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    Predicting Viscosities of Heavy Oils and Solvent–Heavy Oil Mixtures Using Artificial Neural Networks 

    Source: Journal of Energy Resources Technology:;2021:;volume( 143 ):;issue: 011:;page 0113001-1
    Author(s): Chen, Zehua; Yang, Daoyong
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This study investigates the potential of artificial neural networks (ANNs) to accurately predict viscosities of heavy oils (HOs) as well as mixtures of solvents and heavy oils (S–HOs). The study uses experimental data ...
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    Correlations of Equilibrium Interfacial Tension Based on Mutual Solubility/Density: Extension to n-Alkane–Water and n-Alkane–CO2 Binary/Ternary Systems and Comparisons With the Parachor Model 

    Source: Journal of Energy Resources Technology:;2019:;volume 141:;issue 012:;page 122901
    Author(s): Chen, Zehua; Yang, Daoyong
    Publisher: American Society of Mechanical Engineers (ASME)
    Abstract: In this study, new and pragmatic interfacial tension (IFT) correlations for n-alkane–water and n-alkane–CO2 systems are developed based on the mutual solubility of the corresponding binary systems and/or density in a ...
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    A New Low-Damage Drilling Fluid for Sandstone Reservoirs With Low-Permeability: Formulation, Evaluation, and Applications 

    Source: Journal of Energy Resources Technology:;2020:;volume( 143 ):;issue: 005:;page 053004-1
    Author(s): Wang, Chengwen; Wang, Yanji; Kuru, Ergun; Chen, Erding; Xiao, Fengfeng; Chen, Zehua; Yang, Daoyong
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Drilling-induced formation damage is the key factor dominating the failure of the development of hydrocarbon reservoirs with low-permeability (i.e., tight formation). In this paper, a new low-damage drilling fluid was ...
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