Kinetic and reaction engineering model for thermal solution of oil shale in FCC decant oil

Chemical Engineering Sciencr, Printed in Great Britain.

OOIY%2509/86 $3.00+ 0.00 Q 19S6.Pergamon PressLtd.

Vol.41.No. 4. pp. 1005-1011.1986.

FOR

KINETIC AND REACTION ENGINEERING MODEL THERMAL SOLUTION OF OIL SHALE IN FCC DECANT

John

F.

Gary

Gulf

William

Patzer II, L. Jones,

A.

Bruce

OIL

G. Moon King

Research & Development Company P-0. Drawer 2038 Pittsburgh, PA 15230

ABSTRACT

Fundamental reaction kinetics and reaction stoichiometry are developed for the-l solution of oil continuous stirred-tank reactor a once-through, shale based upon analysis of data from 67 runs on (CSTR) bench-scale unit using FCC decant oil as the solution medium. A material-balanced model of optimization theory to derive estimates of the used in conjunction with nonlinear the CSTR is Reactions occur in the liquid phase and are kinetics parameters and stoichiometric coefficients. thermal conversion of kerogsA to form heavy oil and cracking of the liquid of two basic types: The reaction paths, described in oils to form lower boiling oils, gases, and residue, i-e., coke. series oil, involve a cascading terms of pseudocomponents which lump narrow boiling range cuts of cut undergo first-order cracking to form in each boiling range of reactions in which components Each reaction rate is expressed in terms of the classical components in lower boiling ranges. concentration of the pseudocomponent boiling Arrhenius temperature dependence multiplied by the The kerogen decomposition Concentration dependence is first-order for all psuedocomponents. cut. Model rate parameters are comparable to literature values for conventional pyrolysis approaches. agree well with the experimental and product yield structure predictions for kerogen conversion data.

KEYWORDS Material-balanced solution of oil

kinetics; shale.

kinetics

modeling;

nonlinear

parameter

estimation;

oil

shale;

thermal

INTRODUCTION Conventional oil shale processing is based upon the thermal conversion of kerogen to oil products, gases and residue. Traditionally, the research focus has been upon pyrolysis of kerogen to vapor products followed by condensation of the vapor. Lewis, Braun, and Diaz (1984) provide an excellent review of such processes and the interrelationships between them. The major drawback to such processes is that the severe thermal conditions tend to overcrack the kerogen resource to form gases and residue at the expense of more valuable liquid oil products. A less researched approach, which seeks to increase the conversion of kerogen to liquid oil products, is that of thermal solution. In this approach, oil shale is slurried within a liquid medium prior to thermal conversion. The approach generally uses less severe thermal conditions than conventional pyrolysis, thus avoiding excess cracking to gases and residue. Jensen, Barnet, and Murphy (1953) provide a good, early investigation into the approach. found that, while They kerogen conversion and net oil production were high, problems existed with severe cracking of the pyrolysis-derived shale oil which they were using as the thermal solution medium. Other workers (Kafesjian and Tyler, 1984; Baldwin and co-workers, 1983) have explored other solution media, such as hydrogen donor systems, and still others (Curunins and Robinson, 1978; McKay, Chong, and Gardner, 1983) have investigated supercritical extraction techniques. However, as yet, no one has developed a kinetic reaction engineering description of a thermal solution approach in sufficient detail to quantitatively determine the extent of solution medium cracking. The present work seeks to develop the methodology and preliminary reaction engineering description of thermal solution in FCC decant oil in sufficient detail that regimes of maximum kerogen conversion to liquid products and the resultant product distribution, including that from solution medium cracking, can be predicted.

EXPERIMENTAL Conversion structure

unitA continuous-flow, data as a function of the

bench-scale, controllable

slurry processing unit operating parameters:

1005

was used to develop yield conversion temperature,

J.

1006

F. PATZER, ITetal.

I-5

organic content reactor pressure, shale concentration in the slurry. space velocity, and boiling point distribution The range of experimental of the FCC decant oil. provided in Table 1. A block schematic diagram of the unit is shown in Fig- 1. TABLE

1

Reactor

Conditions,

Pseudoccxnoonents,

Reaction Parameters Temperature, C Space velocity, kg/m3/s Pressure, MPa Wt% shale in slurry Shale grade, wt% kerogen

By-product

Cl gases

(H2S,

CO,

CO21

Naphtha (IBP-200 C) Middle distillate (200-350 Gas oil (350-450 C) Heavy oil (450+ C) Kerogen Insoluble organic matter Water Mineral matter

OIL SHALE G

C)

Eoxrimental

Error

Rancle - 462 394 0.3 3.2 3.5 4.9 50.0 60.0 13.2 22.4 Feed

Pseudoccanponent Hvdrocen _ _ Cl-C4 gases

and

of the shale, conditions is

Range, wt.% 0 0

BY

0

N MB Go HO K IOM H20 MIN

2.1 19.1 2.8 9.0

0 7.8 - 33.6 - 18.8 - 16.3

2.2 36.7

3.6 - 49.8

Prod. Exp. Error, (+/-) 95% Limits, w-t% 40.1 0.1
DECANT

OIL c

BATCH SLURRY -~ MAKEUP

1

FEED TANK

HIGH P =- PREHEATER =. CHARGE PUMP

4 HIGH PRESSURE SLURRY

PRESSURE LETDOWN

1

2 -

SLURRY PRODUCT 1.

Block

schematic

CSTR = REACTOR I

SEPARATORS

=* 3 -

ia OIL

HEAVY

Fig.

t

I

GAS

PRESSURE LETDOWN

OIL/ WATER diagram

of thermal

ATMOS. PRESSURE CONDENSERS

GASES

Ok/ WATER solution

experimental

unit.

transferred to the unit feed tank. Green River oil Batches of slurry were prepared off-line and shale was ground to finer than 0.297 am diameter (-50 mesh) prior to blending in the slurry. The preheater, which was pressure feed pump into the slurry slurry was metered through a high 399 C outlet temperature. The preheated slurry entered a continuous typically maintained at stirred-tan:< reactor (CSTR) vessel which was maintained at the specified run temperature. Agitation within the vessel was maintained rotating between 1200 by a specially designed stirrer Several CSTR vessels of varying volumes were used in order to provide a wide range and 1500 qxn. available vessel of nominal space velocities. throughput divided by volume The slurry the provides the nominal space velocity. From

the reactor, a series of separators and product collection vessels. The the slurry went to first high pressure separator, separated the solids-containing slurry from maintained at 366 C, the vaporous overheads. The second high pressure separator, maintained at 302 C, condensed gas oil range materials. The third high pressure separator, maintained at 110 C, condensed distillate

Thermal

I-5

solution

of oil shale

After passing through a range materials. pressure reduction from the gas stream in a series of water vapors were removed regularly analyzed by on-stream gas noncondensible vapors were balances for the unit were typically in the range of 95 to 100%. 10-h Standard experimental procedure was a followed by three Z-h on-stream conditions, experimental data base.

off-stream periods.

1007

valve, the remaining condensible and wet ice traps. The final, chromatography. On-stream mass

period to approach steady-state, lined-out mass-balanced runs comprise the Sixty-seven

the reactor were grouped in terms of The inputs and outputs from Analytical methodologv. as part of the kerogen feed to the Table 1. Bit-n was treated pseudcccgnponents as shown in products of the reaction. Insoluble The gases, HZ, Cl and BY, and the naphtha, N, were reactor. organic matter, IOM, which is defined as toluene-insoluble organic matter associated with effluent shale mineral matter, is comprised of both unconverted kerogen and any residual coke formed by the IOM was not done, the conversion reaction. Although separate determination of the componenets of them. The water product from the able to distinguish between kinetic analysis which follows is the water is constant and relatable to mineral content. Thus, reactor was fairly the shale considered as part of the mineral matter and not a product of kerogen conversion. Product off-gas compositions were determined by on-line gas chromatography. product liquid distributions were determined through distillation of the various fractions obtained from the separators. The IOM associated with the output was determined through toluene mineral matter extraction of the mineral matter followed by analysis for total carbon content and mineral carbon content. The IOM carbon content was then the difference between the two carbon contents. Experimental Error. The experimental experimental error determinations are confidence limits in the wt% of reactor KINETIC

MODEL

data made. output

base contained six replicate runs are given in Table 1 The results for a given component.

from which as +/95%

DEVELCPMENT

Postulated reaction network. A postulated reaction upon irreversible, network, based thermal is illustrated in Fig. 2. cracking reactions, The reaction network proposes that higher molecular the slurry phase weight pseudocomponents in undergo thermal cracking to lower molecular weight pseudocomponents, gases, and coke. Distillation is used as a surrogate measurement for molecular Only components in the slurry phase can undergo such cracking: we assume weight. that gas phase components exit the reactor immediately upon formation and, thus, do not have time to react to any ASPEN simulation (ASPEN Project, 1978) of the reactor indicates that the substantial degree. slurry phase is comprised of middle distillate, gas oil, heavy oil, IOM (kerogen and coke), and minerals under the typical reactor conditions studied. A further postulate of the reaction network is that the by-product gases, are produced primarily from the decomposition of kerogen to soluble products and secondarily from cracking of the heavy oil fraction. Kerogen is thus postulated to decompose to heavy oil, gas oil, middle distillate, light gases, hydrogen, by-product gases naphtha, and coke. The cascade to lower molecular weight for heavy products is similar oil, gas oil and middle distillate. The naphtha, light gases, and by-product gases are in the gas phase and do not react hydrogen, further. Coke is a residual product from cracking and, also, does not react further. Preliminary statistical analysis of between either reactor pressure or kerogen decomposition or cracking of about either contain any postulates matter.

the data to show base failed any significant correlation concentration matter in the slurry and of mineral either the other components. Thus, the reaction network does not pressure or the possible catalytic nature of the mineral

The postulated reaction network ignores the potential of condensation reactions, e.g., two gas oil moieties combining to form a heavy oil moiety. such reactions Although are possible in free radical mechanism reactions, such as the proposed thermal cracking mechanism, we do not have a data base appropriate for distinguishing such reactions. For that reason and because we believe that the forward cracking rate will be much greater than the reverse condensation rate, only the forward cracking reactions are considered. The such an "goodness" of assumption needs to be tested against the resulting model fit to the data base. In sunmary, the salient features of the postulated reaction network are fourfold: (1) higher molecular weight components thermally crack to lower molecular weight componentsand min;trai;) the slurry phase is comprised of middle distillate, oil, heavy oil, IOM, only i gas (3) components of the slurry phase thermally crack; the by-product gases are produced and (4) primarily from decomposition of kercgen and secondarily from cracking of heavy oil. Mass-balanced stoichiometry. A mass-balanced, stoichiometric kinetic reaction model for the proposed reaction network can be developed through appropriate analysis of the data base. The salient feature of such a model is that, for any given reactant, the mass of reactant which undergoes reaction must be exactly equal to the mass in appearance of the products from that reactant. In conventional stoichicanetric notation, using the pseudocomponent abbrwiations of Table 1, this requirement becomes:

1008

J. F. PATZER,

Fig.

HO

fCO HOSC+eMD+fN

-

GO-

f$+

Mo-

fN MD N + f%

above

equations,

for reactant coefficients

MD

fHO HO + fF K

Kd

In the

soluticm

Thermal

2.

=

1,

+ fs

the

N + fg

for

i = K, HO,

CO,

= TFi

+

(-ri)

for

r

pi =F

Fi = 1

for

= -Aj

exp

BY + fFM

BY + fgM

IOM

(1)

IOM

(2)

IOM

(3) (4)

fraction

stoichiometric

requires

CC,

MD,

that

the

conversion sum

of the

coefficients stoichiometric

CO,

ND,

rate

+x

analysis of a CSTR is a straightforward for the pseudocomponents of equations

N, Cl,

that the sum of the equal one, i.e.,

cj

+ fg

+ fF

ICM

mathematical material-balanced

i = K, HO,

(-Ej/T)

+ fgM

HZ

HZ

MD.

Using conventional Arrhenius-type reaction for the various components are given by (-rj)

+ fIoM

i = K, HO,

Note the material-balance constraint reactor inlet and the reactor outlet

Cl + fr

Cl + f;;

fzH2

the mass

network.

N + f;'

N + f;;

MD H2 Cl + fH2

CSTR kinetic model. The material-balanced, The problem in algebra (Carberry, 1976). the reaction network are TPi

+ $

Cl+

fz represent

reaction

Mass balance to product j. reaction equal one, i.e.,

i converting for a given

5 f{

HO

I-5

11 et ai.

weight

N. Cl,

dependency

fj ~~

~x~(-E~/T)

H2,

H2,

BY,

IOM.

fractions

BY,

(6)

of the

components

in the

IOM.

on temperature,

the

rates

of production

ci

i for j and

i = K, HO, (-rj)

=

GO,

MD

1 fj Ai i

and exp(-Ei/T)

ci

HO, GO, MD. appropriate rate expression for j = N, Cl, H2, BY, IOM and i = K, Substituting the into Egn. 6 and using the stoichiometric relations, Eqn. 5, produces the identities of Eqn. 7 for are consistent and internally all components. ThLlS, the CSTR material-balance equations outlined mass-balanced. Kinetic narameter estimation. the kinetic parameters contained fli, four

preexponential

factors,

Complete description in Eqns. 5 through Ai,

and

four

kinetic model requires of the 24 stoichiometric 9. There are

temperature

response

constants,

Ei,

estimation of coefficients, for

a total

of

Thermal

I-5

solution

only 28 independent However, Egn. 5, provide four equality

32 kinetic parameters which need to be estimated. estimated because the mass-balance requirements, the stoichiometric coefficients. The

67-run

density, kinetic

data

experimental

fractions,

Pi,

the at

psi, analysis

C sl corrects

base

the

contains

temperature,

T,

conditions.

The

This

is readily

only

done

inlet

nominal

the

mass slurry

value

through

which the

fractions, space

the

needs

to

be

7,

product and

calculated

the

mass slurry the

for

(10)

output

- PC1

- P*y

weight

- PN

fractions,

not considered water is must be considered in the

FCi

= /3,1

(11)

- PH20' Pi,

for

the

amount

of products

for

i = MD,

Go,

which

are

physically in the reaction sequence, it is relation concentration correction term. The

HO,

K,

IOM,

component Note

MIN

in the

is equivalent

that

the

vapor

present between

in Ci

to the

mass-balance (12)

satisfied.

Simultaneous estimation regression of the model

OF

the

Fi,

velocity,

need be between

relations

outlet weight fraction of any on the fact that the and P. relies 1 the reactor for a CSTR. component within weight fraction of that which can be recast as constraint, Eqn. 7, for the products,

is identically

parameters relations

(pi'cel)/3sl = 1 - PH2

Sl

Although phase. the reactor and

reaction is Ci.

c. = I C

reactor

of oil shale

=

i.e., minimization data base for the to search for the

El

the of equations

zc

kinetic against

(Pi,model

is parameters the data base.

- 'i,data"

accomplished The objective

nonlinear through global, function is defined as

(13)

'

the model predictions and the the total least squares difference between of Standard nonlinear regression techniques (Bard, 1974) are used reactor outputs. "best" values of the Arrhenius parameters and stoichiometric coefficients.

estimated kinetic parameters are given in Table 2. The zero values shown for many The resultant, coefficients were "best fit" parameter estimates from the least squares of the stoichiometric regression procedure. The strongly cascading nature of the reaction network, emphasized in Fig. 2 by the solid lines, is very evident: each major reacting component converts primarily to the next lower boiling pseudocomponent. not formed in Kercgen converts to only HO and BY; IOM residue is the primary conversion step. HO converts only to W and IOM; W converts only to MD and IOM. The lighter boiling components form from cracking of MD to N, Cl, and H2. The fact that N, Cl, and H2 are, essentially, minor products has undoubtedly biased the estimated stoichiometry toward production only from middle distillate. The more likely scenario is that each is formed in small quantities from each of the major reacting species. least squares difference used The unweighted in the regression analysis, however, favors more accurate determination of the stoichiometry of the major components than of the minor components.

DISCTJSSION Several criteria can be used to judge the power of the kinetic model General overall model fit. in adequately representing the conversion reactor. First, how well does the model predict run results for run conditions which lie outside the data base? Originally, the model was developed on the basis of a 44-run data base. When the additional 23 runs which ccanprise the current data base became available, we found that the 44-run data base model predicted the results of the next 23 runs within model and experimental error. This was a powerful indicator of model adequacy because the most recent 23 runs were in a high space velocity regime while the runs comprising the 44-run data base were in moderate to low space velocity regimes. Because the entire 67-run data base appeared homogeneous with respect to the model, updated model parameters were developed based upon the whole data base. No significant changes in parameter estimates were noted. Secondly, statistical estimates of the model fit to the data can be obtained by determining the mean confidence intervals of the difference between the model and the data, i.e., the model fit to the data. Because the analysis procedure is nonlinear, the more traditional method of error analysis, i.e., an ANOVA, is not applicable. Instead, used to find the a T-test was mean difference between the model and the data for each component and the 95% confidence interval about the mean. The results, reported in Table 3, show that the model has some biases. Reactor outlet concentrations of H2, Cl, N, MD, and W are overpredicted. Conversely, reactor outlet concentrations of BY, HO, and IOM are under-predicted. The confidence intervals associated with each prediction are seen to be comparable to the confidence intervals for the experimental error, Table 1. Thus, the model predicts the data within the same degree of accuracy as the data itself. Finally, predicts

T values the data,

and associated i.e., the true

probabilities for the hypothesis difference between the model and the

that data

the model accurately is zero, are provided.

I-5

J.F. PATZER, IIetal.

1010 TABLE 2

Estimated

Arrhenius

Product Comoonent,

i

Thermal

Solution

Parameters

Stoichiometric reactant i i=K HO

Parameters Sjd

&j2A2LEl

Kinetic

Coefficient, f', product j CC MD

K

7.27

1012

24600

0

0

0

0

l-m

2.07

lo5

15100

0.963

0

0

0

GC

3.84

1014

30000

0

0.823

0

0

MU

1.09

1010

21600

0

0

0.838

0

N

0

0

0

0.543

BY

0.037

0

0

0

Cl

0

0

0

0.236

H2

0

0

0

0.048

ICM

0

0.177

0.162

0.173

the model overpredicts On the basis of the T-test, one concludes that components H2 and Cl and underpredicts the yields of the trace component components are reasonably accurately predicted.

TABLE Pseudoccannonent H2

3

(Model - Data) Mean, wt% 0.12 0.11 -0.11 0.03 6.10 0.00 -0.19 -0.06

Cl

BY N MU GO HO IOM

Model

Fit

to the Data

(+/-I 95% Limits, w-t% 0.01 0.04 0.02 0.15 0.25 0.45 0.47 0.01

the yields of However, BY.

the all

trace other

Base

Student T 16.0 5.2 -11.4 0.4 0.8 0.0 -0.8 -1.0

PR W ITI 0~0001 0.0001 0.0001 0.702 0.438 0.996 0.432 0.343

of model adequacy is how well it agrees with other existent data on the Yet another measure of rate of kerogen conversion. Table 4 provides a comparison of the rate expression developed in this work with two rate expressions developed in retorting experiments (Wallman, Tarmn, and Spars, 1981: Richardson and co-workers, 1981) and one developed in a batch CSTR thermal solution approach using a hydrogen donor solvent (Kafesjian and Tyler, 1984). The units for the rate expressions are different, as noted in the table, because the retorting experiments measured the rate of oil evolution, as opposed to rate of the kerogen conversion, which was measured in the thermal solution experiments. The various rate measurements agree within a factor to 2 to 3.

TABLE

4

Keroaen

Decomposition

Rate

Expressions

Nominal 450

* Source

Rate

Expression

Rate c

Wallman

9.64

lOlo

exp(-21943/T)

6.36

Richardson

1.95

1o1O

sxp(-20684/T)

7.34

Kafesjian

2.83

1011 exp(-23000/T)

This

7.27

1012

work

* Units Units

exp(-24600/T)

of Wallman and Richardson of other rate expressions

: (mass~C/mass : l/s

4.33 11.6 total

(x1000) 460 C

at

9.62 10.8 6.69 18.6 C produced)/s

Model aonlication. The point reaction rate description of thermal solution in FCC decant oil developed from the CSTR data can be extended to any reactor type or configuration. The major limitations in extending the model to other flow systems reside in appropriately modeling the flow regime, heat and mass transfer phenomena, and vapor/liquid equilibria. Useful representation can bs developed assuming isothermicity and comparable vapor/liquid equilibria. Extension to a plug flow model assuming that the requires vapor phase, which no longer exits the reactor upon formation, still does not react significantly. The plug flow reactor is of great interest because such a reactor can be designed to maximize the yields of liquid products in a system such as the present, which has a cascading reaction network with undesireable coking reactions occuring in secondary reactions.

Thermal

I-5

1011

solution of oil shale

CONCLUSION tool for understanding FCC decant oil provides a valuable The thermal solution kinetic model for the data base from which The model adequately represents the chemical reactions of the approach. reaction concepts rather model is fundamentally based upon chemical Because the it was derived. those under model to regimes other than than simple correlation of the data, one can extend the which the data were developed. relatively unreactive FCC decant oil as the solution Because the experimental data base uses a solution media. Changes in the model to other medium, caution should be used in extrapolating solution media. However, kinetic parameters and stoichicanetry should be expected with changes in the dynamics of the methodology explored in this work will prove equally useful in understanding other solution media.

ACKNOWLEIX3EMEN'IS The authors The authors work.

thank Drs. also thank

LEGENDOF

C. P. P. Singh and Mr. J. C. Koenig

SYM8OLS

Ai

Arrhenius

C. 1 C Sl

Concentration

of component

Concentration

of slurry

% f! I F. I Pi -ri T

Arrhenius

preexponential

temperature

Stoichiometric Weight Weight Rate

Reactor symbols

P Sl 7

Space

Slurry

factor,

l/s

i in the

in reactor, response

coefficient

reactor

constant,

for

outlet,

conversion

K of reactant

of component

i in the

reactor

feed

fraction

of component

i in the

reactor

product

temperature,

concentration velocity,

of component

kg/m3

kg/m3

fraction

of production

Greek

N. L. Carr for helpful comments in developing this work. of this Resources Company for support and Gulf Mineral

i to product

j

i, kg/m3/s

K

in reactor,

kg/m3

kg/m3/s

REFERENCES ASPEN Project (1978). 1st Annual Report-MIT-2295l'9-4, June 15, 1977; Annual 2nd Report-MIT-2259T9-9, June 15, 1978. Contract E(49-181-2295 Task No. 9, NTIS, U.S. Dept. Of Corranerce. Baldwin, R. M., W. L. Frank, G. L. Baughman, c. s. Minden (1983). 16th Oil Shale Syumposium Proceedinqs, Colorado School of Mines, Golden, Colorado. Bard, J. (1974). Nonlinear Parameter Estimation, Academic Press, New York. Chemical and Catalytic Reaction Enqineerinq, McGraw-Hill Carberry, J. J. (1976). Book Company, New York. Cummins, J. J., W. E. Robinson (1978). LERC-78-l U.S. Dept. of Energy, Laramie Energy Research Center, Laramie, Wyoming. Jensen, H. B., W. I. Barnet, W. I. R. Murphy (1953). U.S. Bureau of Mines Bulletin 533. Kafesjian, S., A. L. Tyler (1984). AIChE 1984 Spring National Meeting, Anaheim, California, May 20-23. Lewis, A. E., R. L. Braun, J. C. Diaz (1984). 17th Oil Shale Symposium Proceedinqs, Colorado School of Mines, Golden, Colorado. McKay, J. F., S-L. Chong, G. W. Gardner (1983). Liquid Fuels Technoloqy, l_, 259-267. Richardson, J. H., J. B. Huss. J. R. Taylor, M. 0. Bishop, L. L. Ott (1981). LLNL Preprint UCRL-86587, December. Wallman, P. H.; P. W. Tarran, B. P. Spars (1981). ACS Symposium Series No. 163, American Chemical Society, Washington, D.C.