1. Using 3-D Seismic Attributes
in Reservoir Characterization
Susan Nissen
Geophysical Consultant
McLouth, KS
Kansas Next Step 2007 Seminar: New Technology/Seismic/Seismic Interpretation
August 9, 2007
Hays, KS

2. Outline
• Brief overview of some reflection seismology basics
• What are seismic attributes and what physical
information can they provide?
• Methods of interpreting attributes from 3-D seismic
volumes
• Reservoir Characterization Examples
– Fault interpretation
– Porosity
– Bed thickness estimation
– Fracture delineation
• Conclusions

3. The Seismic Reflection Method
Source Receiver
ρ1V1
CMP
ρ2V2
Figure Courtesy of Industrial Vehicles
Vibrator truck (source) Geophone (receiver)
Moveout,
stack, migrate
CMP gather 3-D seismic data volume

4. Seismic Reflection Interpretation
Usually horizon-based 0.4
Horizon - the surface 0.5
Travel time (seconds)
separating two different
rock layers; also, the 0.6
reflection from this
surface.
0.7
0.8
ρ1V1 Horizon 1
ρ2V2
Depth
Horizon 2
ρ3V3
Horizon 3
ρ4V4

5. Seismic Applications in Petroleum Exploration
Structural analysis (1920s onward)
• study of reflector geometry
• used to identify faults and
locally high parts of formations
Seismic sequence stratigraphy (1970s onward)
• study of reflection sequences
• used to locate stratigraphic
traps and define the facies
framework of structural traps
deBruin et al. (2007)
Seismic attribute analysis (1970s onward)
• study of seismic attributes
• provides information related to structure,
stratigraphy, and reservoir properties

6. What are Seismic Attributes?
Any measurement derived from the
seismic data is a seismic attribute.
Seismic attributes typically provide
information relating to the amplitude,
shape, and/or position of the seismic
waveform.
Seismic attributes reveal features,
relationships, and patterns in the
seismic data that otherwise might not
be noticed.

7. General classes of attributes
1-D attributes - operate on a single stacked
seismic trace
2-D and 3-D attributes - calculated using
information from adjacent traces

8. Families of Seismic Attributes
Time Attributes (1930s) – related to the vertical position
of the waveform in the seismic section (e.g., horizon
time picks, isochrons)
Complex Trace Attributes q(t)
(1970s) – The seismic data
is treated as an analytic trace, A(t)
θ(t)
which contains both real and
r(t)
imaginary parts. Various
amplitude, phase, and
frequency attributes can be Taner et al. (1989)
calculated. Envelope: A(t) = [q2(t)+r2(t)]1/2
Instantaneous Phase: θ(t) = tan-1[q(t)/r(t)]
Instantaneous Frequency: ω(t)=dθ(t)/dt

9. Families of Seismic Attributes
Window Attributes (1980s) – attributes which summarize
information from a vertical window of data.
Fourier Attributes (1990s) – frequency
domain attributes obtained through
Fourier analysis (e.g., spectral
decomposition)
Multi-trace Attributes (1990s) - attributes calculated
using more than one input seismic trace, which provide
quantitative information about lateral variations in the
seismic data (e.g., coherence, dip/azimuth, volumetric
curvature)

10. Definitions of
selected attributes

11. Instantaneous Attributes
q(t)
A(t)
θ(t)
r(t)
Taner et al. (1989)
Envelope: A(t) = [q2(t)+r2(t)]1/2
Instantaneous Phase: θ(t) = tan-1[q(t)/r(t)]
Instantaneous Frequency: ω(t)=dθ(t)/dt

12. Spectral Decomposition
Uses the Fourier transform to 3D Seismic Volume
calculate the amplitude
} analysis
spectrum of a short time window
window covering the zone of
interest
Single All traces
trace
F1
The amplitude spectrum is
tuned by the geologic units
within the analysis window,
F2
so that units with different
rock properties and/or
thickness will exhibit different
amplitude responses. black = low amplitude
white = high amplitude

13. Seismic Coherence
A measure of the trace-to-trace similarity of the seismic
waveform within a small analysis window
3D Seismic Volume
fault = low coherence
For each point in a 3D seismic volume, compare the waveform
of adjacent traces (e.g., red trace compared to blue traces)
over a short vertical window
fault = low coherence
Coherence Cube
black = low coherence
white = high coherence

14. Volumetric Curvature
Curvature describes how bent a surface is at a
particular point and is closely related to the second
derivative of the curve defining the surface.
May be computed
2-D 3-D at any azimuth
Positive
about a point
Curvature
Cu Zer Zero
rv o Generally
atu Curvature
re computed normal
Negative to tangent plane
Curvature
Anticline
Di Principal
p
Pl pin
X Flat Curvatures (kmax
R
an g
e and kmin) can be
combined to
Syncline define other
Z Curvature (k)=1/R curvature
After Roberts, 2001
attributes
Sigismondi and Soldo, 2003
Volumetric curvature is computed for every point
within a 3-D seismic volume.

15. What physical information is
provided by seismic attributes?
Envelope- presence of gas (bright spots),
thin-bed tuning effects, lithology changes
Phase – lateral continuity of reflectors,
bedding configurations
Frequency – bed thickness, presence of
hydrocarbons, fracture zones
Spectral Decomposition – bed thickness
Coherence, Volumetric Curvature – faults,
fractures, lateral stratigraphic
discontinuities

16. Methods of interpreting attributes
from 3-D seismic volumes
Identify spatial patterns/trends in attribute data
– Cross-sectional view
– Map view (attributes extracted along horizon or from
zone of interest)
– 3D visualization
Tie attributes to well control using statistical
methods (e.g., crossplots)
Automatically analyze multiple attributes (with or
without well control)
– Geostatistics
– Principal component analysis
– Cluster analysis
– Texture analysis

17. Reservoir Characterization
Examples

18. Fault Interpretation – Offshore Trinidad
Seismic Time Slice Coherence Slice
Complex Coherence
faulting shows
difficult to lateral
detect on continuity
seismic of faults
Gersztenkorn et al., 1999

19. Limits of Porous Reservoir
--
Mississippian Dolomite Reservoir
Judica Field
Ness and Gove Counties, KS

20. Judica Field Stratigraphy
System
Penn.
LS Top Miss
Spergen GR
DOLOMITE
?
Judica
Warsaw
Mississippian
pay zone
Meramecian
Series
LS
20%
O/W -1938
Base Warsaw LS
Nt Phi Guard Res
Osagian
Series
After Dubois et al., 2003

21. Judica 3-D seismic survey
Top Mississippian structure
Dry holes on structural
high due to low porosity A
within reservoir interval
A'
A A'
0.80 s
Bhattacharya et al., 2004
Top Miss
Base Warsaw LS
0.85 s

22. 5
4.5
4
3.5
phi-h (porosity-ft)
3
2.5
Base Warsaw LS amplitude map
2
1.5
1
0.5
0
-18000 -16000 -14000 -12000 -10000 -8000 -6000 -4000
seismic amplitude - Base Warsaw LS horizon
Bhattacharya et al., 2004

23. Modeled variation in amplitude of Base Warsaw LS horizon
due to increase in porosity of reservoir zone
Velocity
model
Synthetic
seismic
section
-0.15
Base Warsaw LS
Amplitude
-0.2
-0.25
-0.3
Approximate porosity
of reservoir interval: 5% 25%

24. Top Mississippian Structure Map Base Warsaw LS Amplitude Map
Bhattacharya et al., 2004
Reservoir compartment
mapped from 3-D seismic
structure and amplitudes

25. Judica 3-D attribute analysis
results
Seismic amplitude of the base of Warsaw LS
correlates with porosity-thickness of the
Judica pay zone, providing a method for
discriminating between dry and productive
wells
A combination of seismic structure and
amplitude analysis allows us to better
delineate reservoir compartment boundaries

26. quot;Thin bedquot; thickness
estimation
--
Upper Cretaceous “D” Sand
Sooner Unit, Colorado

27. “D” Sand Reservoir
Upper Cretaceous
Incised valley fill
Fluvial and estuarine sediments
Cannon, 1998

28. quot;Dquot; sand thickness from wells
Objective
Determine “D” sand thickness between well control
points.

29. Sooner 3-D seismic survey
“D” sand isochron map
10 ms
7 ms

30. Unfortunately….
Over most of the 3-D survey
2.0
25
Maximum
area, the “D” sand is below
thickness
seismic resolution (a “thin
of “D” Sand
Maximum absolute amplitude
Two-way apparent thickness
20
bed”).
of composite wavelet
Below seismic resolution,
E
15
UD
reflections from the top and
T
1.0
bottom of the sand maintain a
PLI
S
AM
constant temporal separation,
ES
10
N
K
which is unrelated to the true
b/2
IC
TR
TH
sand thickness. Amplitude,
5
however, decreases with
decreasing bed thickness.
0
0
b/2 10
5
0 15 20 25
Two-way true thickness (ms)
Therefore….
Envelope and spectral
For our model wavelet (Ormsby 12/16-80/100):
decomposition, both related to
b/2 = tuning thickness = 7.9 ms (~ 53 ft)
amplitude, are likely to be
TR = temporal resolution = 7.2 ms (~49 ft)
better potential predictors of
“D” sand thickness

31. Envelope
- extracted along top “D” sand horizon
12000
0
“D” sand thickness
contours from wells

32. Discrete Fourier component thin bed
tuning analysis
40 Hz
Maximum thickness
of quot;Dquot; sand
30 Hz
envelope
amplitude
20 Hz
10 Hz
5
0 10 15 20 25
temporal thickness (ms)
After Partyka, 2001

33. Spectral Decomposition
- 50 ms window centered on “D” sand
20 Hz 30 Hz 40 Hz
0.8
Amplitude
50 Hz 60 Hz 70 Hz
0

34. Spectral Decomposition – 29 Hz
- 50 ms window centered on “D” sand
0.8
0
“D” sand thickness
contours from wells

35. Crossplots of attribute versus “D” sand thickness
Isochron
Envelope Spectral Decomposition – 29 Hz

36. Fracture Delineation
--
Mississippian Reservoir
Dickman Field
Ness County, Kansas

37. Dickman Mississippian Reservoir
Subjacent to regional pre-
Pennsylvanian
unconformity and karst
surface
Composed of multi-layered
shallow shelf carbonates
Production strongly
influenced by solution-
enhanced natural fractures
Supported by strong
bottom water drive
High water-cut production
C.I. = 10 ft 0.5 mile
(>94%)
Seismic depth map of top Mississippian
(pre-Penn unconformity surface)

38. Shale-filled fractures intersected by horizontal well
Ness County, KS
Karst-controlled
Karst-controlled
10-100 ft interval
10-100 ft interval
Provide a barrier to
Provide a barrier to
fluid flow
fluid flow
Carr et al., 2000

39. Seismic Attributes for Delineating
Faults and Fractures
Horizon Curvature Volumetric Curvature
Coherence
Calculated from Calculated directly
interpreted horizon from seismic volume
Extracted along
interpreted horizon

40. Volumetric Curvature – Gilmore City Horizon
Frequency-Azimuth Rose Diagram
fault
Length-Azimuth Rose Diagram
0.5 mile

41. Interpreted shale- and debris-filled
solution-enlarged fracture coincides
with NE-trending curvature
lineament
NE-trending lineament

42. Thickness of karst zone in well versus distance to
nearest NW and NE lineaments
Thicker karst zone
No relationship closer to lineaments

43. Oil production versus distance to nearest
NW and NE lineaments
A B
Increased oil
production farther
from lineaments
C
No relationship
0.5 mile

44. Water production versus distance to nearest
NW and NE lineaments
B
A
No relationship
C
Increased water production
near lineaments
0.5 mile

45. Dickman 3-D attribute analysis
results
NE-trending curvature lineaments appear to
be barriers to fluid flow, and may represent
shale-filled fractures.
NW-trending curvature lineaments appear to
represent open fractures, which serve as
conduits into the underlying aquifer.
Understanding the orientations of open and
filled fractures is an important pre-requisite
for effective reservoir management.

46. General conclusions about attributes
Attributes reveal information which is not readily
apparent in the raw seismic data
Dozens of seismic attributes can be calculated,
some of which are more useful than others
Attributes may be interpreted singly or using
multi-attribute analysis tools
Different attributes reflect different physical
properties of the underlying rock system
Attributes can aid in improving our
understanding of the reservoir
The specific attributes to use in a reservoir
characterization study will vary, depending on the
type of reservoir and the problem being
addressed

47. Acknowledgments
Tim Carr, Marty Dubois, and Saibal Bhattacharya,
Kansas Geological Survey
Kurt Marfurt and Chuck Blumentritt, University of
Houston
Mull Drilling Company, Inc.
Grand Mesa Operating Company
Seismic Micro-Technology, Inc.
IHS, Inc.
U. S. Department of Energy