Quantitative molecular representation and sequential optimization of athabasca asphaltenes

被引:208
作者
Sheremata, JM
Gray, MR
Dettman, HD
McCaffrey, WC [1 ]
机构
[1] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G 2G6, Canada
[2] Natl Ctr Upgrading Technol, Devon, AB T0C 1E0, Canada
关键词
D O I
10.1021/ef049936+
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The chemical complexity and diversity of an Athabasca asphaltene sample was described using a series of molecular representations. The molecular representations were created with a Monte Carlo construction method that represented molecules with a series of aromatic and aliphatic groups. After the groups were randomly sampled for a molecule, a connection algorithm linked them together to form molecules consisting of aromatic groups connected by aliphatic chains and thioethers. A sequential nonlinear optimization algorithm was used to select a small subset of molecules that were consistent with elemental, molecular weight, and NMR spectroscopy (both C-13 and H-1) data. To accurately represent the analytical data for the asphaltene sample, a minimum of five molecules was needed. On the basis of the results of the sequential optimization, at least 50 molecules in the starting population were required to produce an analytically consistent molecular representation.
引用
收藏
页码:1377 / 1384
页数:8
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