AI/machine learning
This work describes a study in which distributed data parallel training, paired with a node-local caching pipeline, enabled efficient multigraphics-processing-unit scaling for a CO₂-storage graph-neural-network surrogate while maintaining generalization.
This paper presents a novel reservoir engineering/reservoir simulation approach—a data-driven interwell-connectivity model augmented as a digital twin—to predict reservoir dynamics and optimize operations in the Changqing oil field of China.
This work uses a novel pseudosteady-state-based simulation to reduce training-data-generation cost while maintaining high-performance predictions of data-driven proxy models for carbon-sequestration projects.
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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. -
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.
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Despite streams of data being available on platforms about the condition of topside and drilling equipment, most experts agree that only a small fraction of such data is used. Whether for a fleet or single platform, AI can transform an offshore enterprise.
