Kerogen structural model

Reuter, J. H., and Perdue, E. M. (1984). A chemical structural model of early diagenesis of sedimentary humus/proto-kerogens. Mitt. Geol.-Palaon. Inst. 56,249-262. 

As part of this investigation, kerogen pyrolysis models different from the one proposed here were considered. One such model of theoretical appeal is similar in structure to the one given in Figure 9 but with a pure diffusion process for the heavy oil production. However, this alternative model is incompatible with some experimental findings It predicts lower coke concentrations on the surface of the particle than in the interior, whereas microprobe results indicate a uniform coke distribution. Further, this diffusion model predicts zero coke yield for infinitely small particles, whereas the limited amount of data available for small particle sizes suggest a leveling-off of the coke yield below a particle size of 0.4 mm. 

The sidebands in C solid-state NMR spectra of 13 polycyclic aromatic hydrocarbon model compounds associated with kerogen structure were suppressed with C CP MAS TOSS NMR. The chemical shift values of these model compounds were obtained and were subsequently used to determine the chemical shifts of aliphatic and aromatic carbons in a series of kerogens via C CP MAS TOSS NMR. Dipolar dephasing (DD) was used to obtain the spectra of nonprotonated carbon present. ... 

These differences in pyrolysis behavior of the oil shales can be explained by structural differences in the corresponding kerogen types. The kerogens of oil shales Aleksinac, Estonia, and Korea are associated with type I, which is of predominantly paraffinic nature. Oil shale Knjazevac is associated with kerogen type HI, which is of predominantly aromatic nature. Thus the multi-step model appears to be suitable for simulating the pyrolysis of oil shales with kerogen type I, but cannot be properly adjusted for the other kerogen types. 

Recently, there have been a number of studies using computational chemistry techniques to model macromolecules of kerogens (Faulon et al. 1990), coals (Carlson 1992 Nakamura 1993 Murata et al. 1993 Faulon et al. 1994), asphaltenes (Murgich et al. 1996 Kowalewski et al. 1996 Diallo et al. 1998), wood and lignin (Faulon 1994, 1995 Faulon and Hatcher 1994), and biomarkers (Peters et al. 1996 Peters 2000). Computational chemistry models have been used to predict a variety of physical and chemical properties, such as the density of coals (Nakamura et al. 1993 Murata et al. 1993), the microporosity of coals (Faulon 1994, 1995), and the self-association of asphaltenes and resins (Murgich et al. 1996 Subramanian and Sheu 1997 Zajac et al. 1997). Oil companies and petroleum research organizations are interested in compositional and structural chemistry of these macromolecules because of its potential for solving both upstream and downstream problems. 

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