Robotics & Machine Learning Daily News2024,Issue(Mar.15) :103-104.

New Machine Learning Study Results from University of Calgary Described (Modelin g of Methane and Carbon Dioxide Sorption Capacity In Tight Reservoirs Using Mach ine Learning Techniques)

Robotics & Machine Learning Daily News2024,Issue(Mar.15) :103-104.

New Machine Learning Study Results from University of Calgary Described (Modelin g of Methane and Carbon Dioxide Sorption Capacity In Tight Reservoirs Using Mach ine Learning Techniques)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Machine Learning are discussed in a new report. According to news reporting originating in Calgar y, Canada, by NewsRx journalists, research stated, “The viability of enhanced co albed methane recovery (ECBM) and enhanced shale gas recovery (ESGR) are abundan tly explored in various studies since they present a solution for ongoing energy demand and environ-mental crisis. As a matter of challenge, the prediction of t he gas sorption profile poses a significant obstacle in the development of such resources.”

Key words

Calgary/Canada/North and Central Ameri ca/Alkanes/Anions/Carbon Dioxide/Chemicals/Cyborgs/Emerging Technologies/Inorganic Carbon Compounds/Machine Learning/Methane/Oxides/University of Cal gary

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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