Modeling Heavy Oils in
Aspen HYSYS
Engineering Excellence Webinar Series
26 January 2010
© 2010 Aspen Technology, Inc. All rights reserved
Modeling Heavy Oils in Aspen HYSYS
• Dr. Mohammad Khoshkbarchi
− Senior Project Manager, Process Ecology
− Email: [email protected]
• Sanjeev Mullick
− Director, Product Marketing, AspenTech
− Email: [email protected]
• http://support.aspentech.com
© 2010 Aspen Technology, Inc. All rights reserved
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Agenda
ƒ Heavy Oil Overview
ƒ Best Practices for Modeling Heavy Oils in Aspen HYSYS
ƒ Sample Applications
ƒ Recommendations and Conclusions
ƒ Q&A
© 2010 Aspen Technology, Inc. All rights reserved
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What is Heavy Oil?
• By definition, has API gravity < 20° & viscosity > 1,000 cP
• Has over 60 carbon atoms, and hence, a high BP & MW
• Mainly comprised of hydrocarbons heavier than pentanes,
with a high ratio of aromatics and
naphthenes to paraffins
• High amounts of nitrogen, sulfur (~5%),
oxygen and heavy metals
• Exists in a semi-solid state and may not
flow in its naturally occurring state
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Comparative Oil Properties
Oil Viscosity:
Conventional Crude
<~ 30,000 cSt
Conventional Heavy
30,000 – 40,000 cSt
Thermal Heavy
200,000 – 250,000
cSt
0.5 – 11.0 cSt
Diluent
Oil API:
Conventional Crude
Conventional Heavy
> 25 °API
25 – 18 °API
Extra Heavy (Thermal)
Tar Sand
20 – 12 °API
12 – 7 °API
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Where Does it Exist?
• Heavy oil deposits total almost 5½ trillion barrels (est.);
80% of deposits are in the Western Hemisphere
- In the U.S., heavy hydrocarbon deposits are estimated to be
more than eight times that of the nation's remaining reserves
of conventional crude oil
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Where Does it Exist?
1. Western Canada
– Mainly in the form of oil sands in Alberta
• 44% of Canadian oil production in 2007 was from oil sands, with an
additional 18% being heavy crude oil
– Average density is API = 8°
– Viscosity within a range 5000-10,000 cP,
and higher (up to 100,000 cP)
2. Venezuela
– Mainly heavy oil
– Viscosity within a range of 1000-5000 cP
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Challenges in Modeling Heavy Oils
• Characterizing the oil
– Defaults
– Data
ƒ Bulk
ƒ Curves
– Viscosity
• Blending to match properties at wellhead
– Emulsion viscosity
• Phase entrainment/carryover
• Foaming
• Further effects of adding solvents
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Implications of Poor Modeling
• Incorrect wellhead conditions
– Steam-Oil ratio
– Properties prediction
– Flash conditions: vapor when it’s really a liquid/vice versa,
trivial phases
• Large pressure gradients
• Unattainable separations
–
–
–
–
Products: SCO
Capacity
Yields
Over/under design of towers, drums
• Misrepresented utilities
– Over/under design of heat exchanger units
© 2010 Aspen Technology, Inc. All rights reserved
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Agenda
ƒ Heavy Oil Overview
ƒ Best Practices for Modeling Heavy Oils in Aspen HYSYS
ƒ Sample Applications
ƒ Recommendations and Conclusions
ƒ Q&A
© 2010 Aspen Technology, Inc. All rights reserved
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Best Practices Workflow
Assay Setup
Oil Properties
Build PFD
Enter Assay
lab data
Enter User
Cutpoint
ranges
Blend Oil &
Water streams
Check
Correlation set
Verify/alter
Extrapolation
& Conversion
Methods
Blend Assay &
Cut into Hypos
Alter emulsion
viscosity, if
necessary
Compare
Property Plots
Incorporate
entrainment
Install Oil
Use Utilities to
check products
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Oil Characterization in Aspen HYSYS
• Purpose: convert lab analyses Æ Aspen HYSYS library and
hypothetical components
• 3 steps in Oil
Characterization:
1.
Characterize
the Assay
2.
Generate
Pseudo
Components –
Cut/Blend
3.
Install the Oil in
the Flowsheet
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True Boiling Point (TBP)
FBP
True Boiling Point Curve
1200
Bolining Point (C)
1000
IBPi
FBPi
800
600
400
200
0
IBP
0
20
40
• Alternative Methods:
− ASTM D86 (atmospheric batch distillation)
− ASTM D1160 (vacuum batch distillation)
− ASTM D2887 (chromatography)
• Usually unsuitable for heavy crudes
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60
Volum e % Distilled
80
100
1. Characterizing the Assay
• Know how your lab handles its analysis:
– Which analysis type?
– Are they applying any corrections?
– Are light-ends included? Or is it a separate analysis?
ƒ Input Composition
ƒ Auto Calculate
ƒ Ignore
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True Boiling Point (TBP)
Conventional Oil TBP
Heavy Oil TBP
700
1200
600
1000
Bolining Point (C)
Bolining Point (C)
800
500
400
300
200
100
800
600
400
200
0
-100
0
20
40
60
80
100
0
0
20
Volum e % Distilled
40
60
Volum e % Distilled
• Heavy oil TBP has much fewer experimental points
• No FBP or close point to it
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80
100
1. Characterizing the Assay
• Light Ends handling and Bulk Property fitting:
– Are Light-ends included in the input curves?
– Are Light-ends included in the bulk properties?
– What bulk data do you have? Do you also have property
curves?
– Do you want to control which part of the curve is tuned to
match the bulk property?
• Understand the correlations used
• Understand which conversion and extrapolation methods
are used
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Best Practices
Specify Properties for Heavy Oils
• Bulk property options include:
– Molecular Weight > 16
– Mass Density = 250 ~ 2000 kg/m3
Required
– Watson K Factor = 8 ~ 15
Recommended
– Bulk Viscosity, @ 100°F and @210°F
Required
• Add other property curves
– Molecular Weight curve
– Density curve
Recommended
– Viscosity curve (two curves)
Recommended
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2. Generating Pseudocomponents
• Blending is used to blend a number of assays. It provides a
general presentation of the whole crude. Cutting not only
generates the
pseudocomponents,
but also determines
their compositions
in the crude
– Auto Cut: based
on values specified
internally
– User Points:
specified cut points
are proportioned based on internal weighting scheme
– User Range: specify boiling point ranges and the number of
cuts per range
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Best Practices
Creating Hypotheticals for Heavy Oils
• When generating pseudocomponents for heavy oil
fractionation, recommend using User Points or User Defined
Ranges
• How many?
– Minimum of 4 pseudocomponents per draw
– Use Composite plot to
determine exact number
for each temperature
range
ƒ Test accuracy of input
assay data against
generated hypotheticals
“How well does my data
match with Aspen HYSYS”?
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True Boiling Point (TBP)
• The undershoot in the
extrapolation could change to
overshoot as well
True Boiling Point Curve
1200
1000
B o lin in g Po in t (C )
• In the absence of high FBP
experimental data the
extrapolation of the curve
could result in abnormalities.
This will have a great impact
on the set up of some unit
operations such as
distillation.
800
600
400
200
0
0
20
40
60
Volume % Distilled
• Solution:
− Use a guide point such as FBP or IBP
− Use other distribution
© 2010 Aspen Technology, Inc. All rights reserved
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80
100
Best Practices
Predict Heavy Oil Fractions
• Use the Distribution Plot to help predict crude products
– Enter custom cuts
to slice oil as desired
– See product changes
with temperature
– Use these fractions
as initial product
draw rates for
converging the
column (i.e., for
front end of an
upgrader)
“Approximately
how much of every
product will I get”?
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3. Installing the Oil
• Installing the oil in the flowsheet is done by providing a
stream name on the Install Oil tab. This:
1. Adds the pseudo components to the Fluid Package
2. Transfers the pseudo component information into the
Flowsheet
3. Creates a stream on the Flowsheet with a defined
composition
If you forget this step, you will not be able to see the oil
composition in the flowsheet!
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Best Practices
Stream Utilities for Oils
• Use stream Utilities to check individual streams against the
composite oil
– Boiling Point Curves: calculates simulated distillation data and
critical property data for each cut point and cold properties
– Cold Properties: shows boiling point
curve and breakdown of Paraffins/
Naphthenes/Aromatics for the
installed oil
© 2010 Aspen Technology, Inc. All rights reserved
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Aspen HYSYS Can Accurately Predict
Important Heavy Crude Properties
The following section looks at special considerations in
predicting heavy oil properties, including:
n Specific Gravity/Standard Density
o Extrapolation Methods & Fitting Options
p Viscosity
q General Oil Properties, i.e., Thermal Conductivity
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n Specific Gravity
• Specific gravity is an extremely important data point for the
accurate extrapolation of heavy oils, as well as an important
data point to generate a missing SG curve
– Bulk SG is, by default, optional and part of the assay analysis
• It is therefore
recommended
that the bulk density
(or density curve)
be supplied as an
input parameter
for the accurate
characterization of
a heavy oil
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Specific Gravity
Example Problem and Solution
• Problem: Range of discrepancy in estimated density
values is 6% at lower NBPs and up to 11% at
higher NBPs
• Solution: Apply different correlation sets for multiple NBP
ranges
– Inconsistent/unreliable SGs at heavy ends can
result especially if the SG is estimated from any
correlation where NBP is the only independent
variable, since SG might also be a function of MW
– The SG curve generated from input data should be
consistent and follow the trend of the boiling point curve
– Watson K method creates a Watson K curve based on boiling curve
and average SG. This Watson K curve is used to generate component
SG boiling point, then moved up and down to match bulk SG.
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o Curve Extrapolation
• Available mathematical extrapolation methods (for both
ends) include:
– Probability
– Least squares
– Lagrange
• Recommended
selections for heavy
oils are shown here
– The linear
extrapolation method
is not appropriate for extrapolating the SG, MW and viscosity
curves for heavy ends. The least squares (2nd order
polynomial), applied at both ends, is recommended.
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Curve Fitting Options
– Curve Includes L.E.
• For each input curve, can specify:
– Bulk Value
– Bulk Value Incl. L.E.
– Head %
– Head Adjust Weight
– Main %
– Main Adjust Weight
– Tail Adjust Weight
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Curve Fitting Options
Example Problem and Solution
• Problem: Property curves are shifted along y-axis
• Solution: To correct discrepancies, you have 3 options:
− Change Bulk
Value (least
accurate), or
− Adjust Main %
and Tail Adj Wt.
to correspond
with data entry
points (manual),
or
− Apply Smart
Bulk Fitting
(automatic)
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Curve Fitting Options Example
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Curve Fitting Options
Example Problem and Solution
• Problem: TBP Curve is shifted along the liq. vol. x-axis
– A TBP, by default, includes light ends; however, if the TBP was
obtained from a light-ends free sample, Aspen HYSYS can readjust the curve to the overall crude
• Solution:
Choose to fit
with or without
light ends, as
appropriate:
– In situations when only partial light ends analysis data is
available, Aspen HYSYS can generate overlapping hypothetical
components to compensate the missing portion of the light
ends, making the output stream matching both the partial light
ends input and the other input curves
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p Viscosity
• Viscosity is key to both successfully understanding the fluid
properties of a heavy oil and for predicting oil recovery
• Both viscosity reduction and thermal expansion are the key
properties to increase productivity of heavy oils
– Viscosity influences every aspect of a heavy oil development
• Effect of viscosity on pressure gradients
– For real liquids, the effect of pressure is relatively small when
compared to the temperature effect; but large pressure
gradients tend to occur with high viscosity oils. At higher flow
rates, frictional heating effects can become significant, and the
heating tends to reduce the oil viscosity, which in turn, affects
the pressure gradient. The net result is that the predicted
pressure gradient may be higher than should actually be
expected.
© 2010 Aspen Technology, Inc. All rights reserved
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Viscosity Options in Aspen HYSYS
• Since viscosity is the key property to proper heavy oils
characterization, we do not recommend omitting this
variable
• Optional to use:
– Bulk viscosity values (recommended)
– Only viscosity curve
– Two viscosity curves (optimal)
• Higher flexibility on temperature extrapolation
• Note: Bulk viscosity and viscosity curves can be input at
different temperatures
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Heavy Crude Viscosity Trends
Cut Viscosity vs. Final Boiling Point
120000
250000000
100000
200000000
Viscosity (cSt)
Viscosity (cSt)
Full Crude Viscosity vs. Temperature
80000
60000
40000
20000
150000000
100000000
50000000
0
0
0
50
100
150
0
200
400
Temperature (C)
600
800
1000 1200
FBP (C)
• Use two points from full crude viscosity curve.
• High FBP viscosities are usually a result of extrapolation
using a log(log) approach.
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Viscosity Curves
Example Problem and Solution
• Problem: Calculated and inputted viscosity values don’t
match. Depending on the application, bulk values are
good, but in other cases (like heavy oils) the cuts value
(i.e., residue) is better.
– Quite a typical case:
ƒ Low quality viscosity
curves for extrapolation purposes
ƒ It is a measure range
problem
ƒ Inconsistent data
leads to a mismatch
of input to calculated
• Solution: Manipulate
bulk value by trial and
error to match residue viscosity
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Indexed Viscosity
• Viscosity cannot be blended linearly, so a methodology is
adopted that substitutes a function of the measured viscosity
that is approximately linear with temperature. A linearized
equation for viscosity is given by Twu and Bulls (1980).
• On the Parameters tab for equation of state methods, you
can change the viscosity calculation method from HYSYS
Viscosity to Indexed Viscosity to determine the blended liquid
viscosity
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q General Oil Properties
• When comparing Aspen HYSYS-predicted property values
against vendor, lab, or plant data, for properties such as
liquid density, viscosity, thermal conductivity and heat
capacity, there can be some discrepancies, since:
– They are generated from general thermodynamic models
– It is not realistic to expect model predicted results to exactly
match real data
• To improve the accuracy of these properties, use the Tabular
feature in Aspen HYSYS to:
– Edit the coefficients for property correlation
– Regress lab data directly in Aspen HYSYS
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Example: Improving Thermal Conductivity
Alter coefficients
Regress data
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Checklist for Modeling Heavy Oils
9 Enter lab data—distillation data, light ends, bulk properties,
and/or curve data (MW, density, viscosity)
9 Verify correlation set used for assay over entire
temperature range
9 Validate appropriate selections for assay extrapolation and
conversion methods
9 Blend and cut assay using user cutpoint ranges
9 Compare plots of input data vs. calculated TBP curve,
gravity, viscosities, etc.
9 Install oil
© 2010 Aspen Technology, Inc. All rights reserved
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Checklist for Modeling Heavy Oils
9 Blend water and oil streams; check emulsion properties
9 Build flowsheet
9 Incorporate phase entrainment in separators (using
carryover function) and columns (via efficiencies)
9 Use stream utilities (BP curves, Cold Properties) to check
individual streams against the composite oil
© 2010 Aspen Technology, Inc. All rights reserved
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Agenda
ƒ Heavy Oil Overview
ƒ Best Practices for Modeling Heavy Oils in Aspen HYSYS
ƒ Sample Applications
ƒ Recommendations and Conclusions
ƒ Q&A
© 2010 Aspen Technology, Inc. All rights reserved
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Steam Assisted Gravity Drainage (SAGD)
RECOVERED
DILUENT/SCO
DILUENT/
SYNTHETIC
CRUDE
Gas
Treating
SWEET
GASES
SOUR
GASES
GAS
Well Pad
Emulsion
Gas-OilWater
Separation
OIL [DILBIT/
SYNBIT]
WATER
STEAM/HEAT
Steam
Generation
© 2010 Aspen Technology, Inc. All rights reserved
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To
Upgrader
or Pipeline
Steam Assisted Gravity Drainage (SAGD)
Aspen HYSYS Model
GAS TREATMENT
Make up Streams
Well Pad
DilBit
Diluent
To Upgrader
or Pipeline
OIL TREATMENT
WATER TREATMENT
STEAM GENERATION
© 2010 Aspen Technology, Inc. All rights reserved
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Steam Assisted Gravity Drainage (SAGD)
DESIGN
OPERATIONS
• Model wellpad characteristics
• Model separation of water,
oil, and gas phases
• Use model to make decisions
in all phases of operation—
preheat, steam injection & oil
production, and blowdown
• Track and report key
components—sulfur, etc.
• Determine how operating
improvements
– Additions of diluent and/or
solvents, their flow conditions,
separation scheme & recovery
– Bitumen treatment and recovery
– Steam generation
– Water treatment (incl. softening)
• Perform profit calculations
(upgrade to SCO or sell)
• Consider new technology—
partial upgrading in-situ,
combustion, VAPEX, etc.
– Increase bitumen separation/
recovery
– Reduce energy requirements
– Improve water usage
© 2010 Aspen Technology, Inc. All rights reserved
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44
Agenda
ƒ Heavy Oil Overview
ƒ Best Practices for Modeling Heavy Oils in Aspen HYSYS
ƒ Sample Applications
ƒ Recommendations and Conclusions
ƒ Q&A
© 2010 Aspen Technology, Inc. All rights reserved
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Recommendations for Heavy Oils
1. For Assay data, generally suggest entering Gravity, Boiling
Point Range, Watson K;
For Heavy Crudes, recommend including Viscosity—Bulk or
Curve
2. When generating Pseudo-Components, Auto-Cut option is
not the best choice for heavy oil fractionation; recommend
using User Points or User Defined Ranges; generate a
minimum of 4 pseudo-components per draw
3. Suggested Thermodynamic Methods are:
Heavy Hydrocarbons:
Light Hydrocarbons:
Hydrogen Rich:
Sour Water:
Peng
Peng
Peng
Peng
Robinson with Lee-Kesler Enthalpies
Robinson
Robinson
Robinson Sour
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Recommendations for Heavy Oils
4. Verify usage of:
–
–
–
Correlations set
Extrapolation methods for property curves
Fit option with light ends
5. Use Plots and Utilities to match data to model and correct
for any deficiencies in data
–
–
Plots: Composite, Oil Distribution
Utilities: Cold Properties, BP Curves
6. Integrate lab/plant data into thermodynamic parameters
© 2010 Aspen Technology, Inc. All rights reserved
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Recommendations for Heavy Oils
7. Aspen HYSYS can match Heavy Oils data for simulation
studies as validated in three papers
–
–
–
Hyprotech, HYSYS, and Oils
Technical Audit of Heavy Oil Characterization Methods
Heavy Crude Oil Handling
8. Simulation Basis Manager—Chapter 4, Aspen HYSYS Oil
Manager—provides all the technical details and options
9. Support Knowledge Base offers many solutions on this topic
–
–
–
Sample files
Technical tips: keywords such as, viscosity, thermal conductivity,
density
Example file: The usage of Indexed Viscosity option in HYSYS
with an example
© 2010 Aspen Technology, Inc. All rights reserved
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Agenda
ƒ Heavy Oil Overview
ƒ Best Practices for Modeling Heavy Oils in Aspen HYSYS
ƒ Sample Applications
ƒ Recommendations and Conclusions
ƒ Q&A
© 2010 Aspen Technology, Inc. All rights reserved
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49
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Dr. Mohammad Khoshkbarchi
Senior Project Manager, Process Ecology
Email: [email protected]
Dr. Glenn Dissinger
Director, Product Management, AspenTech
Email: [email protected]
Sanjeev Mullick
Director, Product Marketing, AspenTech
Email: [email protected]
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