Digital Transformation
The Genesis Mission is a US Department of Energy initiative that integrates AI, national labs, and cross-sector collaboration to accelerate scientific discovery, strengthen energy innovation, and enhance national security.
Agentic AI could help upstream oil and gas operations reduce emissions by enabling real-time methane detection, optimizing flaring and energy use, and improving carbon capture efficiency.
This article examines how domain experts can use no-code ML platforms to explore decision-relevant problems, validate hypotheses, quickly build prototypes, and engage more effectively with data science teams when solutions transition toward production.
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Well-interference issues can be hard to diagnose, but this startup may be figuring that out. The data-driven process it developed can also help operators come up with more effective ways to use diverters. -
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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Venture groups spend their time evaluating hundreds of companies each year to only make a handful of investments. These two cover interesting ends of the upstream spectrum: aerial drones and downhole artificial lift.
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This interview explores the opportunities, challenges, and what young professionals need to know to have a rewarding career in drilling data analytics.
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Acquiring data from an abandoned subsea well has been done before, but never quite like this.
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Microsoft deployed a datacenter underwater near Scotland’s Orkney Islands, as part of a project to assess bringing datacenters closer to population centers.
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Wearable computers are turning heads in the oil and gas industry and appear to be on a trajectory for widespread adoption.
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Data story consumers are focused on summarized results and highlights instead of details of the analysis. It’s a data scientist’s responsibility to identify the significance of the data and to present it in a simple but scientific manner.
