Upload
blake-walls
View
48
Download
0
Embed Size (px)
DESCRIPTION
Establishing Patterns Correlation from Time Lapse Seismic. Jianbing Wu [1] , Andre Journel [1] , Tapan Mukerji [2]. [1] Stanford Center for Reservoir Forecasting [2] Stanford Department of Geophysics. Objective. Establish patterns correlation between seismic and water saturation variables - PowerPoint PPT Presentation
Citation preview
Establishing Patterns Correlation from Time Lapse Seismic
Jianbing Wu[1], Andre Journel[1], Tapan Mukerji[2]
[1] Stanford Center for Reservoir Forecasting[2] Stanford Department of Geophysics
2
Objective
• Establish patterns correlation between seismic and water saturation variables
• Predict the water saturation field (future work)
3
Outline• The challenge of 4D seismic• The Stanford V reservoir• Flow simulation• Seismic amplitude simulation• Point-to-point correlation• Pattern correlation• Conclusions and future work
4
• 4D seismic can be used to detect fingering, monitor fluid movement, improve recovery and locate new wells
• Success stories are limited to clastic reservoirs, shallow reservoirs, some carbonate reservoirs and reservoirs with great density differentiation
• This study aims at establishing correlation between seismic and water saturation variables in intermediary less favorable cases
The challenge of 4D seismic
5
The challenge of 4D seismic (cont.)
t1=Jan.1, 2000 t2=Jan.1, 2002Overall correlation: -0.11yet excellent visual pattern correlation
Seismictimelapse
Watersaturationtimelapse
. . .
6
The Stanford V reservoir (Layer 2)
Clastic fluvial channels
Facies Proportion
mudstone 47%
sandstone 45%
crevasse 8%
injectorproducer
7
Introduction to Stanford V reservoir (cont.)
10130100 stratigraphic grid
t op
st r at i gr aphi ccoor di nat es
s=0
s=1
613m
1097m
283m
60m
dept h( t r ue coor di nat es)
0m
600m
1100m
Layer 2
bot t om of r eser voi r envel ope
t op of r eser voi r envel ope
dz=10m
10sub- l ayer sz( x, y, j )
z( x, y, i )
50130100 true depth grid
8
The Stanford V reservoir (cont.)
(md)
Channel sand 0.27 648
Crevasse 0.24 521
Mudstone 0.07 1.5
All layer 0.17 314
K
9
Flow simulation
Oil density 45API0
Pressure 1100psiTemperature 1800FWater viscosity 0.325cPGOR 850scf/STB
Reservoir parameters:
Initial water saturation:15.0Sw30.0Sw
in sandstone and crevasse
in mudstone
10
Flow simulation (cont.)
0.0 0.2 0.4 0.6 0.8 1.00.0
0.2
0.4
0.6
0.8
1.0
krw kro
rela
tive
pe
rme
ab
ility
water saturation0.0 0.2 0.4 0.6 0.8 1.0
0.0
0.2
0.4
0.6
0.8
1.0
krw kro
rela
tive
pe
rme
ab
ility
water saturation
Relative permeability curves:
mudstone sandstone & crevasse
11
Oil saturation field on Dec. 29, 2013 (before breakthrough)
Vertical Section at x=20
12
Normal incidence 1D convolution model
with Fresnel zone lateral averaging
Seismic amplitude simulation
Seismic amplitude should be able to
distinguish velocity difference when
saturated with 100% brine vs. 100% oil
13
Forward simulate seismic amplitude (cont.)
Sandstone Crevasse
Mudstone
14
Fresnel zone: 225m
Horizontal resolution
Vertical resolution: 15m
Vertical section X=1 Initial ( Jan. 1, 2000)
lithofacies
Layer 2 mean thickness: 152m
Forward simulate seismic amplitude (cont.)Impedance
Amplitude
MudstoneCrevasseSandstone
15
• Different volume supports
Seismic amplitude: Fresnel zone
Saturation: grid node
• Seismic amplitude shows vertical impedance contrast
Point-to-point correlation
. . .
16
Point-to-point correlation (cont.)
L
l l
L
l ll SwSw
1
1
u
1,,,,,, kjiSwkjiSwkjiSwd
Colocated correlation between seismic amplitude and a vertical contrast of spatially averaged saturation values.
399 L total nodes within a moving window
with:
17
Point-to-point correlation (cont.)
(Jan. 1, 2000)
seismic amplitude
vertical water contrast
Overall 3D colocated correlation: -0.20 poorbut excellent visual pattern correlation
18
Spatial pattern correlation
Principal component analysis (PCA)Canonical analysis (CA)
1. Well understood, easy to apply
2. Linear combinations of data within 3D moving windows
3. PCA aims at max. within-window variance contribution
4. CA aims at defining pairs of max. correlated linear combinations
19
Spatial pattern correlation (cont.)
Template sizes:
Seismic: only vertical
W 1(u,1)W 1(u,2)
W 1(u,7)
k-3k-2
k+3
Z
Water saturation: 3D
X
Y
Z
W 2(u,1),W 2(u,2),W 2(u,3)
W 2(u,4),W 2(u,5),W 2(u,6)
k-1
k
k+1W 2(u,7),W 2(u,8),W 2(u,9)
X
Y
u(i,j) i+2i-2
j+2
j-2
W (u,1): va lue a t
W (u,2): m ean va lue over
W (u,3): m ean va lue over
20
Spatial pattern correlation (cont.)
3D correlation (space only) :
PCA applied to data recorded on Jan. 1, 2000:% within-template variance explained by 1st seismic PC: 84% 1st saturation difference PC: 84%Overall colocated correlation 0.39
PCA repeated on data recorded on Jan.1, 2002:correlation is 0.32
Correlation values improve, but still low!
21
Spatial pattern correlation (cont.)
4D correlation:
PCA and CA performed on time lapse data:
time difference of seismic amplitude:
time difference of water saturation vertical contrast:
1212 ,,,,,,,,,, tkjiseistkjiseisttkjiseis
1212 ,,,,,,,,,, tkjidSwtkjidSwttkjisw
tkjiSwtkjiSwtkjidSw ,1,,,,,,,, with:
22
Spatial pattern correlation (cont.)
1st PCseis
1st PCsw
t1=Jan.1, 2000 t2=Jan.1, 2004
Overall 4D correlation: 0.78 !! Significant
. . .
23
Spatial pattern correlation (cont.)
1st CCseis
1st CCsw
t1=Jan.1, 2000 t2=Jan.1, 2004
Overall 4D correlation: 0.82 !! Significant
24
seis
sw
t1=Jan.1, 2000 t2=Jan.1, 2004
Overall 4D correlation: 0.34
4D colocated point-to-point correlation
25
• Colocated point-to-point correlation between seismic amplitude and water saturation variables is low because of different resolutions
Conclusions
• 1st PC and 1st CC can capture the spatial patterns of seismic and saturation time lapse variables
• High correlation between PC’s or CC’s can be used towards predicting saturations from time lapse seismic data
26
Available data:
• Water saturation at well locations (hard) :
• Time lapse of seismic amplitude (soft) :
• Water saturation at present time obtained from a flow simulator :
Saturation prediction (Future work)
2,tSw u
tseis ,u
1,tSw u
ttt 12
27
• Use as an external drift for kriging water saturation time lapse
21*
1021 ,,,, ttaattE SwSw uuuu with
1221 ,,,, tSwtSwttSw uuu
21*
12* ,,,, tttSwtSw Sw uuu
• Predict water saturation
Saturation prediction (Future work), cont.
• Predict time lapse by regression from known tseis ,u
tSw ,* u
*Sw
2121* ,,,, tttt SwSw uu locationswell:,
28
29
amplitude diff. impedance diff.
Sw diff. pressure diff. (Mpa)
4 year time lapses of amp, imp, Sw and Pres. at vertical section X=20
30
seis
sw
t1=Jan.1, 2000 t2=Jan.1, 2004
Original 1st PC 2nd PC
Correlation: 0.34 0.78 0.55