Stright, SCRF Affiliates Meeting: May 1, 2009
OBTAINING LOCAL PROPORTIONS FROM INVERTED SEISMIC DATA TOWARD PATTERN-BASED DOWNSCALINGOF SEISMIC DATA
Lisa Stright and Alexandre BoucherSchool of Earth SciencesSTANFORD UNIVERSITY
Stright, SCRF Affiliates Meeting: May 1, 2009
Multiple-point geostatistics - SNESIM
P(A = channel | B = TI ) = 4/5 = 80%P(A = non-channel | B = TI ) = 1/5 = 20%
Journel, 1992; Guardiano and Srivastava, 1992;
Strebelle, 2000, 2002
A = Categorical VariableB = Training imageC = Seismic Probability
Stright, SCRF Affiliates Meeting: May 1, 2009
Multiple-point geostatistics with soft data
P( A = channel | C = Seismic ) = 70%
P( A = channel | B = TI ) = 4/5 = 80%P( A = non-channel | B = TI ) = 1/5 = 20%
P( A | B, C ) - Combine with Tau Model - Use dual training images
1
0
Seismic Attribute
Pro
bab
ilit
y
0
1
A = Categorical VariableB = Training imageC = Seismic Probability
Stright, SCRF Affiliates Meeting: May 1, 2009
Scaling and probabilities?SeismicAttribute
Seismic Attribute
Pro
bab
ilit
y
0
1
47
%4
7%
47
%2
0%
20
%2
0%
PSand#1 #2 #3
47
%2
0%
Data Calibration Realization(s)
Stright, SCRF Affiliates Meeting: May 1, 2009
Assumptions – Scale???Probabilities and Facies can be scaled
to the model grid– Seismic informs a homogeneous
package– Homogeneous package can be
represented by “most of” facies upscaling in wells
Probabilities account for inexact relationship between wells and seismic attribute(s)
(1
0’s
)mete
rs
10’s of meters
Meters to 10’s of meters
1 m
Model scale
?
Seismic
Well
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
after Campion et al., 2005; Sprague et al., 2002, 2006
~ 1
00
m
~ 100 m
Stright, SCRF Affiliates Meeting: May 1, 2009
Proposed approach or methodology
Assumptions challenged when:– System is heterolithic (more than two categories)– Heterogeneities are smaller than seismic resolution (always?)– Multiple seismic attributes lumped into probabilities
Proposed Solution:• Create a multi-scale, multi-attribute well to seismic calibration• Use calibration to obtain local facies proportions at each
seismic voxel location
Advantages of proposed approach– Can use any number of seismic attributes– Not dependent upon forward modeling (but can leverage forward
modeling)– Uncertainty in tie between data types– Considers underlying cause of fine scale heterogeneity on coarse
scale measurement response– Powerful when combined with knowledge of data
(rock physics response, depositional setting and patterns)
Stright, SCRF Affiliates Meeting: May 1, 2009
Local Proportions from seismic attributes
Seismic Attributes
Seismic Attribute #1
Seis
mic
Att
rib
ute
#2
1) Directly from calibration2) From forward modeling
Data Calibration Realization(s)
?
Stright, SCRF Affiliates Meeting: May 1, 2009
Validation: Upper Cretaceous Cerro Toro Formation, Magallanes Basin
WL1 Mud Matrix Supported - Top of Slurry
WL1 Sandy Matrix Supported Top of Conglomerate
WL1 Debris Flow
WL2 Clast Supported Conglomerate
WL2 Clast Supported Conglomerate - Base of Slurry
WL3 Thin Beds - Sandstone/Mudstone/Conglomerate
WL3 Fine Grained Sandstone
WL3 Medium Grained Sandstone
WL3 Coarse Grained Sandstone
WL4 Thin Beds - Sandstone/Mudstone
WL5 Mud
Stright, SCRF Affiliates Meeting: May 1, 2009
Wildcat Lithofacies
Channel fill– Clast supported
conglomerate
– Conglomeratic mudstone
– Thick bedded sandstone
Out-of-channel– Interbedded sandstone
& mudstone
– Mudstone with thin sand interbeds
Stright, SCRF Affiliates Meeting: May 1, 2009
Rock Properties: Late Oligocene Puchkirchen Formation, Molasse Basin, Austria
Bierbaum 1
AI (g/cm3m/s)
5000 13000
10km
17km
Stright, SCRF Affiliates Meeting: May 1, 2009
Multi-scale, multi-attribute calibration
1.7
1.8
1.9
2
2.1
2.2
6 8 10 121.4
1.5
1.6
4
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
2.2
4 6 8 10 12
Vp /
Vs
Acoustic Impedance (g/cm3 m/s)
Stright, SCRF Affiliates Meeting: May 1, 2009
0.8 0.043 0.106 0.014 0.029 0 0 0 0.002 0.006
0.083 0.781 0.005 0.01 0.005 0 0 0 0 0.115
0.018 0 0.952 0.003 0.011 0.002 0 0 0.002 0.012
0.006 0 0.014 0.956 0.011 0.002 0 0 0.002 0.011
0.005 0 0.012 0.002 0.978 0.002 0 0 0.001 0
0 0 0 0 0 0.978 0.022 0 0 0
0 0 0.006 0 0.004 0.001 0.989 0 0 0
0 0 0.017 0 0 0 0 0.983 0 0
0 0 0.004 0.002 0.008 0.002 0 0 0.984 0
0.003 0.012 0.022 0.001 0 0 0 0 0 0.962
Create synthetic properties: Markov Chains
Synthetics
1.4
1.5
1.6
1.7
1.8
1.9
2
2.1
2.2
4 6 8 10 12
Vp /
Vs
Acoustic Impedance (g/cm3 m/s)
10763630
10723630
10683630
10643630
10603630
10563630
10523630
10483630
10443630
10403630
10363630
10323630
10283630
XLIL
10763630
10723630
10683630
10643630
10603630
10563630
10523630
10483630
10443630
10403630
10363630
10323630
10283630
XLIL
1.7
1.8
1.9
2
2.1
2.2
6 8 10 121.4
1.5
1.6
4
Stright, SCRF Affiliates Meeting: May 1, 2009
50 Hz15 Hz25 Hz
Forward and Inverse Modeling
WL1 Mud Matrix Supported - Top of SlurryWL1 Sandy Matrix Supported Top of ConglomerateWL1 Debris FlowWL2 Clast Supported ConglomerateWL2 Clast Supported Conglomerate - Base of SlurryWL3 Thin Beds - Sandstone/Mudstone/ConglomerateWL3 Fine Grained SandstoneWL3 Medium Grained SandstoneWL3 Coarse Grained SandstoneWL4 Thin Beds - Sandstone/MudstoneWL5 Mud
Stright, SCRF Affiliates Meeting: May 1, 2009
Realizations
Conglomerate(s)
Sandstones(s)
ThinBeds(s)
Stright, SCRF Affiliates Meeting: May 1, 2009
0
1
2
3
4
5
6
7
8
9
10
0 1 2 3 4 5 6 7
Mean Thickness (m)
Ab
solu
te E
rro
r in
Pro
po
rtio
nOutcrop results: Local Proportions
Prediction “good” when mean bed thickness is at least 1/10 of seismic resolution
WL1 Mud Matrix Supported - Top of Slurry
WL1 Sandy Matrix Supported Top of Conglomerate
WL1 Debris Flow
WL2 Clast Supported Conglomerate
WL2 Clast Supported Conglomerate - Base of Slurry
WL3 Thin Beds - Sandstone/Mudstone/Conglomerate
WL3 Fine Grained Sandstone
WL3 Medium Grained Sandstone
WL3 Coarse Grained Sandstone
WL4 Thin Beds - Sandstone/Mudstone
WL5 Mud
Stright, SCRF Affiliates Meeting: May 1, 2009
Subsurface Application: Single Well
6000
13000
Stright, SCRF Affiliates Meeting: May 1, 2009
Subsurface application: log validation
Realization #
Vp/Vs
IsIp
Proportion
Stright, SCRF Affiliates Meeting: May 1, 2009
Subsurface Application: Single Well
0
1
6000
13000
Stright, SCRF Affiliates Meeting: May 1, 2009
Stratigraphic Layer 3
Prop( Sand | Ip, Is, Vp/Vs )
Prop( ThinBeds | Ip, Is, Vp/Vs )Prop( Conglomerate | Ip, Is, Vp/Vs )
Prop( Mud/Disturbed | Ip, Is, Vp/Vs )
Stright, SCRF Affiliates Meeting: May 1, 2009
Compiling patterns from each layer
Stright, SCRF Affiliates Meeting: May 1, 2009
Summary and Conclusions
• Multi-scale, multi-attribute calibration– Extract more information from well to seismic calibration
to define inhomogeneous seismic “packages”– Explicitly handling scale differences in data to get full
information content of each data source– Aid in calibrating inexact relationship between wells and
seismic• Facies from wells/core• Multiple attributes from seismic
• Gaps of unsampled events filled with forward modeling
• Proportions and stacking patterns (vertical and lateral) need to be considered together
• Underlying “patterns” linked to better search uncertainty space
Stright, SCRF Affiliates Meeting: May 1, 2009
Future Work
Methodology Validation with Outcrop Models– What is the effect of seismic resolution and/or noise on the
predictions?– What controls when a proportion set is prediction correctly?
• Number of facies?• Bed thicknesses?• Stacking patterns?• Surrounding facies?
Calibration and Realizations– More intelligent selection of proportions based on spatial
relationship with adjacent cells – Leverage the tie between the proportion and the underlying
“pattern”
Determine which proportions are consistently predicted with multiple realizations and “freeze”– Analyze to better understand seismic “packages”– Remaining components defined by the model (Training Image)
Training Image generation and modeling
Stright, SCRF Affiliates Meeting: May 1, 2009
Industry Sponsor:Richard Derksen and Ralph Hinsch (RAG)
SPODDS Students:Dominic Armitage, Julie Fosdick,
Anne Bernhardt, Zane Jobe, Chris Mitchell, Katie Maier, Abby Temeng,Jon Rotzien,
Larisa Masalimova
Advising Committee:Stephen Graham, Andre Journel,
Gary Mavko, Don Lowe Alexandre Boucher
Acknowledgements
Stright, SCRF Affiliates Meeting: May 1, 2009
References
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Chugunova, T. L., and Hu, L. Y., 2008, Multiple-Point Simulations Constrained by Continuous Auxiliary Data, Mathematical Geosciences, v. 40, no. 2, p. 133-146.
González, E. F., Mukerji, T., and Mavko, G., 2008, Seismic inversion combining rock physics and multiple-point geostatistics, Geophysics, v. 73, p. R11.
Krishnan, S., 2008, The Tau Model for Data Redundancy and Information Combination in Earth Sciences: Theory and Application, Mathematical Geosciences, v. 40, no. 6, p. 705-727.
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