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机译:基于新的集成混合神经网络和常规井测井曲线的页岩储层总有机碳含量预测
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
Yangtze Univ Key Lab Explorat Technol Oil &
Gas Resources Wuhan 430100 Hubei Peoples R China;
shale reservoir; organic carbon content; machine learning; integrated hybrid neural network; adaptive tabu compound rainforest optimizing algorithm; low TOC reservoir;
机译:基于新的集成混合神经网络和常规井测井曲线的页岩储层总有机碳含量预测
机译:极限学习机和神经网络在线测井有机页岩总有机碳含量预测中的应用
机译:神经网络测井参数总有机碳含量预测的数学建模 - 以华南地板煤气井的案例研究
机译:基于测井参数,BP神经网络建立的煤源岩中总有机碳含量的预测模型
机译:使用常规孔隙度位移和人工神经网络预测毛细管压力和相对渗透率曲线
机译:使用常规井日志和光谱伽马射线预测人工神经网络预测德文郡页岩总有机碳
机译:基于测井参数,BP神经网络建立的煤源岩中总有机碳含量的预测模型