Understanding and design of SAGD and Solvent-SAGD in thermal applications is discussed by PetroTeach webinar.

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Outline
• Brief Introduction to PetroTeach
• Introducing our Distinguished Instructor Dr. Mazda Irani
• Webinar Presentation (45 - 60 min.)
• Introducing Course “SAGD And Solvent-SAGD Design And
Analysis “
• Q&A (15 - 20 min.)

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SAGD And Solvent-SAGD Design And Analysis
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8. Dr. Mazda Irani
PetroTeach
Distinguished Instructor
• Dr. Mazda Irani is PetroTeach Distinguished Instructor.
• Dr. Irani got his PhD in petroleum engineering from University of
Calgary in 2017 and geomechanics from the University of Alberta in
2012 and three Masters degrees in petroleum engineering,
geotechnical engineering, and structural engineering.
• Dr. Irani is the director of Ashaw Energy Ltd. He is currently engaged
in the designing and optimization of Steam Assisted Gravity Drainage
(SAGD) and proper near wellbore modeling for the SAGD wells. One of
his main tasks is to help and develop a software that can help
operators run their SAGD wells at optimum subcool, manage the hot
spots, and modify their FCD design in heterogeneous reservoirs.
• Dr. Irani was previously employed in technical and supervisory roles
with Cenovus Energy, Suncor Energy, RPS Energy, and C-FER
Technologies. He has published and presented more than 40 technical
papers on different aspects of the SAGD operation.
Advanced Analysis of Carbonate Systems 8
Biographyof the Presenter

9. SAGD And Solvent-SAGD Design And
Analysis
Dr. Mazda Irani
21.10.2020
World Class Training Solutions
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10. 1. What is the ES-SAGD Process?

11. time
Production rate
Steam Injection rate

12. Steam Circulation
time
Production rate
Steam Injection rate
Circulation time ≈ 3 months

13. Steam Injection
time
Production rate
Steam Injection rate

14. Steam Injection
time
Production rate
Steam Injection rate

15. Steam Injection
Production rate
Steam Injection rate

16. Steam Injection
Production rate
Steam injection rate
Solvent injection rate

17. Steam Injection
Production rate
Steam injection rate
Solvent injection rate

18. 2. Nsolv Process

19. Vapex Hydrate concern and field problems
Vapex with propane tried by Cenovus in Foster Creek in 2003. the operation
stops due to hydrate formation. Hydrate banks instead of oil banks have
isolated the pattern. Cenovus tried to get below 1500 kPa (i.e. the hydrate
envelope). They tried several different operations to get the chamber
pressure below 1500 kPa. Due to production operation limitations they
could not operate below 1500 kPa and then they tried to heat up the
propane to 150°C at 3000kPa.
Hydrates will form and are stable at 2700kPa and 12°C: when methane,
propane and water are present in various proportions. They found that
methane has been detrimental to this Vapex pilot. There are two sources for
methane: dissolution gas from bitumen, and impurity in supplied propane.
Both of these cannot be excluded. There is a large cost associated with
purification of propane which will effect the project economics.

20. Injection temperature (°C)
Vaporchamberpressure(MPa)
Vaporchamberpressure(MPa)
Hydrate formation envelopes for propane-methane-water mixtures

21. Hydrate formation envelopes for butane-methane-water mixtures
Injection temperature (°C)
Vaporchamberpressure(MPa)
Vaporchamberpressure(MPa)

22. Temperature(°C)
Temperature(°C)
Heated Vapex or Nsolv resolved Hydrate concerns

23. Temperature(°C)
Temperature(°C)
Heated Vapex or Nsolv resolved Hydrate concerns
Focus zone

24. Temperature(°C)
Temperature(°C)
Heated Vapex and Nsolv resolved Hydrate concerns

25. 3. ES-SAGD Process

26. Latentheat(kJ/mol)
Chamber Temperature (°C)
Chamber Temperature (°C)
Latentheat(kJ/mol)
Organic components are not containing a large latent heat
Great enthalpy gap

27. SDRP application

28. Steam-Solvent Azeotropic Behaviour

29. Steam
condensation
Solvent
condensation
Steam and solvent
co-condensation
Steam-Solvent Azeotropic Behaviour

30. Steam-Solvent Azeotropic Behaviour

31. Azeotropic Point: Grid size causing a shift
100
250
100
150
250
Temperature(°C)
200
150
Temperature(°C)
200
nButane x or y (mole fraction)
Chamber pressure = 3091 kPa
Butane condensation line
Steam condensation line
Bubble curve
10
0.20 10.4 0.6 0.8
0.2 0.4 0.6 0.8
nButane x or y (mole fraction)
LL
V
VL
Side Drained Flow
C
B
B
A
A
At interface grid
5050
Solvent/oil mixture zone
D
D

32. 4. Solvent solubility into Bitumen

33. What is K-value for bitumen?
Because bitumen is non-volatile, the k-values for bitumen were considered to
be zero:
bitumen
bitumen
bitumen bitumen
y 0
K 0
x x
  

34. 100+1
Carbon Number
Weightfraction(%)
0.0
2.5
0.5
1.0
1.5
2.0
MacKay River/Suncor
10 20 30 40 70 8050 60 90
Surmont/ConocPhilips
Weightfraction(%)
0.0
2.5
0.5
1.0
1.5
2.0
NegligibleC10
Produced Sample
C21
C20
Bitumen/steam/solvent system
The equilibrium temperature and solvent concentration at the interface is determined
by the phase behavior of the bitumen/steam/solvent system at the edge of the steam
chamber.
However, because bitumen is mainly composed of the heavy fractions and there is no
volatile component (negligible <C10), the vapor phase from bitumen is negligible and
bitumen mole fraction into vapor phase can be assumed as zero (i.e., Kbitumen =0).

35. K-value of the solvent as a function of solubility
In binary mixture of solvent/bitumen, bitumen is non-volatile or solvent is
only the volatile phase, so vapor phase (y) is almost pure solvent vapor, i.e.,
ysolvent=1 :
So K-value of solvent is inverse of solvent solubility.
The method presented for water k-value is only accurate for phases which
their solubility in oil or bitumen is negligible and is not suggested for solvents
and any soluble phase.
solvent
solvent
solvent solvent
y 1
K
x x
 

36. 5. Tuning of K-value from Solubility
Data

37. 0 9.03.0
Pressure (MPa)
6.0
0.0
0.2
0.0
0.2
B
Temperature (°C)
2.5
100 120 140 160 180
1.0
1.5
2.0
KvalueNumber()
3.0
2.5
1.0
1.5
2.0
3.0
Nonlinear correlation
CMG Kvalue
KvalueNumber()
Linear vs. nonlinear correlation
Ln(P)+Ln(K) vs. temperature in propane-bitumen mixture is more
pronounced. It shows that ϖ2 should be included.

38. Nonlinear correlation in propane solubility
The results of the nonlinear correlation matching shows great success for
propane solubility matching.
0 9.03.0
Pressure (MPa)
6.0
0.0
0.2
0.4
0.6
0.8
1.0
Measured
A
PropaneMoleFraction(fraction)
0.0
0.2
0.4
0.6
0.8
1.0
B
100 °C
150 °C
175.4 °C
189.3 °C
Nonlinear match
PropaneMoleFraction(fraction)

39. Checking the Tuning exercise
Ln(P)+Ln(K) vs. temperature is plotted to evaluate competency of the linear
correlation versus the non- linear correlation.
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
80 100 120 140 160 180 200
Ln(P)+Ln(K)
Temperature(°C)
Predicted
Measured

40. Checking the Tuning exercise
The red dots in Ln(P)+Ln(K) vs. temperature can be an outlier, or
experimental error. So should be excluded from data set.
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2.2
80 100 120 140 160 180 200
Ln(P)+Ln(K)
Temperature(°C)
Predicted
Measured

41. 6. Asphaltene Deposition

42. 200150100500
4
2
6
0
8
10
200150100500
Temperature (°C)
Temperature (°C)
Pressure(MPa)
4
2
6
0
8
10
LL Region
VL Region
LL Region
VL Region
Propane saturation curve
Pressure(MPa)
Asphaltene Deposition

43. Gas-liquid interface
(Propane has the highest
concentration)
Onset of Asphaltene precipitation
(layer of Asphaltene left behind)
Fresh bitumen interface
(Propane contacting fresh bitumen. No
Asphaltene precipitation because propane
concentration is low)Diluted bitumen draining
Bitumen
Vapor propane
Asphaltene Deposition

44. Fringes of Asphaltenes: Das and Butler Hele-Shaw tests

45. Solvent/bitumen Mixture Viscosity
1
10
3
4
105
0 0.2 1.0
Mixtureviscosity(cp)
Propane mole fraction (fraction)
0.4 0.6 0.8
2
0.1
0.01
SaturationLimit
Liquid
C3
pseudo
C3
Asphaltene
(Heavy Phase)
Light Phase
Bitumen
10
10
10

46. 7. Diffusion/Dispersion

47. Bitumen Saturated Zone
x
VaporInterface
Vapor Chamber
Ux
Butane Encroachment
Solvent Mole Fraction
xvapor
xsolubility
Capillary
Mixing
Dispersion
Zone
Conduction Heating
DiffusionZone
Temperature
Tchamber
Drained Flow
xbitumen

48. Mix
Butane Transport into Streaks
Mixing/Diffusion
x
CondensateAccumulationattheEdge
CondensateInterface

49. Solvent intrinsic and overall diffusivity
Firstly, we should calculate the solvent intrinsic diffusivity from
overall diffusivity.
s
s
D
D
1 0.969c


: for Athabasca bitumen

50. As shown the intrinsic diffusivity is yielding infinity:
0.1
1
10
100
0 0.2 0.4 0.6 0.8 1
D×106(cm2/sec)
Volume fractionof Toluene
Solvent intrinsic and overall diffusivity

51. SAGD and Solvent-SAGD Design and Analysis in Thermal Recovery
(online)
2021: 25 - 26 Jan./ 10 - 11 June / 9 - 10 Nov
Register@petro-teach.com
Learning Objectives and Themes
This is a 2-day course designed to provide participants with a complete understanding
and design of steam assisted gravity drainage (SAGD) oil production and SOR
evaluation and also new technologies of Solvent in thermal applications.
In 1st-day of this course is an introduction to Butler assumptions and mathematical
principles and its limitations and also briefly discusses other studies which address
steam assisted gravity drainage (SAGD) oil production and SOR evaluation. In this
course there will be examples using Excel spreadsheets.
In 2nd-day of this course the thermodynamics and pressure-volume-temperature (PVT)
and tuning parameters to fit laboratory data is described. Different analytical models for
oil rate predictions such as Butler-Mokrys (1989) and Dunn-Nenniger-Rajan (1989)
models will be
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Any Questions ?
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