Atomistic Modelling of Oil Shale Kerogens and...

Atomistic Modelling of Oil Shale Kerogens and Asphaltenes ���

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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

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Chemical Shift

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13C NMR Comparison of the spectra of the six Siskin asphaltenes

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Campana

HC

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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���

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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.

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Experimental PDF

Campana Asphaltene Pyrolysis Results

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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