机译:优化神经网络估计烃储层中CO_2洪水中的最小混溶性压力
China Univ Geosci Beijing Sch Energy Resources Beijing 100083 Peoples R China|Minist Educ Key Lab Marine Reservoir Evolut & Hydrocarbon Enr Beijing Peoples R China;
China Univ Geosci Beijing Sch Energy Resources Beijing 100083 Peoples R China|Key Lab Geol Evaluat & Dev Engn Unconvent Nat Gas Beijing Peoples R China;
Sinopec Corp Res Inst Petr Explorat & Dev Shengli Oilfield Dongying Peoples R China;
Petrochina Coalbed Methane Co Ltd Beijing Peoples R China;
China Univ Geosci Beijing Sch Energy Resources Beijing 100083 Peoples R China;
China Univ Geosci Beijing Sch Energy Resources Beijing 100083 Peoples R China;
China Univ Geosci Beijing Sch Energy Resources Beijing 100083 Peoples R China;
Sinopec Corp Res Inst Petr Explorat & Dev Shengli Oilfield Dongying Peoples R China;
Enhanced oil recovery; CO(2)injection; minimum miscibility pressure; back-propagation neural network; evolutionary algorithm;
机译:使用烃类气体和CO_2从Bakken和Cut Bank Lockoir中使用烃气体和CO_2的最小混溶性压力的实验测定
机译:利用径向基函数神经网络和进化技术的混合对纯净和不纯CO_2驱油过程中的最小混溶压力建模
机译:预测CO_2驱油最小混溶压力的人工神经网络模型的开发
机译:使用CO_2可溶性表面活性剂降低油藏CO_2洪水的最小混溶性压力
机译:使用基于神经网络的代理模型优化自然裂缝储层中的循环压力脉动设计。
机译:交联聚合物驱后普通稠油油藏的优化聚合物增强泡沫驱
机译:优化神经网络估计碳氢化合物储层中二氧化碳洪水的最小混溶性压力
机译:一种优化分层油藏混相驱的新方法的实验验证