Upload
voquynh
View
222
Download
0
Embed Size (px)
Citation preview
Atomistic Modelling of Oil Shale Kerogens and Asphaltenes ���
���
Julio Facelli*, Anita Orendt, Ian Pimienta, Shyam Badu, Ronald Pugmire
31st Oil Shale Symposium
October 17 - 21, 2011
This work has been partially supported by United States Department of Energy, National Energy Technology Laboratory Award DE-FE0001243 and by and allocation of computer time at the University of Utah Center for High Performance Computing.
Goals • Use modern computational chemistry tools to:
– Obtain high fidelity 3D models for kerogens and for asphaltenes – Validate models by calculating spectroscopic properties and
comparing to actual experimental data • Use the models for further studies of behavior, including
modeling of pyrolysis and the study of the interaction with the inorganic substrates
• Use the models to test approaches to more efficiently recover the organic material from oil shale/sands
2D Models • 2D models in the literature are based on a variety of
different experimental data – Elemental analyses – NMR – Mass spectroscopy – X-ray photoelectron spectroscopy – Pyrolysis/cracking products – Chemical analyses results
• However the 2D models are not suitable for computational modeling studies
3D structures are needed to: • Confirm that the 2D models actually reproduce
experimental data on the samples they are based upon
• Determine which experimental measurements are sensitive to structural differences between models
• Explore the chemical nature of the interaction between organic material and inorganic matrix
• Explore what is happening during in situ pyrolysis
Methodology Used • Molecular mechanics (HyperChem/ReaxFF)
– For starting structures – Optimization of larger systems – Pyrolysis modeling
• Ab initio calculations (Gaussian/GAMESS) – For structure refinement – Calculation of spectroscopic properties
• Specialty packages to calculate other observables (DIFFUSE for pairwise distribution functions, CRYSOL for x-ray scattering curves)
2D Kerogen model Siskin’s 1995 2D model for a type I kerogen from a Green River oil shale
Siskin et al, in Composition, Geochemistry and Conversion of Oil Shales (NATO ASI Series C volume 455) 1995
2D models of asphaltene
Siskin’s 2006 2D models for six representative asphaltenes Siskin et al, Energy & Fuels, 2006, 20, 1227
3D Kerogen Model
• Single unit of Siskin’s 2D model after four cycles of thermal annealing and energy optimization
3D Kerogen Model
• 12 units of Siskin’s 2D model – over 20,000 atoms
Representative 3D Asphaltene models Geometry optimized paying attention to flexible linkage between aromatic and aliphatic portions
Mid-Continent US Campana
Interaction with mineral matrix
• Illite (aluminum silicate clay) used
• Still need to determine best way to explore lowest E orientation of asphaltene on clay
Calculation of Experimental Data
• 13C NMR chemical shifts • IR frequencies • Pairwise distribution functions • Small angle x-ray scattering (SAXS) • Pyrolysis products
13C NMR of kerogen
0
20
40
60
80
100
120
140
160
180
0 50 100 150
Inte
nsity
Chemical Shift
!"""!""#""$""%%&
'())*+,-.)(+/)(01)*2+3(04+50()2+!6#5 !$+5%&78
50() !
50() #
13C NMR Comparison of the spectra of the six Siskin asphaltenes
0
2
4
6
8
10
12
14
0 20 40 60 80 100 120 140 160 180 200
Inte
nsity
Chemical Shift (ppm)
Campana
HC
LW
Maya
MC
SJ
Possible Structures of Mid Continent Asphaltene
13C NMR spectra for the eight different configurations of single unit of mid continent asphaltene
obtained by simulated annealing���
Experimental from: Siskin, M.; Kelemen, S.R.; Eppig, C.P.; Brown, L.D.; Afeworki, M. Energy & Fuels, 2006, 20, 1227-1234
13C NMR spectra for the five different configurations of trimmers of mid-continent asphaltene obtained by simulated annealing
Experimental from: Siskin, M.; Kelemen, S.R.; Eppig, C.P.; Brown, L.D.; Afeworki, M. Energy & Fuels, 2006, 20, 1227-1234
13C NMR spectra for average of eight different configurations of single unit of
mid continent asphaltene obtained by simulated annealing���
-150 -100 -50 0 50 100 150 200 250 300 350
Average
exp
Experimental from: Siskin, M.; Kelemen, S.R.; Eppig, C.P.; Brown, L.D.; Afeworki, M. Energy & Fuels, 2006, 20, 1227-1234
IR Vibrational Spectroscopy
• Vibrational bands can be related of detailed information about functional groups present as they have different vibrational frequencies
• Quick and easy to obtain experimental spectra
Sensitivity of calculated IR spectrum
Campana versus Mid-Continent US
Pairwise Distribution Function (PDF) • Obtained from X-ray scattering from samples
– working with Dr. Randy Winans at the Advanced Photon Source (APS) at Argonne National Laboratory
• Provides information about the distribution of atom-atom distances
• Can predict pattern based on atomic positions from 3D model and details of shape of system
Calculated PDF showing the interatomic distance distribution for the different sized kerogen models ���
Comparison of Experimental and Calculated PDFs ������������
Darren R. Locke, Randall E. Winans, Karena W. Chapman, and Peter J. Chupas. X-ray Science Division, Advanced Photon Source, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, Illinois 60439. Use of the Advanced Photon Source was supported by the U. S. Department of Energy, Office of Science, Office of Basic Energy Sciences, under Contract No. DE-AC02-06CH11357. DRL acknowledges support by the Chevron Energy Technology Company through a contract with University of Utah.
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
2.5
3
0 2 4 6 8 10 12 14
G(r
)
Radius [Å]
Dodecamer Model
Experimental PDF
Campana Asphaltene Pyrolysis Results
0
5
10
15
20
25
30
35
0 10 20 30 40 50 60
Num
ber o
f mol
ecul
es
Time (Ps)
2000K
2250K
2500K
2750K
3000K
C41H27 C5H5 C2H5 HN O C 2C3H3 5C2H3 CH3 C2H2 C5H9 C3H4 C2H CH2O 7H 2H2
Fragments from 3000K simulation
Pyrolysis Modeling on Campana Asphaltene
NVT-MD simulation of (a) single unit, (b) parallel stack (c) anti-parallel stack and (d) inverted stack at different temperatures
Conclusions • Using modern computational tools it is possible to develop 3D
models of kerogens and asphaltenes
• Calculated spectroscopic properties show good sensitivity with respect of the models
• Calculated spectroscopic properties show overall agreement with our limited experimental information
• Even this limited comparison with experimental measurements shows need for improvement of the models