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Updated: May 13, 2025

Microfluidic Devices for Characterizing Pore-scale Event Processes in Porous Media for Oil Recovery Applications
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机器学习与超参数优化应用在碳酸盐油库中面积支持的透性建模中

Watheq J Al-Mudhafar1, Alqassim A Hasan2, Mohammed A Abbas3

  • 1Basrah Oil Company, Basra, Iraq. watheq.almudhafar@utexas.edu.

Scientific reports
|April 15, 2025
PubMed
概括

在碳酸盐储中准确地预测透性对于石油流动至关重要. 机器学习模型,特别是XGBoost,使用井日志有效预测透性,改进水库开发计划.

关键词:
碳酸盐储存库中的碳酸盐.面部的分类 面部的分类超参数优化超参数优化机器学习是机器学习.透度建模的模型.记录完善的数据质量记录.

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