or dove right in?
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For organizations that do it well, data management provides a competitive edge in an increasingly digital oil field. But teams all too often are so busy managing all the moving parts of data management that they take their eye off of “the prize”—the payoff after you have put everything into place to sustain successful data management.
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This paper details experiences gained while developing a novel technology-driven approach to risk assessment methodologies such as process hazard analysis, hazard identification, and hazard operability in oil and gas.
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SPE Data Science and Engineering Analytics Technical Director Silviu Livescu and SPE Reservoir Technical Director Rodolfo Camacho address some of the challenges in the application of data analytics, artificial intelligence, and machine learning to several reservoir engineering problems.
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The use of artificial intelligence in the clean energy sector increases the availability and accessibility of clean energy, making it a more viable and cost-effective alternative to traditional energy sources.
