AI/machine learning
Speakers at ATCE said innovative technologies will play a critical role in balancing energy security, affordability, and sustainability in the years ahead.
Known as Arena, the collaboration aims to improve decision-making across increasingly complex reservoirs and growing volumes of subsurface data.
Robotic and autonomous systems are transforming energy operations, but their full value emerges only when paired with data science, engineering analytics, and AI/ML to turn data into decisions. The transition of the SPE Robotic & Autonomous Systems Technical Section into the SPE Data Science & Engineering Analytics Technical Section helps bridge this critical technolo…
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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. -
A study of 25 years of artificial-intelligence research suggests the era of deep learning may come to an end.
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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.
