,使

Parsa Kharazi Esfahani1,2, Hadi Mahdavi Basir3, Ahmad Reza Rabbani1

  • 1Department of Petroleum Engineering, Amirkabir University of Technology (Tehran Polytechnic), 424 Hafez Avenue, Box 15875-4413, Tehran, 1591634311, Iran.

Scientific reports
|September 2, 2024
PubMed
概括

这项研究引入了先进的机器学习模型,ExtraTree和XGBoost,使用Rock-Eval热解数据准确预测玻璃矿石反射率 (VR). 与传统方法相比,这种新的方法显著提高了VR预测的准确性.