Post on 05-Jan-2016
description
5. AVO-AVA
• Introduction
• Weak-contrast, short spread approximation for reflection coefficient
• Information content
• Classification
• Tuning effect
• Examples
Introduction
• AVO (amplitude versus offset)
• AVA (amplitude versus angle)
The link between AVO and AVA is ray traycing in overburden.
Introduction
• Seismic lithology is the process by which rock properties such as lithology, porosity and pore fluid content are determined by analysis of seismic and other data.
• Ideally, seismic data would uniquely determine velocity, attenuation, and anisotropy for P-waves and S-waves as functions of angle.
• AVO has the advantage of being applicable to many conventional seismic data sets without the requirements of prohibitive acquisition, processing, and analysis costs.
Weak-contrast, short spread approximation for reflection coefficient
2 4
3
0 sin sin
sin sin
PP
PS
r R G K
r B C
2
2
1 10
2 2
12 2
2
1
21
22
R
G
K
B
P-wave: R(0) is intercept, G is gradient and K is curvatureC-wave: B is intercept and C is curvature
(5.1)
(5.2)
Information content
• Anomalously low Vp/Vs ratios caused by hydrocarbons produce anomalous AVO response
• However, Vp/Vs ratios can not be uniquely inverted from AVO data alone
Vp versus Vs
Castagna, 1993
Vp versus density
Castagna, 1993
Vp/Vs versus Vp
Figure 5.1. Vp/Vs ratio versus Vp for different lithology
Rss versus Rpp
Figure 5.2. S to P reflection coefficients for different lithology
Gas-brine properties distributions
Figure 5.3. Seismic properties for gas/brine sands
Some conclusions
• For large negative P-wave reflection coefficients, gas-sand and brine-sand reflection coefficients are distinct for all shale velocities. The lower the shale velocity, the greater the separation
• For small P-wave reflection coefficients, gas-sand and brine-sand reflection coefficients are well separated only for low shale velocities and only if the shale velocity is approximately known
• For large positive P-wave reflection coefficients, gas-sand and brine-sand reflection coefficients are well separated only for the lowest shale velocities and only if shale velocity is approximately known
AVO checklist• Is the expected rock properties variation sufficient to produce a
detectable AVO anomaly?• Can the same seismic response result from other earth models?• If AVO correctly predicts the occurence of hydrocarbons, what are
the chances that the saturation will be commercial?• Is there sufficient angular coverage for the event of interest?• How do I know that processing has preserved and isolated the ”true”
relative AVO response?• What is the seismic data quality?• Overburden? Processing?• Does the AVO anomaly conform the structure?• Do I understand what ”red” on the AVO display really means in
physical terms
AVO misconceptionsMyth• AVO does not work• Gas-sand amplitude increases
with offset• AVO can not be used to detect oil
sands• AVO does not work in carbonates• Land AVO is more difficult than
marine AVO• Vp/Vs is 1.6 for brine sands, 1.8
for dolomites, 1.9 for limestones, and 2 for shales
• Rp and Rs are readily extracted from R(0)
Reality• AVO does work under the right
circumstances• Gas-sand reflection coefficients
generally become more negative with increasing of offset.
• High GOR light oil-saturated rocks may exibit significant AVO anomalies
• There are some applications• The marine short-period multiples
are still a problem• Vp/Vs varies significantly• Rp and Rs can be extracted from
R(0) and G if Vp/Vs is kbown
Classification
R(0) G
+ +
+ -
- +
- -
Classification
Figure 5.4. For brine-saturated clastic rocks over a limited depth range in a particular locality, there may be a well-defined relationship between the AVO intercept (A) and the AVO gradient (B). A variety of reasonable petrophysical assumptions (such as the mudrock trend and Gardner’s relationship) result in linear A versus B trends, all of which pass through the origin (B = 0 when A = 0). Thus, in a given time window, nonhydrocarbon-bearing clastic rocks often exhibit a well-defined background trend; deviations from this background are indicative of hydrocarbons or unusual lithologies.
Classification
Figure 5.5. We propose that the classification of AVO responses should be based on position of the reflection of interest on an A versus B crossplot. First, the background trend within a given timeand space window must be defined. This can be done with well control if the seismic data are correctly amplitude calibrated, or with the seismic data itself if care is taken to exclude prospectivehidden hydrocarbon-bearing zones. Top of gas sand reflections then should plot below the background trend and bottom of gas sand reflections should plot above the trend. We can classify the gas sand response according to position in the A-B plane of the top of gas sand reflections.
Classification
Tuning
Tuning
Turbidite system example
0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0
-0,8
-0,6
-0,4
-0,2
0,0
B
R(0)
G
R(0
),G
,B
Net-to gross ratio
RPP
=R(0)+Gsin2R
PS=Bsin
Figure 5.6. AVO attributes versus net-to-gross
Stovas, Landro and Avseth, 2005
Seismic section
Figure 5.7. Seismic section from offshore Brazil
AVO attributes
7300 7400 7500 7600 7700 7800 7900 80003300
3200
3100
3000
2900
2800
2700
3300
3200
3100
3000
2900
2800
2700
CDP
3300
3200
3100
3000
2900
2800
27007300 7400 7500 7600 7700 7800 7900 8000
3300
3200
3100
3000
2900
2800
2700
Figure 5.8. AVO attributes sections
Inversion of AVO attributes
7300 7400 7500 7600 7700 7800 7900 80000,0
0,1
0,2
CMP
0,0
0,2
0,0
0,2
0,4
0,6
well
Oil content
S
N/G-0,02
0,00
0,02
-0,004
0,000
0,004
G
A
G
A
3200
3000
2800
Tim
e, s
3200
3000
2800T
ime,
s
Figure 5.9. AVO attributes inversion from the top reservoir
Inversion of AVO attributes (2)
7300 7400 7500 7600 7700 7800 7900 80000,0
0,1
0,2
CMP, m
0,0
0,2
0,0
0,2
0,4
0,6
well
Oil content
S
N/G
0,00
0,01
-0,004
-0,002
0,000
0,002
G
A
G
A
3200
3000
2800
Tim
e, s
3200
3000
2800T
ime,
s
Figure 5.10. AVO attributes inversion from the arbitrary reflection