Robotics & Machine Learning Daily News2024,Issue(Jun.7) :58-59.

King Fahd University of Petroleum and Minerals Researcher Highlights Recent Rese arch in Machine Learning (Improving Water- Based Drilling Mud Performance Using B iopolymer Gum: Integrating Experimental and Machine Learning Techniques)

法赫德国王石油和矿物大学的研究员重点介绍了机器学习的最新研究(使用B iopolymer胶改善水基钻井泥浆性能:综合实验和机器学习技术)

Robotics & Machine Learning Daily News2024,Issue(Jun.7) :58-59.

King Fahd University of Petroleum and Minerals Researcher Highlights Recent Rese arch in Machine Learning (Improving Water- Based Drilling Mud Performance Using B iopolymer Gum: Integrating Experimental and Machine Learning Techniques)

法赫德国王石油和矿物大学的研究员重点介绍了机器学习的最新研究(使用B iopolymer胶改善水基钻井泥浆性能:综合实验和机器学习技术)

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摘要

由机器人与机器学习每日新闻的新闻记者兼新闻编辑-研究人员详细介绍了人工智能的新数据。根据来自沙特阿拉伯宰赫兰的Newsrx编辑的消息,这项研究称,“由于井眼的不稳定性,在页岩地层中钻探可能费时费力。此外,还需要开发环保的抑制剂。”我们的新闻记者从法赫德国王石油和矿物大学的研究中获得了一句话:“我们的研究发现了使用阿拉伯胶(ArG)解决这一问题的成本效益高的方法。我们通过线性溶胀试验、毛细管抽吸计时器试验和Zeta Poten Tial,流体损失,评估了rG粘土膨胀抑制剂和流体损失控制器在水基泥浆(WBM)中的抑制潜力。”结果表明,当ArG浓度为1.0wt.%时,膨润土(Na-Ben)的线膨胀率明显降低,达36.1%(ArG浓度为1.0wt.%),毛细管吸水时间也随ArG浓度的增加而增加。在钻井液中加入ArG能显著降低钻井液的失水率达50%以上,降低了基泥浆的剪切应力,表现出良好的缓蚀减摩作用,说明ArG是一种很好的绿色防膨降滤失剂。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in artific ial intelligence. According to news originating from Dhahran, Saudi Arabia, by N ewsRx editors, the research stated, “Drilling through shale formations can be ex pensive and time-consuming due to the instability of the wellbore. Further, ther e is a need to develop inhibitors that are environmentally friendly.” Our news reporters obtained a quote from the research from King Fahd University of Petroleum and Minerals: “Our study discovered a cost-effective solution to th is problem using Gum Arabic (ArG). We evaluated the inhibition potential of an A rG clay swelling inhibitor and fluid loss controller in water-based mud (WBM) by conducting a linear swelling test, capillary suction timer test, and zeta poten tial, fluid loss, and rheology tests. Our results displayed a significant reduct ion in linear swelling of bentonite clay (Na-Ben) by up to 36.1% a t a concentration of 1.0 wt. % ArG. The capillary suction timer (C ST) showed that capillary suction time also increased with the increase in the c oncentration of ArG, which indicates the fluid-loss-controlling potential of ArG . Adding ArG to the drilling mud prominently decreased fluid loss by up to 50% . Further, ArG reduced the shear stresses of the base mud, showing its inhibitio n and friction-reducing effect. These findings suggest that ArG is a strong cand idate for an alternate green swelling inhibitor and fluid loss controller in WBM .”

Key words

King Fahd University of Petroleum and Mi nerals/Dhahran/Saudi Arabia/Asia/Cyborgs/Emerging Technologies/Machine Lea rning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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