Using Transient Temperature Analysis to Evaluate...
Transcript of Using Transient Temperature Analysis to Evaluate...
Using Transient Temperature Analysis to Evaluate Steam Circulation in SAGD Start-
up Process
Lijuan (Judy) Zhu, M.A.Sc., Fanhua (Bill) Zeng, Ph.D., P.Eng.,
Gang (Garry) Zhao, Ph.D., P.Eng., Farshid Torabi, Ph.D., P.Eng.
University of Regina
Outline
Introduction (background, TTA)
Methodology (assumptions , models)
Two-system, three-system and superposition
Results and discussion
Sensitivity analysis
Synthetic case studies
Field case study
Conclusions
Recommendations2
Introduction
Steam ChamberInjected steam expands vertically and horizontally in the formation.
ImportanceHeating effectiveness estimation;SAGD optimization (evenly distributed);Communication determination in start-up.
Steam chamber may not be evenly distributed
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Technologies Available
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3D/4D (time-lapse) seismicPros: Direct, successful applications;Cons: 1) Expensive, only shot at long time-interval;
2) Methane or Steam? 3) Resolution; 4) 2-D view;
3D/4D (time-lapse) seismicPros: Direct, successful applications;Cons: 1) Expensive, only shot at long time-interval;
2) Methane or Steam? 3) Resolution; 4) 2-D view;
Temperature analysis
Temperature analysis
ThermocouplePros: Stand high temperature, permanentCons: Several points
ThermocouplePros: Stand high temperature, permanentCons: Several points
Fiber opticPros: Continuous monitoring Cons: 1) Hydrogen ingression; 2) Elevated temperature? New Optolog@DTS-HT (Kaura, 2008), hydrogen resilient
Fiber opticPros: Continuous monitoring Cons: 1) Hydrogen ingression; 2) Elevated temperature? New Optolog@DTS-HT (Kaura, 2008), hydrogen resilient
Other approaches
Application of Temperature Analysis
Non-thermal recovery process:
1) Infer sand-surface flow rate of each layer;
2) Complement Transient Pressure Analysis (TPA) : φ, K and thermal properties (Duru & Horne, 2010);
Thermal recovery process:
Duong(2008) proposed a model to use exponential integral solution for radial heating to estimate cooling time and formation thermal diffusivity for a SAGD process.
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No longer new
TTA Technology for SAGD Process
180
200
220
240
1 10 100 1000 10000
Log cooling time, days
Tem
per
atu
re, C
temp@50,3,25
temp@50,4,25
temp@50,1,25
TTA
TTA
TTA
Transient Temperature Analysis
Objective: T->shape/sizeTo evaluate steam chamber size and shape distribution along the horizontal wellbore using temperature falloff data obtained from fiber optics or thermocouple after injector is shut-in.
Approach: Shape/size->TTo establish P.D.E. to calculate temperature falloff based on the temperature distribution when injector is shut-in.
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MethodologyAssumptions Heat conduction is dominant in shut-in period; Homogeneous and infinite-acting(conduction) reservoir; A radial coordinate system.
Models developed1.Two-systems 2.Three-systems 3.Superposition-in-space
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2
2
1 p
t
CT T T
r r r K t
ρ∂ ∂ ∂+ =∂ ∂ ∂
Ts Ts
TrSystem1
System2
R
Rw
∞
Tr
Ts
Tr
Ts Ts
TrSyste
m1mSyste
m2
R1R1
R2
R
w
∞
System
3
Ts
Tr
Tr
Ts Ts
TrSystem1
System2
R1
R2
Rw
∞
System3
T
s
Tr
Ts Tr
TTA vs. TPA
( , 0)( , ) r t iP r t P= = ( ) Ω∈== rforTtrT s0,
( ) Ω∉== rforTtrT r0,
Solution to TPA is not applicable to TTA! Other app roach.Solution to TPA is not applicable to TTA! Other app roach.
2
2
1 tCP P P
r r r K t
φµ∂ ∂ ∂+ =∂ ∂ ∂
2
2
1 p
t
CT T T
r r r K t
ρ∂ ∂ ∂+ =∂ ∂ ∂
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Sensitivity Analysis—Hot Zone Size/Shape in Two-system Model
D
D
td
dT
ln
The shape of the hot-zone determines the shape of temperature and its derivative curve.
The larger the hot-zone is, the later the temperature starts to falloff.
Ts Ts
TrSystem1
System2
R
Rw
∞
Tr
Ts
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The chamber size and shape plays a significant role.The chamber size and shape plays a significant role.
1. The existence of transition zone slows down the temperature falloff. 2. The larger the transition zone is, the greater the temperature falls off.
Sensitivity analysis –Transition Zone in Three-system Model
Tr
Ts Ts
TrSyste
m1mSystem
2
R1R1
R2
R
w
∞
System3
Ts
Ts Ts
TrSystem1
System2
R1
R2
Rw
Ts
Tr
TsTr
The effect of transition zone can’t be neglected.The effect of transition zone can’t be neglected.
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Synthetic Case (SAGD Start-up)BASIC SIMULATION PARAMETERS
Rock Fluid Property
Permeability 6.12 Darcy
Porosity 0.337
Pi 2000 Kpa
Soi 0.799
Swi 0.201
Ti 8 C
µo 80 poise
Thermal property
Matrix Thermal conductivity 2.74e5 J /m-day-C
Heat capacity 2.347e6 J/m3-C
Oil Thermal conductivity 1.15e4 J /m-day-C
Heat capacity 5.53e5 J/m3-C
Water Thermal conductivity 5.35e4 J /m-day-C
Heat capacity 4.195e6 J/m3-C
Well constraints
Q 50 m3/day
Steam quality 0.6
Tinj 250 C
Pinj 4500 Kpa
Ppro 4550 Kpa
Yuan(2010), SPE 143655
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Temperature at Heel
R1=1.15mR2=11.05mD=1m
0
0.1
0.2
0.3
0.4
0.01 0.1 1 10
TD
t(Day)
0
0.2
0.4
0.6
0.8
1
0.01 0.1 1 10 100
TD
t(Day)
TD_CMG
TD_3Sys
TD'_CMG
TD'_3Sys
ln( )D
D
dT
d t
TTA
TTA Interpreted results
Simulation temperature distribution
R1-Radius of the steam zone R2- Radius of the transition zone D- Distance between center and the observing point
T
r
T
s
T
s TrSyste
m1mSyste
m2
R1R1
R2
R
w
∞
Syste
m3
T
s
Tr
T
r
T
s
T
s Tr
R1
R2∞
TsTr
T
sTr
d
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Temperature in the MiddleR1=1.15mR2=11.05mD=1m
0
0.1
0.2
0.3
0.4
0.01 0.1 1 10
TD
t(Day)
0
0.2
0.4
0.6
0.8
1
0.01 0.1 1 10 100
TD
t(Day)
TD_CMG
TD_3Sys
TD'_CMG
TD'_3Sys
ln( )D
D
dT
d t
TTA
TTA
R1-Radius of the steam zone R2- Radius of the transition zone D- Distance between center and the observing point
Interpreted results
Simulation temperature distribution
T
r
T
s
T
s TrSyste
m1mSyste
m2
R1R1
R2
R
w
∞
Syste
m3
T
s
Tr
T
r
T
s
T
s Tr
R1
R2∞
TsTr
T
sTr
d
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Temperature at ToeR1=0.7mR2=9mD=0.75m
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
0.01 0.1 1 10 100
TD
t(Day)
TD_CMG
TD_3Sys
TD'_CMG
TD'_3Sys
TTA
TTA
0
0.1
0.2
0.3
0.4
0.5
0.01 0.1 1 10
TD
t(Day)
TD_CMG
TD_3SysTTA
Simulation temperature distribution
Interpreted results
T
r
T
s
T
s TrSyste
m1mSyste
m2
R1R1
R2
R
w
∞
Syste
m3
T
s
Tr
T
r
T
s
T
s Tr
R1
R2∞
TsTr
T
sTr
d
R1-Radius of the steam zone R2- Radius of the transition zone D- Distance between center and the observing point
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Field Case StudyDuong (2008), SPE 117435
Location of Producer is
consistent with field observation
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
1 10 100 1000
Result of TTA method using superposition of 2-system model
Data obtained on the producer wellbore
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Conclusions
Two-systems, three-systems and superposition radial model have
been established to model the temperature falloff behaviour. The
superposition model can be employed to model complex hot-zone
shape.
Sensitivity analysis indicated the steam chamber size and shape
have great impacts on the temperature falloff.
Synthetic case study suggested the three-system and superposition
model is helpful in evaluating the performance of SAGD start-up
process.
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Recommendations
To establish an advanced model which considers the
contribution of steam condensation.
To develop optimization algorithm for inverse problem
solving, which is to analyze steam chamber size and shape
through interpreting the measured temperature data.
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Acknowledgements
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A. DUONG
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