Investigators from Egyptian Petroleum Research Institute Report New Data on Mach ine Learning (Improving Permeability Prediction Via Machine Learning In a Hetero geneous Carbonate Reservoir: Application To Middle Miocene Nullipore, Ras Fanar ...)

Robotics & Machine Learning Daily News2024，Issue(MAY.8) ：46-47.

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Investigators from Egyptian Petroleum Research Institute Report New Data on Mach ine Learning (Improving Permeability Prediction Via Machine Learning In a Hetero geneous Carbonate Reservoir: Application To Middle Miocene Nullipore, Ras Fanar ...)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting originating in Cairo, Egypt, by News Rx journalists, research stated, “Predicting and interpolating the permeability between wells to obtain the 3D distribution is a challenging mission in reservoi r simulation. The high degree of heterogeneity and diagenesis in the Nullipore c arbonate reservoir provide a significant obstacle to accurate prediction.” Financial support for this research came from Egyptian Petroleum Research Instit ute (EPRI).

Key words

Cairo/Egypt/Africa/Alkalies/Anions/Carbonates/Carbonic Acid/Cyborgs/Emerging Technologies/Machine Learning/Egy ptian Petroleum Research Institute

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出版年

2024

Robotics & Machine Learning Daily News

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