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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DNV GL has published a paper to support the safe use of artificial intelligence. The paper asserts that data-driven models alone may not be sufficient to ensure safety and calls for a combination of data and causal models to mitigate risk. -
Machine learning and artificial intelligence technology offer offshore operators the chance to automate high-cost, error-prone tasks to avoid the effects of inconsistency and errors in analysis, improving efficiencies and safety.
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Technologies are being developed that have the potential to support marine mining in all stages from prospection to decommissioning. These developments will likely have substantial influence in the oil and gas industry, itself searching for ways to maximize exploitation of assets.
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Hundreds of rod-lift wells in North Dakota are about to get a big upgrade.
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A recent research effort has shown that the digital journey is full of stumbling blocks. Just like humans, advanced computing technology will get some things right and some things wrong.
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The company behind the world’s most popular search engine is trying to click with the upstream business at the most distinguished technical event of the year.
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The perceived change stemming from the spread of machine learning and artificial intelligence can feed alarming predictions about massive job losses, but replacement of humans is a low priority among organizations implementing these technologies.
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Total is expanding its development and use of artificial intelligence to bolster its exploration work, collaborating with Google Cloud—which is stepping up its presence in the oil and gas industry.
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The goal of cognitive computing is not to eliminate humans but allow highly skilled professionals to spend time doing what’s most valuable for the company.
