Application of a Digital Oil Model to Solvent-Based Enhanced Oil Recovery of Heavy Crude Oil
Application of a Digital Oil Model to Solvent-Based Enhanced Oil Recovery of Heavy Crude Oil
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DOI:
10.1021/acs.energyfuels.9b02801
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发表时间:
2019-10
期刊:
影响因子:
5.3
通讯作者:
M. Iwase;Yunfeng Liang;Y. Masuda;Masato Morimoto;T. Matsuoka;E. Boek;Y. Kaito;K. Nakagawa
中科院分区:
文献类型:
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作者:
M. Iwase;Yunfeng Liang;Y. Masuda;Masato Morimoto;T. Matsuoka;E. Boek;Y. Kaito;K. Nakagawa
To investigate enhanced oil recovery processes, we constructed a molecular model of a live heavy crude oil (digital oil) and studied the crude oil properties at the reservoir temperature and a wide range of pressures. We identified the liquid phase components of the digital oil by flash calculation and calculated the density and viscosity by molecular dynamics simulations. The calculated density and viscosity were in good agreement with experimental data. To evaluate the effectiveness of various solvents to enhance oil recovery, we calculated the oil property changes when different solvents were added to the digital oil. First, we compared methane and carbon dioxide (CO₂). The results indicated that CO₂ was more effective in terms of oil-viscosity reduction, oil swelling, and diffusion in the oil. Second, we evaluated the effectiveness of 11 different solvents: nitrogen, CO₂, methane, ethane, propane, n-heptane, n-octane, toluene, and three xylene isomers (o-xylene, m-xylene, and p-xylene). Ethane had the greatest effect on oil-viscosity reduction and oil swelling, and CO₂ had the highest diffusion coefficient. From these results, ethane and CO₂ are appropriate solvents for this crude oil. In addition, it is interesting to note that the decreases of the viscosity among the three xylene isomers were different, but there were no differences in the swelling factors and diffusion coefficients. The different rotation motion characteristics of the xylene isomers can account for the viscosity differences. Such information will be helpful for further development of digital oil models.