AI/machine learning
Reaching further than dashboards and data lakes, the agentic oil field envisions artificial intelligence systems that reason, act, and optimize.
This paper introduces an agentic artificial-intelligence framework designed for offshore production surveillance and intervention.
In the past year, publications on CO2, natural gas, and hydrogen storage have increasingly focused on the design, evaluation, and optimization of storage plans. These efforts encompass a broad spectrum of challenges and innovations, including the expansion of storage reservoirs from depleted gas fields and saline aquifers to stratified carbonate formations and heavy-o…
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The 5-year effort will take advantage of Microsoft technologies in machine learning, augmented reality, user interactions, and the industrial Internet of things to deliver integrated solutions to the upstream industry. -
This policy brief explores the key issues in attempting to improve cybersecurity and safety for artificial intelligence as well as roles for policymakers in helping address these challenges.
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Research shows how to understand the role of individual neurons in a neural network.
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Like biological brains, artificial neural networks may depend on slow-wave sleep for learning.
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With their gee-whiz—albeit artificial—intelligence, robots may be the industry’s answer to jobs deemed dangerous, dirty, distant, or dull.
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Machine learning enables fast, cost-effective, and accurate methane emissions detection in remote areas.
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Artificial intelligence just seems to get smarter and smarter. But some of the improvement comes from tweaks rather than the core innovations their inventors claim—and some of the gains may not exist at all, says Davis Blalock, a computer science graduate student at MIT.
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The Offshore Technology Conference was cancelled for the first time ever due to the COVID-19 pandemic. But the flow of ideas continues. As proof, this curated summary of technical papers highlights unique concepts that might someday reduce the offshore sector’s heavy cost burdens.
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The Internet giant is walking away from the exploraiton and production business following a report that claimed it was undermining its own climate initiatives by offering its machine-learning tools.
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The AI-driven tool will detect anomalies in subsea oil and gas infrastructure.
