Robotics & Machine Learning Daily News2024,Issue(Nov.25) :75-76.

New Data from China University of Petroleum (East China) IlluminateFindings in Machine Learning [Analytical Method Based On Machine Learning (Am-bml) for a Cased Borehole Under Anisotropic In-situ Stresses In Formation]

中国石油大学(华东)最新数据解读机器学习研究成果[基于机器学习(AM-BML)的套管井地层各向异性地应力分析方法]

Robotics & Machine Learning Daily News2024,Issue(Nov.25) :75-76.

New Data from China University of Petroleum (East China) IlluminateFindings in Machine Learning [Analytical Method Based On Machine Learning (Am-bml) for a Cased Borehole Under Anisotropic In-situ Stresses In Formation]

中国石油大学(华东)最新数据解读机器学习研究成果[基于机器学习(AM-BML)的套管井地层各向异性地应力分析方法]

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-调查人员发布马学习的新报告。根据新闻报道在中华人民共和国青岛,NewsRx编辑,研究称,"抽象这项工作,提出了一种基于机器学习(AM-BML)的应力分布预测方法在具有各向异性地应力的地层中套管钻孔周围。首先,应力场方程用弹性力学理论推导了含待定系数的应力场套管BO Rehole。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators publish new report on Ma chine Learning. According to news reportingout of Qingdao, People’s Republic of China, by NewsRx editors, research stated, “AbstractIn this work,an analytical method based on machine learning (AM-BML) is proposed to predict the stress dis tributionaround a cased borehole in the formation with anisotropic in-situ stre sses. Firstly, the stress field equationswith undetermined coefficients are der ived using the elasticity theory to formulate the stress field near thecased bo rehole.”

Key words

Qingdao/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/China University of Petrole um (East China)

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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