AI/machine learning
Aurora Innovation and Detmar Logistics have inked a deal for 30 autonomous trucks that will begin hauling sand in the region next year.
Sustainability in reservoir management emerges not from standalone initiatives but from integrated, data-driven workflows, where shared models, closed-loop processes, and AI-enabled insights reduce fragmentation and make sustainable performance a natural outcome.
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In oil and gas operations, every decision counts. For more than 2 decades, SiteCom has been the trusted digital backbone for well operations worldwide, driving insight, collaboration, and efficiency.
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A study of 25 years of artificial-intelligence research suggests the era of deep learning may come to an end. -
In 2015, the United Nations ratified the 2030 Sustainable Development Goals. Technology will be critical in the pursuit of these ambitious targets, but the pace and scale of change creates risks that humanity must take very seriously.
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Leading corporations seem to be failing in their efforts to become data-driven. This is a central and alarming finding of NewVantage Partners’ 2019 Big Data and AI Executive Survey.
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BP Ventures has invested $5 million in Belmont Technology’s Series A financing to further bolster BP’s artificial intelligence and digital capabilities in its upstream business.
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The technology is being proven in millions of phones and homes across the world. Now, a small group of software startups wants to introduce chat bot technology to oil and gas professionals.
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Royal Dutch Shell is heavily investing in research and development of artificial intelligence, which it hopes will provide solutions to some of its most pressing challenges.
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Artificial intelligence has come to the oil patch, accelerating a technical change that is transforming the conditions for the oil and gas industry’s 150,000 US workers.
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Researchers borrowed equations from calculus to redesign the core machinery of deep learning so it can model continuous processes like changes in health.
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An increasingly buzzy term tossed around at industry events, “digital twin” is leveraging data analytics, machine learning, and artificial intelligence to improve efficiencies from design to decommissioning.
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As shale plays are becoming economically viable, operators have fast-adopted best practices to optimize drilling and completion processes to drive down the lifting costs. Adoption of data-driven analytics to improve completion design, drive efficiency, and yield economic gains has been less swift.
