7.Effective medium
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Transcript of 7.Effective medium
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7.Effective medium
• Upscaling problem
• Backus averaging
• O’Doherty-Anstey approximation
• Reuss and Voigt models
• Bio-Gassmann model
• Hertz-Mindlin model
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Upscaling problem
Does seismic wave see thethin-layering?
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Upscaling problem
• From microscopic to macroscopic scale
• From pore (graine) scale (millimeters)• From log-scale (centimeteers)
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Upscaling problem
• Traditionally, upscaling has meant upscaling of reservoir petrophysical properties and flow parameters dedicated for reservoir fluid flow simulation. However, due to the progresses mentioned above, there is a need to extend the concept of upscaling of geological models, for rock physics properties, seismic modelling and analysis. For instance, in 4D history matching, the need for up and downscaling might differ from the traditional concept of upscaling.
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Backus averaging
• Sequential Backus Averaging is a method of averaging the properties of a stack of thin layers so they are similar to average properties of a single thick layer.
Figure 7.1. The Backus averaging scheme
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Backus averaging• The advantage of Sequential
Backus Averaging is that no artificial "blocks" are introduced into the geology during the upscaling of the well-log data. In this example the density log is blocky, but the compressional- and shear-wave velocity logs have gradational tops and appear thicker. Blocking would distort the amplitudes. Furthermore, if blocking were based solely upon either the density or the sonic curves, the result would be wrong for the other curve.
Figure 7.2. The Backus averaging versus blocking averaging
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Backus averaging
• Thin beds appear thinner at oblique incidence angles.
Figure 7.3. The thin beds
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Backus averaging• At nonnormal incidence, the averaging operator must be adjusted to include the
apparent bed thinning.
Figure 7.4. Adjusting of averaging operator
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Backus averaging
• The offset synthetic shows differing AVO signatures for the same elastic property contrasts, associated with step-functions, blocky beds, and gradational interfaces.
Figure 7.5. AVO signatures from different models
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Backus averaging
ij kC , , k 1,M
ijˆ ˆC ,
(7.1)
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Backus averaging
133
21311
213313
13313
133
cccppcc
pccc
A
1
44cp
pB
How many combinations of the stiffness coefficients enter these matrices?
(7.2)
(7.3)
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Backus averaging
2 11 11 13 33
12 33
13 13 33
14 44
M
k kk 1
A c c c
A c
A c c
A c
1m d m
D
23
11 12
313
2
332
444
Ac A
A
Ac
A
1c
A
1c
A
(7.5)(7.4)
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The effective vertical velocity from Backus averaging
2 2 21 1
1
2 21 1
21
2 2 21 1
1 1
1 12
1 4
1
N Nj
j jj jEF j j
N Nj k j j k k
j k jTA j k k k j j
N Nj k jk
j k jTA j k jk
dd
V D v
d d v v
V D v v v v
d d r
V D v v r
Stovas and Arntsen, 2003
(7.6)
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Layering
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35 0,40
-0,04
-0,02
0,00
0,02
0,04
M1
Time, s
-0,04
-0,02
0,00
0,02
0,04
M2
-0,04
-0,02
0,00
0,02
0,04
M4
-0,04
-0,02
0,00
0,02
0,04
M8
Figure 7.6. The layering effect (each model computed by compression and doubling of the previous one)
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Reflection-transmission versus layering and contrast
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-2
0
2
M2
M1
Time, s
-2
0
2-2
0
2
M4
-2
0
2
M32
M28
M24
M20
M16
M12
M8
-2
0
2-2
0
2-2
0
2-2
0
2-2
0
2-2
0
2
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-1
0
1
M2
M1
Time, s
-0,5
0,0
0,5
-0,5
0,0
0,5
M4
-0,2
0,0
0,2
M32
M28
M24
M20
M16
M12
M8
-0,1
0,0
0,1
-0,1
0,0
0,1-0,03
0,00
0,03
-0,01
0,00
0,01
-0,005
0,000
0,005-0,003
0,000
0,003
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-0,5
0,0
0,5
M2
M1
Time, s
-0,5
0,0
0,5-0,5
0,0
0,5
M4
-0,5
0,0
0,5
M32
M28
M24
M20
M16
M12
M8
-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0
-1
0
1
M2
M1
Time, s
-1
0
1
-1
0
1
M4
-1
0
1
M32
M28
M24
M20
M16
M12
M8
-1
0
1
-1
0
1
-1
0
1
-1
0
1
-1
0
1
-1
0
1
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-2
0
2
M2
M1
Time, s
-2
0
2-2
0
2
M4
-2
0
2
M32
M28
M24
M20
M16
M12
M8
-2
0
2-2
0
2-2
0
2-2
0
2-2
0
2-2
0
2
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-1
0
1
M2
M1
Time, s
-0,5
0,0
0,5
-0,5
0,0
0,5
M4
-0,2
0,0
0,2
M32
M28
M24
M20
M16
M12
M8
-0,1
0,0
0,1
-0,1
0,0
0,1-0,03
0,00
0,03
-0,01
0,00
0,01
-0,005
0,000
0,005-0,003
0,000
0,003
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-0,5
0,0
0,5
M2
M1
Time, s
-0,5
0,0
0,5-0,5
0,0
0,5
M4
-0,5
0,0
0,5
M32
M28
M24
M20
M16
M12
M8
-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5-0,5
0,0
0,5
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0
-1
0
1
M2
M1
Time, s
-1
0
1
-1
0
1
M4
-1
0
1
M32
M28
M24
M20
M16
M12
M8
-1
0
1
-1
0
1
-1
0
1
-1
0
1
-1
0
1
-1
0
1
Figure 7.7. The reflection (bottom)and transmission (top) responses withdifferent contrasts (to the right is 4 times larger).
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Binary medium (multiples)
0,0 0,1 0,2 0,3 0,4 0,5
0M1
Time, s
0M2
0M3
0M4
0M5
0M6
0
Full reflected field
M7
0,0 0,1 0,2 0,3 0,4 0,5
0M1
Time, s
0M2
0M3
0M4
0M5
0M6
0
Primaries only
M7
0,0 0,1 0,2 0,3 0,4 0,5
0M1
Time, s
0M2
0M3
0M4
0M5
0M6
0
Multiples only
M7
Figure 7.8. Multiples contribution into the reflection response
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Propagation versus contrast
0,00 0,05 0,10 0,15 0,20 0,25 0,30 0,35 0,40 0,45 0,50
Time, s
r=0.87
second multiple
first multiple
Model: 256 x 1m
primary transmission
r=0.79
r=0.70
r=0.60
r=0.48
r=0.33
r=0.16
r=0.00
Figure 7.9. Transmission from thin layer model (change in r due to change in only)
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Effective properties versus net-to-gross
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0
2,10
2,12
2,14
2,16
2,18
2,20
linear
, g/cm3
Net-to gross ratio
0,91,01,11,21,31,41,5
non-linear
VS0
, km/s
2,00
2,05
2,10
2,15
2,20
2,25
non-linearV
P0, km/s
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0-0,08
-0,06
-0,04
-0,02
0,00
symmetric
Net-to gross ratio
-0,14
-0,12
-0,10
-0,08
-0,06
-0,04
-0,02
0,00
non-symmetric
Figure 7.10. Effective properties from Backus averaging in a binary medium
Stovas, Landro and Avseth, 2004
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Turbidite sequence from Ainsa basin
Figure 7.11. Turbidite system as an example of binary medium
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Binary medium
1 2
1 2 * *12 21
1 10 01
1 10 0
Si i
i i
r r a be e
r r b at t e e
1 2 2
1 2 2
1
22
2
2
22 2
1
1
1 2 sin
1 1
i i
i i
i
e r ea
r
re e irb e
r r
2 k k kfd v
(7.7)
(7.8)
(7.9)
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Binary medium
2
1 2 1 22
2
1 2 1 22
2Re cos sin sin
1
2Im sin cos sin
1
ra
r
ra
r
2 2det 1 S a b
2 2
2 2
22 2 *2
222 2 2* 2
2
2 sin2 4 sin
2 sin2 1
S S I I
i i
H
i i
r i r e ea b a b r
i r e e rab a b r
(7.10)
(7.11)
(7.12)
The propagator matrix is not unitary
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Binary medium
det 0 S I
21,2 Re 1 Re a i a
From the characteristic equation
we compute the eigenvalues
(7.13)
(7.14)
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Binary medium
21,2 Re Re 1
, Re 1
, Re 1
i
a a
e a
e a
The propagating regime with complex eigenvalues and the blocking regime with real eigenvalues:
(7.15)
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Propagating and blocking regimes
0 100 200 300 400 500 600 700-1
0
1
Frequency, Hz
-1
0
1-1
0
1-1
0
1-1
0
1-1
0
1-1
0
1
M1
M2
M4
M8
M16
M32
M64
r=0.87
0 100 200 300 400 500 600 700-1
0
1
Frequency, Hz
-1
0
1-1
0
1-1
0
1-1
0
1-1
0
1-1
0
1
M1
M2
M4
M8
M16
M32
M64
r=0.16
Figure 7.12. Re a as a function of frequency versus layering and contrast.Filled low frequency area relates to an effective medium, next coming gaprelates to transition medium. The interchanging of these zones is repeatable.
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Velocity limits
1 2
1 2
TA
dv
d dv v
21 2
2 2 2 21 2
1 1 4 1
1
EF TA
d d r
v v d v v r
1 2
1 22 d v v
vd d
The time average limit means thatthe pulse width is much less than the propagation time through the cycle)
The effective medium limit can be computed assuming phases beingsmall (low frequency limit)
The geometrical average limit
(7.16)
(7.17)
(7.18)
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Velocity limits versus volume fraction
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,01000
2000
3000
4000
5000
6000
7000
8000
r=0.16r=0.48
r=0.87
vRT
v
Vel
oci
ty, m
/s
Volume fraction
vRT
v v
EF
Figure 7.13. Velocity versus fraction. The larger reflection coefficient the more deviationbetween time-average and effective medium velocities. The position for maximum difference between them moving to high values of volume fraction with r increase.
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Stack of binary layers
1S UΛU
1 2, Λ diag
1 2
1 1
Ua b a b
The propagator matrix can be represented by the eigenvalue decomposition
(7.21)
(7.20)
(7.19)
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Stack of binary layers
1 22 2 21 2 11
22 21 21 22 2 1 2 22 1 21
1
Q S UΛ UM M M M
M M
M M M M
u u
u v u u u u
1 2 122
2 2 1 1
2 1112 22
2 2 1 1
D M M
M M
D M M
t qa a
br q q
a a
(7.23)
(7.22)
Product of M cycles
Transmission and reflection response
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Stack of binary layers
cos Re a
Propagating regime
Re 1a
1,2 ie
Blocking regime
Re 1a
1,2 e
cosh Re a
(7.24)
(7.25)
(7.26)
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Stack of binary layers
2
coscos
1sin
sin
M
CM
C b
1
2
2
2
sin
sin cos Im sin 1
sin
sin cos Im sin 1
i
D
i
D
et
M i a M C
b M Cer
M i a M C
Propagating regime
(7.28)
(7.27)
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Stack of binary layersBlocking regime
1
2
2
2
sinh
sinh cosh Im sinh 1
sinh
sinh cosh Im sinh 1
i
D
i
D
et
M i a M C
b M Cer
M i a M C
2
coshcos
1sinh
sinh
M
CM
C b(7.30)
(7.29)
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Stack of binary layers
0 100 200 300 400 500 600 700-1,0-0,50,00,51,0
Frequency, Hz
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
M1
M2
M4
M8
M16
M32
M64
r=0.87
0 100 200 300 400 500 600 700-1,0-0,50,00,51,0
Frequency, Hz
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
-1,0-0,50,00,51,0
M1
M2
M4
M8
M16
M32
M64
r=0.16
Figure 7.14. cos as a function of frequency versus layering and contrast(blue line is for the reference time average medium).
Stovas and Ursin, 2005
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Stack of binary layers
0 100 200 300 400 500 600 700-20-10
01020
Frequency, Hz
-20-10
01020
-20-10
01020
-20-10
01020
-20-10
01020
-20-10
01020
-20-10
01020
M1
M2
M4
M8
M16
M32
M64
r=0.87
0 100 200 300 400 500 600 700-2-1012
Frequency, Hz
-2-1012
-2-1012
-2-1012
-2-1012
-2-1012
-2-1012
M1
M2
M4
M8
M16
M32
M64
r=0.16
Figure 7.15. Amplitude C as a function of frequency versus layering and contrast(the gaps relates to the extremely large values).
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Stack of binary layers
0,00 0,02 0,04 0,06 0,08 0,10-101 TEM
TRT
M4
M2
M1
r = 0.87
Time, s
-101
-101
-101
M64
M32
M16
M8
-101
-101
-101
0,000 0,013 0,026 0,039 0,052 0,065 0,078 0,091-404 TEM
TRT
M4
M2
M1
r = 0.16
Time, s
-404
-404
-404
M64
M32
M16
M8
-404
-404
-404
Figure 7.16. Transmission response versus layering and contrast.Note the difference between TRT (transmission time for time average medium) andTEM (transmission time for effective medium). Weak transmission for r=0.87 andModel M16 is due to the wavelet spectrum is in the blocking regime, see Figure 7.12)
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Stack of binary layers
0,00 0,02 0,04 0,06 0,08 0,10-404
Time, s
-404
M1
M2
M4
M8
M16
M32
M64
-404
-404
2*TEM
-404
-404
-404
r = 0.87
0,00 0,02 0,04 0,06 0,08 0,10-1,50,01,5 2*TEM
Time, s
-1,50,01,5
M1
M2
M4
M8
M16
M32
M64
-1,50,01,5
-1,50,01,5
-1,50,01,5
-1,50,01,5
-1,50,01,5
r = 0.16
Figure 7.17. Reflection response versus layering and contrast.
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Stack of binary layers
0 100 200 300 400 500 600 7000,00,51,0
M64
M32
M16
M8
M4
M2
M1
r=0.87
Frequency, Hz
0,00,51,0
0,00,51,0
0,00,51,0
0,00,51,0
0,00,51,0
0,00,51,0
0 100 200 300 400 500 600 7000,00,51,0
M64
M32
M16
M8
M4
M2
M1
r=0.16
Frequency, Hz
0,00,51,0
0,00,51,0
0,00,51,0
0,00,51,0
0,00,51,0
0,00,51,0
Figure 7.18. Transmission (solid line) and reflection (dotted line) amplitudes as a function of frequency versus layering and contrast.
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Phase velocity
0 100 200 300 400 500 600 700
1500
3000
4500
6000
M64
M32
M16
M8M4
M2
M1
VEF
VTA
r=0.87
Frequency, Hz
0 100 200 300 400 500 600 7003600
3800
4000
4200
M64
M32
M16M8
M4
M2M1
VEF
VTA
r=0.16
Frequency, Hz
Figure 7.19. Phase velocity as a function of frequency versus layering and contrast.The effective medium is the low frequency part (around effective medium limit), thetransition medium is for dramatical increase in velocity and time average medium isfor oscillating part around time average velocity limit. Note that for small r, the widthof transition zone is narrow comparing with high r case.
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Transition from effective to time average medium
• Critical wavelength-spacing ratio:
/d=3 (Helbig, 1984)
/d=5-8 (Carcione et al., 1991)
/d=10 (Marion et al., 1992, 1994)
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Transition from effective to time average medium
Re 1a
1 21
tan tan2 2 1
r
r
1
1
1
2
1tan
1
1tan
2 1
ra
d r
ra
d r
(7.31)
(7.34)
(7.33)
(7.32)
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Transition from effective to time average medium
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9
0
4
8
12
16
20
24
28
32
36
40/d
Time average medium
Effective medium
Transition zone
Absolute value of r
Figure 7.20. Effective, transition and time average medium (volume fraction 0.5)versus contrast.
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O’Doherty-Anstey approximation
• Plane waves are normally incident on a sequency of horizontal layers. If the layers are lossless the shape of the frequency spectrum of the reflection response depends on the reflection coefficient series. The law of dependence can be found by solving the wave equation for the boundary and initial conditions of the seismic experiment. The O’Doherty-Anstey formula is an approximation to this law, and its validity would imply a lowpass spectrum of the reflection/transmission response if the reflectivity power spectrum has a highpass trend.
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O’Doherty-Anstey approximation
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O’Doherty-Anstey approximation
The ODA result for the retarded transmissivity caused by propagation through a set of layers is:
where N is the number of layers and R+(z) is the causal half of the normalized autocorrelation of the reflectivity function in a z-transform notation
z-transform:
(7.35)
(7.36)iz e
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O’Doherty-Anstey approximation
its Fourier representation
(7.37)
(7.38)
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O’Doherty-Anstey approximation
Now recall that reflectivity is a differential process, and if the elastic parameters are stationary in time, then
and our first, scaling, coefficient goes to zero leaving,
(7.40)
(7.39)
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O’Doherty-Anstey approximation
Figure 7.21. Examples of submillimetric fine layering from Beringen coal mine:Top – coarse sedimentary rock (sandstone),Bottom – fine sedimentary rock (shaly siltstone)
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O’Doherty-Anstey approximation
Figure 7.22. Thin micrograph of Rotliegend Sandstone (at 2990m depth).Left – laminated structure due to differences in grain size and packing.Right – details of two laminae, upper: coarser grained laminae with intergranular pores, lower: finer grained laminae with partly filled inrergranular space by detrital clays and dolomite.
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O’Doherty-Anstey approximation
Figure 7.23. Thin section micrographs. Scale = 0.25 mm. (A) Single lamina of very fine-grained, poorly sorted quarz sandstone in shale (2570m depth).(B) Two laminae of very fine-grained, well sorted quartz arenit interlaminated wirh sandy shale
(2920m depth).(C) Laminated, very fine grained sandstone and interbedded silty shale (2650m depth)
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O’Doherty-Anstey approximation
Figure 7.24. Thin section of Rotliegend sandstone (left) and P-wave increase with triaxial pressure increase
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O’Doherty-Anstey approximation
2 2
0 0Dkk k DPSDkk
1 1t , k, z exp i z exp r z r z
2 2
0
z''
z'
z
g12
g12
g11
g11
S
P
PP
P
P
PPP
P
P
P
Pg
12
g12
g22
g22
g12
g12
g11
g11
S
SS
SS S
SS
SSP
P
P
P
P
PPPP
z
z'
z''
z'''
0
(7.40)
Stovas and Ursin, 2004
Figure 7.25. Contrubution of first-order multiples into PP transmission (left) and PS reflection (right).
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O’Doherty-Anstey approximation
* *1
Q QN
N N
N jjN N
A B
B A
1
2
1 1
1
1 ...1
Nj k
i N Ni
N k jNk j k
jj
eA r r e
r
2
1
1
...
1
N jN
Nii
jj
N N
jj
e r e
Br 1
k
k jj
The propagator matrix for the stack of N layers (see eq. 7.7)
j j jd v(7.44)
(7.43)
(7.41)
(7.42)
Stovas and Arntsen, 2003
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O’Doherty-Anstey approximation
2 2
1 1
1det det
1
Q QN N
jN N N j
j j j
rA B
r
det 1QN
Determinant of propagator matrix
For binary medium
(7.46)
(7.45)
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O’Doherty-Anstey approximation
The elements of the total propagator matrix
12
1 1
1
1,1 1 ...1
Nj k
i N Ni
N k jNk j k
jj
eQ r r e
r
2
1
1
...
1, 21
N jN
Nii
jj
N N
jj
e r e
Qr
(7.48)
(7.47)
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O’Doherty-Anstey approximation
1 1
12
1 1
12,2
1 ...
N
D
j k
Ni
kN k
N N Ni
k jk j k
e rt Q
r r e
22
11
12
1 1
...
1, 2 2,2
1 ...
N jN
D
j k
Nii
jjN
N N N Ni
k jk j k
e r e
r Q Q
r r e
The transmission and reflection response:
(7.50)
(7.49)
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O’Doherty-Anstey approximation
1
1
1
D
N
kN k
rt
1
1
N
kk
r
11
The transmission amplitude
consists of two two terms:
attenuation due to transmission
attenuation due to scattering
(7.51)
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O’Doherty-Anstey approximation
The transmission phase
Imtan
1 Re
N N a
also consists of two terms
the time-average term
the scattering term
N
Imtan
1 Rea
(7.52)
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O’Doherty-Anstey approximation
1
1 1
1
1 1
1 1 Im 1 1 Imtan tan
Re 1 Re
sin 2 ...1 1
tan1 cos 2 ...
D
D TA
N N
k j j kk j k
N NTA
k j j kk j k
ta a
V D t V D
r r
aV D r r
The phase velocity
(7.53)
1
1 1
100
1 1
...1 1 1 2
lim1 ...
N N
k j j kk j k
N NTA
k jk j k
r r
V V V D r r
The zero-frequency limit
(7.54)
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O’Doherty-Anstey approximation
1 e
1
1 1
cos2
1
1
N N
k j j kk j k
r r NND k
k
t e r
1
1 1
2
0
N N
k j j kN k j k
r r
TAV V e
With approximation of the type
and transmission amplitude 7.51 we obtain
and zero-frequency limit 7.54 becomes
(7.57)
(7.56)
(7.55)
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O’Doherty-Anstey approximation
0 5 10 15 20 25 30 350,5
0,6
0,7
0,8
0,9
1,0
Tra
nsm
iss
ion
Frequency, Hz
0 5 10 15 20 25 30 351980
2000
2020
2040
2060
2080
2100
2120
data, = 2 weak-contrast O'Doherty-Anstey
Vel
oci
ty, m
/s
Figure 7.26. The phase velocity and transmission amplitude versus frequency. The comparison between exact, weak-contrast and O’Doherty-Anstey approximation. Note the low frequency range, less than 5 Hz.
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Reuss model
• Isostress model (valid for suspensions, with the fluid phase load-bearing), porosity is greater than critical porosity.
Ni
i 1R i
1 1 d
M D M
The critical porosity separates the mechanical and acoustic behavior into two disctinct domains. For porosity less the critical one the mineral grains are load-bearing.For porosity larger the critical one the sediment becomes a suspension.
(7.58)
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Voigt model
• Isostrain model (the load-bearing domain), porosity is less than critical porosity
N
V i ii 1
1M d M
D
(7.59)
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Thin-layer model
Figure 7.27. Snapshot for a thin layer model (f=30Hz)
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Reuss averaging
Figure 7.28. Snapshot for an effective Reuss model (f=30Hz)
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Voigt averaging
Figure 7.29. Snapshot for an effective Voigt model (f=30Hz)
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Average slowness
Figure 7.30. Snapshot for an effective average slowness model (f=30Hz)
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Average velocity
Figure 7.31. Snapshot for an effective average velocity model (f=30Hz)
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Backus average
Figure 7.32. Snapshot for an effective Backus model (f=30Hz)
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Bio-Gassmann model
• Biot (1956): frequency dependent velocities of saturated rocks in terms of the dry rock properties
• Gassmann (1951): the low frequency limit of Biot equations
Assumptions and limitations:- Rock is isotropic- All minerals making up rock have same bulk and
shear moduli- Fluid-bearing rock is completely saturated
Biot equations can be extended to VTI medium
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Gassmann model
2fr ma2fr
ma frma
f ma
K K1 4K
3 K KK 1
K K
2
frK
maK
fK
P-wave velocityS-wave velocityDensityBulk modulus of solid frameworkShear wave modulusIntrinsic modulus of solid matrixSaturated fluid bulk modulusPorosity
(7.60)
(7.61)
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Fluid densityMatrix densityOil densityWater densityOil bulk modulusWater nulk modulus
Gassmann model f ma1
f w o
1 S 1 S
K K K
f
ma
f w oS 1 S
wK
w
oK
o
Density
Fluid bulk modulus
Fluid density (7.64)
(7.63)
(7.62)
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Hertz-Mindlin model
• The Hertz-Mindlin model (Mindlin, 1949) can be used to describe the properties of precompacted granular rocks
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Poisson’s ratioShear modulusPorosityAverage number of contacts per grainHydrostatic confinig pressure
Hertz-Mindlin model
22 2
3eff 22
C 1K P
18 1
22 2
3eff 22
3C 15 4P
5 2 2 1
C 9
P
(7.66)
(7.65)
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Gassmann-Mindlin
Figure 7.32. The vertical P-wave and S-wave velocities versus water saturation and effective pressure changes.
Stovas and Landro, 2005
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Gassmann-Mindlin
Figure 7.33. Relative (to the initial model) changes in P-wave velocity, S-wave velocityand density versus water saturation and effective pressure changes. Within the Hertz-Mindlin model density does not change with pressure.
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Gassmann-Mindlin
Figure 7.34. The behavior of the PP and PS reflection coefficients with changing water saturation. The initial model reflection coefficients are plotted by circles. The curves are sampled in the water saturation change of 0.2.
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Gassmann-Mindlin
Figure 7.35. The behavior of the PP and PS reflection coefficients with changing effective pressure. The initial model reflection coefficients are plotted by circles. The curves are sampled in the change in effective pressure of 0.001 Gpa.
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Gassmann-Mindlin
Figure 7.36. Stacked PP reflection coefficient versus saturation and pressure
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Gassmann-Mindlin
Figure 7.36. Stacked PS reflection coefficient versus saturation and pressure