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Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City, Utah Pankaj Tiwari Jacob Bauman Milind Deo October, 19 th , 2011 1 http://from50000feet.wordpress.com
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Page 1: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Mathematical Modeling of Oil Shale Pyrolysis

Department of Chemical Engineering University of Utah, Salt Lake City, Utah

Pankaj Tiwari Jacob Bauman

Milind Deo

October, 19th , 2011

1 http://from50000feet.wordpress.com

Page 2: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Oil shale thermal treatment-Pyrolysis

2

Page 3: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Background

3

Research phase More than 80 years worldwide More than 40 years at LLNL (USA)

Key points Experimental studies

•Source material dependent

•System dependent

•Different results – Mechanism, kinetic and product distribution

•Formulation of heat and mass transfer effects

•Multiscale modeling

•Coupled physical and chemical phenomena

Modeling studies

Page 4: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Oil shale pyrolysis

Several Interrelated Physical and Chemical Phenomena

Heat transfer

Chemical reaction kinetics

Multiphase flow

Phase changes

Mineral alteration and interaction

Physical properties changes

4

Page 5: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

5

Heating the surface

Oil shale pyrolysis process Experimental approach

Sweep gas

Simplified modeling approach

Variation in r direction only

Page 6: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

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Modeling of pyrolysis process

Shrinking core model Grain model

Single particle decomposition

Oil shale pyrolysis

Grain Model Particle-mesh size – TGA experiments

BC’s: Isothermal Nonisothermal

Page 7: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Modeling and simulation approach

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Heat Transfer Model (Shape and size)

Kinetic Model (Distributed reactivity)

Mass Transfer Model (Secondary reactions)

Thermodynamic Model (Distribution/lumping)

Properties of products

Heat capacity Equilibrium constant Density, etc.

Temperature distribution

Product distribution

Concentration profile

Product distribution

Quality and Yield

Operating conditions

Temperature Heating rate Pressure properties

Parameters

Raw material properties

Residence time distribution

Time-temperature history Pressure Porosity and permeability

Convection heat

Sweep/reactive gas

Model for oil shale thermal treatment

Changes in the physical properties

COMSOL Multiphysics

Page 8: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

COMSOL Multiphysics

• COMSOL Multiphysics - finite element analysis and solver

software package for physics and engineering applications

• The main advantage of COMSOL is its ability to solve

coupled phenomena

• Many built-in modules including Chemical Reaction, Earth

Science, Acoustics, Heat transfer, etc.

• COMSOL also has a model library

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Page 9: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

COMSOL Multiphysics Heat transfer module

Kinetic models

Three different kinetic models

Secondary reaction, coking and cracking

Darcy’s law - single phase flow

Transport of species module - mass based

Coupled governing equations Solved simultaneously

Appropriate changes in the physical properties

Mathematical model

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Page 10: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

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Governing equations

–ρ = overall density –Cp = heat capacity –k = thermal conductivity

–Q = Heat source/sink (heat absorbed by reactions)

•ci = Mass/concentration of i •DAB = diffusion coefficient =10-50

•ri = reaction rate •u = velocity vector

•Species transfer equation –Diffusion, convection and reaction term

•Heat transfer equation – Conduction and convection

•Rate equations

Kerogen decomposition rate,[kg or mol/(m3.s)]

Heat of reaction = - 370kJ/kg (Camp W.D., LLNL)

0

TuCpQTktTCp

iiiABi curcDtc

0

Page 11: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

11 [Campbell et al., In -Situ (1978)

Physical properties- raw material

- rho_org = density of organic = 1050 [kg/m^3] - rho_shale = density of rock = 2700 [kg/m^3] - org = organic content = 0.18 wt% [unit less]

• Heat capacity of the raw material- function of oil yield and temperature = [ J/(kg*K)]

• Thermal conductivity of the raw material –function of oil yield and temperature = [W/(m*K)]

• Density of the raw material- function of organic contain (org) = [kg/m^3]

Heat equation • Grade -30gal/ton

• 18% organic matter

Page 12: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

12

Kerogen decomposition kinetic

• Oil shale pyrolysis- TGA

Kinetic Parameters of Kerogen Decomposition

Activation energy,- E

Pre-exponential factor -A

Seven heating rates – 0.5oC/min to 50C/min [100 interval]

0.E+00

1.E+14

2.E+14

3.E+14

4.E+14

5.E+14

6.E+14

7.E+14

8.E+14

9.E+14

1.E+15

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

A.f(α

), 1/s

Extent of conversion

Distribution of A.f(α)

0

50

100

150

200

250

300

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Activ

ation

energ

y, kJ/m

ol

Extent of conversion

Distribution of activation energy

Tiwari and Deo, AIChE Journal (2011)

Weight loss Conversion Kinetic model

Page 13: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Reaction mechanism

Single step mechanism

Kerogen a* Oil + b * Gas + c * Coke a : 63 b: 24 c: 13

Aa , Ea

Two step mechanism

Kerogen a* Oil + b * Gas + c * Coke a : 63 b: 24 c: 13 e: 80 f: 20

Aa , Ea

Oil d* Gas + e* Coke A , E

Multistep mechanism • Kerogen

decomposition • Oil phase reaction • Gas phase reaction • Char decomposition

Oil Shale

Kerogen

Liquid

Gas

Solid

Oil

Non-condesable Methane Char and Coke

Heavy oil Light oil

Products

[Campbell-1978]

13

Page 14: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

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Reactions- Pyrolysis Reaction Networks

1. Kerogen ----> a1*HO + a2*LO + a3*Gas + a4*Char +a5*CH4

2. HO ----> b1*LO + b2*Gas + b3*Char + b4*CH4

3. LO ----> c3*Gas + c4*Char + c5*CH4

4. Gas ----> d4*Char + d5*CH4

5. Char ----> e3* Gas + e5*CH4 + e6*Coke

Stoichiometric coefficients- Mole or mass

Component KEROGEN HO LO GAS CHAR METHANE COKE

C 1479.000 31.751 11.189 3.354 1.004 1.000 1.185

H 2220.000 42.818 17.510 11.634 0.546 4.000 0.316

Ratio 1.501 1.349 1.565 3.468 0.544 4.000 0.267

MW 20000.550 424.492 152.034 52.011 12.604 16.042 14.552

Reaction scheme adopted from various sources –[Burnham and Braun] Bauman and Deo Energy & Fuels (2011)

[Aa , Ea]

Page 15: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results TGA Scheme- Single particle

Isothermal-400C Noniosthermal-10C/min Single Step Mechanism

K O + G+ C

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Page 16: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results TGA Scheme- Single particle

Isothermal-400C Noniosthermal-10C/min

Two Step Mechanism

K O + G+ C OG +C

16

Page 17: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results

Isothermal-400C Noniosthermal-10C/min

Multi Step Mechanism

TGA Scheme- Single particle

17

Page 18: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results

Isothermal-400C Noniosthermal-10C/min

Multi Step Mechanism

TGA Scheme- Single particle

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Page 19: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Heat application- Two cases

Surface heating Lab scale experiments

Center heating Reservoir thermal treatment

Surface heating- Products travel from cold to hot zone- fast secondary reactions Center heating- Products hit low temperature/pressure – condensation

1cm radius

Kinetic conversion- Combined isothermal and non-isothermal history 19

Page 20: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results- No flow

Core sample -10[cm] radius

Isothermal-400C Noniosthermal-10C/min Multistep Mechanism

Surface heating

20

Page 21: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Core sample -10[cm] radius

Isothermal-400C Noniosthermal-10C/min Multistep Mechanism

Results- No flow and no convection

Surface heating

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Page 22: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Core sample -10[cm] radius

Isothermal-400C Noniosthermal-10C/min

Multistep Mechanism

Results- No flow and no convection

Surface heating

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Page 23: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Core sample -10[cm] radius

Isothermal-400C Noniosthermal-10C/min

Multistep Mechanism

Results- No flow and no convection

Surface heating

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Page 24: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Products flow

ε = 0.003+(0.0146+0.0129 ∙(Grade_OS∙xK)-0.000046 ∙(Grade_OS ∙xK)2)

Porosity of oil shale

K = Dp2 ∙ ε 3/(150 ∙(1- ε)2)

Permeability of oil shale [Kozney –Carman]

Average pore diameter

Dp = 50e-6 [m]

Velocity field is determined by the pressure gradient, the fluid viscosity, and the structure of the porous medium

Continuity equation

Darcy flow

Baughman Gary L. [1978]

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Page 25: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results- Darcy’s law Surface heating Core sample -10[cm] radius Multistep Mechanism With Convection

Velocity profile Pressure profile

Isothermal-400C

Nonisothermal-10C/min

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Page 26: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Results- Effect of convection Surface heating Core sample -10[cm] radius Multistep Mechanism Surface point

Reaction rates of product

No convection With convection

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Page 27: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Core sample -10[cm] radius Flux from Boundary- Average Isothermal-400C

Results- Comparison of the two different heating options

Center heating- isothermal-400C Surface heating- isothermal-400C

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Page 28: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Summary

• Local thermodynamics of the phase changes may alter the product distribution.

• Mineral reactions can be important to generate the gas pressure, may also

participate in the reaction network.

• The development of the comprehensive model will depend on Literature.

• Heterogeneity of raw material is crucial.

• Other physical process -Expansion and fractures.

• Reliable mechanism of product formation is required.

• Kinetics play an important role in product distribution/formation.

• Secondary reactions regulate the final products.

• Study of time-temperature is important to optimize the desired products.

• Many assumptions.

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Page 29: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Department of Energy [DOE] – Financial support

Member of Institute for Clean and Secure Energy [ICSE]

Member of Petroleum Research Center [PERC]

COMSOL Multiphysics- Academic License

Acknowledgement

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Page 30: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

Literature • Mathematical modeling of In-situ oil shale retorting(George and

Harris 1977) • Pyrolysis kinetics for oil Shale particles(Granoff and Nuttall 1977) • PMOD: A flexible model of oil and gas generation, cracking and

expulsion(Braun and Burnham 1991) • Mathematical model of oil generation, degradation, and

expulsion(Braun and Burnham 1990) • Efficient formulation of heat and mass transfer in oil shale retort

models(Parker and Zhang 2006). Heat Conduction Modeling Tools for Screening In Situ Oil Shale Conversion Processes(Symington and SPiecker 2008)

• Practical kinetic modeling of petroleum generation and expulsion(Stainforth 2009)

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Page 31: Mathematical Modeling of Oil Shale Pyrolysis · 2012-05-18 · Mathematical Modeling of Oil Shale Pyrolysis Department of Chemical Engineering University of Utah, Salt Lake City,

0.01K/min – profiles- Surface heating

10cm

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