Sensitivity Analysis of Rock Physics
Parameters for Modeling Time-Lapse
Seismic(4D) response of Norne Field
Amit Suman and Tapan Mukerji
25th SCRF Annual Meeting
May 9 – 11, 2012
Joint Inversion Loop
Predicted
flow and
seismic
response
Generate
multiple
models
Observed
flow and
seismic
response
.
SCRF
Reservoir
Model
Evaluate
misfit
2
Motivation
Dynamic
modeling
Rock physics
modeling
Production
data at time t
Δ Pressure
Δ Saturation
Optimize
mismatch
Velocity at
time t
Seismic data
at time t
Update
parameters
3
Previous Work
• Last year we investigated parameter sensitivity
for modeling time-lapse seismic and flow data of
Norne field
• One of the investigated parameters was rock
physics model
• We didn’t investigate sensitivity of varying rock
physics parameters on modeling 4D response
SCRF
4
Questions?
“Should we investigate sensitive rock
physics parameters in modeling 4D
response?”
“What are the sensitive rock physics
parameters in modeling 4D
response?”
SCRF
5
Norne Field Segment E
F1H
E
G
E3H
D
C
In this study well log data of two wells are used
SCRF
6
Data Available
• Well logs (Sw, Sonic, Phi)
• Horizons
• Well data
- Oil , gas and water flow rate
- BHP (Bottom hole pressure)
SCRF
7
Rock Physics Modeling
Near the Well
Well Logs
Rock Physics
K and G
(All Brine)
Reservoir
Vp and Vs
(Initial)
K and Phi
G and Phi
Sonic
Sw, Phi
Gassmann’s
Substitution
K and G
(All Brine)
Facies
classification
K and G
(at Reservoir)
Calculate
Vp and Vs
(All Brine)
Populate K ,G
based on Phi
K : Bulk Modulus G: Shear Modulus
SCRF
8
Facies Classification
Shale
Vp / Vs
Brine Sand
Shaly Sand
Oil Sand
AI
Vsh
SCRF
9
Rock Physics Modeling
Near the Well
Well Logs
Rock Physics
K and G
(All Brine)
Reservoir
Vp and Vs
(Initial)
K and Phi
G and Phi
Sonic
Sw, Phi
Gassmann’s
Substitution
K and G
(All Brine)
Facies
classification
K and G
(at Reservoir)
Calculate
Vp and Vs
(All Brine)
Populate K ,G
based on Phi
K : Bulk Modulus G: Shear Modulus
SCRF
10
Sensitivity Parameters in fluid substitution
• Clay content
• Salinity
• Gas-oil ratio (GOR)
• Pore pressure
The sensitivity of varying above parameters to
variations in Response
Response: Sum of seismic P-wave velocity after
fluid substitution
SCRF
11
Experimental Design
Clay content (%)
0
20
40
Salinity (ppm)
150000
155000
160000
GOR
175
200
225
Pressure (Mpa)
25
27
30
SCRF
12
Results of fluid substitution
Response
Sensitivity to clay content
0
20
40
Sensitivity to pore pressure
25
27
30
Sensitivity to salinity
15000
15500
16000
Sensitivity to GOR
175
200
225
Clay content and GOR are the first and second most
sensitive parameters in fluid substitution
13
Rock Physics Modeling
Near the Well
Well Logs
Rock Physics
K and G
(All Brine)
Reservoir
Vp and Vs
(Initial)
K and Phi
G and Phi
Sonic
Sw, Phi
Gassmann’s
Substitution
K and G
(All Brine)
Facies
classification
K and G
(at Reservoir)
Calculate
Vp and Vs
(All Brine)
Populate K ,G
based on Phi
K : Bulk Modulus G: Shear Modulus
SCRF
14
Rock physics model
Varying clay content and GOR (9 cases)
SCRF
15
Constant cement model
Clay
content
Cement
fraction
Coordination
number
16
Fluid mixing
• Seismic velocities depend on fluid saturation as
well as saturation scale
• Reservoirs with gas are very likely to show patchy
behavior
Sengupta ,2000
SCRF
17
Effective pressure model
Two effective pressure models are selected for
sensitivity study
SCRF
18
Sensitivity Parameters in modeling 4D response
• Clay content
• Gas-oil ratio (GOR)
• Coordination number
• Cement fraction
• Effective pressure model
• Fluid mixing (Uniform or Patchy)
The sensitivity of varying above parameters to
variations in Response
Response: L1 Norm of change in seismic P-wave
impedance after 4 years
19
Experimental Design
Clay content (%)
0
20
40
GOR
175
200
225
Coordination
number
5
7
9
Cement fraction
(%)
1
3
5
Effective
Model 1
pressure model
Model 2
Fluid mixing
Patchy
Uniform
Total number of cases: 324
20
Methodology
Dynamic
modeling
(1997-2001)
Rock
physics
modeling
Δ Pressure
Δ Saturation
P-wave
impedance in
1997 and 2001
Difference in
impedance
SCRF
Compare
21
Results
Clay content = 0 %
P-wave impedance
change in 4 years
(m/s.kg/m3)
SCRF
Clay content = 20 %
22
Results
Sensitivity to clay content
Response
0
20
40
Sensitivity to GOR
175
200
225
Sensitivity to effective pressure model
Model 1
Model 2
Sensitivity to coordination number
5
7
9
Sensitivity to cement
1
3
5
Sensitivity to fluid mixing
Uniform
Patchy
23
Conclusions and Future Work
• Clay content is the most sensitive parameter in
fluid substitution
• Salinity and pore pressure have a lesser impact
than clay content
• Coordination number is the most sensitive
parameter in modeling 4D response of Norne
field
• The result of this study will be used in joint
inversion of time-lapse and production data of
Norne field
SCRF
24
Acknowledgement
• Statoil for data
• Norwegian University of Science and
Technology (NTNU)
SCRF
25
Conclusions and Future Work
• Clay content is the most sensitive parameter in
fluid substitution
• Salinity and pore pressure have a lesser impact
than clay content
• Coordination number is the most sensitive
parameter in modeling the time lapse seismic
signature of Norne field
• The result of this study will be used in joint
inversion of time-lapse seismic and production
data of Norne field
SCRF
26