Department of Applied Geophysics Researchers Publish New Data on Machine Learnin g (A machine learning approach for the prediction of pore pressure using well lo g data of Hikurangi Tuaheni Zone of IODP Expedition 372, New Zealand)

Robotics & Machine Learning Daily News2024，Issue(MAY.7) ：14-15.

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Department of Applied Geophysics Researchers Publish New Data on Machine Learnin g (A machine learning approach for the prediction of pore pressure using well lo g data of Hikurangi Tuaheni Zone of IODP Expedition 372, New Zealand)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on artificial intelligenc e is the subject of a new report. According to news reporting originating from J harkhand, India, by NewsRx correspondents, research stated, “Pore pressure (PP) information plays an important role in analysing the geomechanical properties of the reservoir and hydrocarbon field development. PP prediction is an essential requirement to ensure safe drilling operations and it is a fundamental input for well design, and mud weight estimation for wellbore stability.” Financial supporters for this research include Science And Engineering Research Board; Iilinois State Museum; Department of Science And Technology, Ministry of Science And Technology, India.

Key words

Department of Applied Geophysics/Jharkh and/India/Asia/Cyborgs/Emerging Technologies/Machine Learning

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2024

Robotics & Machine Learning Daily News

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