Data & Analytics
The emerging vision is an industry where engineers focus on judgment, risk assessments, and accountability.
This paper presents the large-scale deployment and operational integration of an advanced, automated rheometer in the Ghawar gas field, one of the world’s most prolific and technically complex hydrocarbon developments.
This study demonstrates the transformative potential of physics-informed neural networks as a hybrid framework for multiphase flow measurement.
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Premier Corex and Teverra will be combining their efforts to aggregate data for companies involved in large-scale geothermal projects. -
The artificial intelligence technology is expected to increase understanding of subsurface structures.
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The collaboration expects to redefine methane detection and contribute to emission-reduction efforts across dozens of industries, including energy, agriculture, manufacturing, and transportation.
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This article presents a deep-learning approach, the long short-term memory network, for adaptive hydrocarbon production forecasting that takes historical operational and production information as input sequences to predict oil production as a function of operational plans.
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The authors of this paper describe a continuous monitoring system based on the Internet of Things (IoT) to use methane-concentration sensors permanently installed at facilities and connected to a cloud-based interpretation platform.
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The Robotic Supervision System project is expected to bring autonomous cooperation a step closer for oil and gas operators.
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Ocean services provider DeepOcean has mobilized its first autonomous inspection drone and plans to conduct offshore trials for an operator on the Norwegian continental shelf.
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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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This paper proposes a series of work flows to simplify model deployment and set up an automatic advisory system to provide insight in justifying an engineer’s day-to-day engineering decisions.
