Multi-Component Seismic Anisotropy in a Mississippi Lime Play, North-Central Oklahoma Scott Singleton*, Shihong Chi, Lisa Sanford, ION Geophysical Corp.
Paul Constance, HighMount Energy
Summary
A high density, full azimuth, multicomponent survey was
designed, acquired and processed in the Mississippi Lime
play of north-central Oklahoma. Processing was carefully
performed in order to quantify compressional and
converted wave anisotropy. A large suite of log controls
enabled calibration of the seismic data and attributes to
rock properties. Analysis of the PP anisotropy at well
control confirmed that high Vfast velocities combined with
low anisotropy indicates relatively low fracture density.
Conversely, lower Vfast velocity combined with relatively
high anisotropy indicates higher relative fracture density.
Analysis of PS anisotropy demonstrates that the
predominant anisotropic signature present in PS data relates
to regional maximum horizontal stress (σh-max). However,
birefringence can be detected by the use of the transverse
component of PS data. Areas with high amounts of
transverse energy correlate to higher fracture density.
Therefore, by using both PP and PS velocity anisotropy,
operators can high-grade fracture density within prospects
whose production is known to be driven by the presence of
natural fractures.
Introduction
This paper showcases the benefits of multi-disciplinary
data integration and reservoir characterization within a
data-rich prospect. The prospect is a tight limestone
reservoir (the Mississippi Limestone) overlying an organic
calcareous mudstone (the Woodford Shale) in north-central
Oklahoma. The base data set is a 180 sq mi high density,
full azimuth, multi-component survey that was designed,
acquired and processed using a VectorSeis Nodal
acquisition system (Constance, et al., 2015). Processing
was carefully performed in order to quantify compressional
and converted wave anisotropy (Schapper, et al., 2009;
Simmons, 2009). The last step was a reservoir
characterization that integrated rock and fracture properties
with a full suite of calibration data from multiple wells,
including vertical and lateral FMI logs, mudlogs, Sonic
Scanners, chemical tracer in the laterals, completion results
and microseismic data.
In this paper we describe the results of our analysis of
seismic anisotropy within a portion of this data set. This
area surrounds a vertical saltwater disposal well (George 1-
23 SWD) and two laterals (George 23-1H and 23-2H).
Seismic Anisotropy
Both P-waves and S-wave converted energy (PS waves) are
sensitive to anisotropy, which causes both kinematic
(travel-time) as well as dynamic (amplitude) variations.
These variations can occur because of layered stratigraphy,
which causes vertical transverse isotropy (VTI), as well as
parallel sets of vertical fractures, which causes horizontal
transverse isotropy (HTI). In modern full-azimuth land data
VTI effects are typically removed by anisotropic migration
algorithms. Therefore, we will restrict our discussion below
to HTI anisotropy. Further, we will only consider kinematic
travel-time effects on the velocity field, leaving dynamic
amplitude effects (AVAZ) to another discussion.
P-Wave Anisotropy: Seismic P-wave energy travels faster
parallel to fractures and slower perpendicular to fractures,
provided the fractures are not cemented (i.e. open) and
especially if they are filled with fluids. Therefore, under
these circumstances, azimuthal gathers will show decreased
travel-time in the direction of fractures and increased
travel-time perpendicular to fractures (Schapper, et al.,
2009). The azimuth of fracturing can thereby be determined
and the difference between Vfast and Vslow directions
(known as PP velocity anisotropy) is proportional to
fracture density. This anisotropy can be calibrated with
fracture logs, thus giving an aerial fracture density map.
However, several conditions can interfere with this
calibration. First, fracture fill and cementation can vary
across an area and this will change the response of the
anisotropy. Second, many geologic basins contain multiple
sets of vertical (or nearly vertical) fractures at different
orientations. This violates the HTI assumption. It leads to a
decrease in Vfast velocity because all azimuths then may
encounter fractures, thereby reducing P-wave velocity in all
directions. It also will lead to a decrease in PP anisotropy
for the same reason. However, on the positive side, this
effect can be detected by co-rendering Vfast and PP
anisotropy; if both of these decrease then it is possible that
orthorhombic fracture symmetry (multiple orthogonal
vertical fracture sets) is being encountered. Third, layer
lithology can vary across the area, meaning that the
magnitude of Vfast can change due to a cause totally
unrelated to fracturing. Fourth, principle stress variations
are known to cause changes in velocity anisotropy,
meaning that we now have two factors unrelated to
fracturing that can cause variations in velocity anisotropy.
Applying these principles to the study area in the vicinity of
the George well pad, it is apparent there are distinctly
different conditions on either side of the major NE-trending
fault to the east of the well pad (center of Figure 1). To the
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Multi-Component Seismic Anisotropy
east of the fault the anisotropy is higher (3-8%) and a large
portion of the azimuths are in an easterly direction (which
is the orientation of σh-max) although there is significant
local variation, presumably in response to local fracturing.
In addition, the Vfast velocities are lower in magnitude
(16000-18000 ft/sec in areas adjacent to the fault) than on
the west side of the fault (up to 20000 ft/sec). However, to
the south of the southern lateral in the pad the velocities
decrease to 15000 ft/sec along with an increase in
anisotropy. The situation on the west side of the fault,
therefore, seems to indicate that fracture density is low over
much of the region except for the area to the south of the
southern lateral. This correlates well with data from an FMI
log in the lateral wellbore, which shows fracture density at
the heel of up to 5 fractures/ft, gradually decreasing
towards the toe to 1 fracture/ft or less (Figure 4, left panel).
PS-Wave Anisotropy: PS converted waves (known as C-
waves) are especially sensitive to subsurface fractures in
that both travel-time and polarization are affected
(Simmons, 2009). Vertical fractures cause the propagating
shear waves to be polarized into a fast shear wave (S1)
parallel to the fracture strike, and a slow shear wave (S2)
perpendicular to the fracture strike. Thus, upon propagation
through an anisotropic medium a shear wave will be split
into a fast component and a slow component and will
accumulate delay times between these two components as
they pass through this media (Crampin and Chastin, 2003).
The splitting estimation (and subsequent compensation)
operates on radial and transverse azimuth gathers.
Normally, all energy resides on the radial component
(which is the source-receiver orientation). However, in the
presence of subsurface HTI fractures C-wave reflection
energy polarizes onto the transverse component and
azimuth dependent, pseudo-sinusoidal travel-time
variations are introduced into the radial component. Energy
transferred into the transverse component has amplitudes
that reverse polarity at 90° intervals, which correspond to
azimuthal nodes on radial component sinusoids (Simmons,
2008). The time separation of the fast and slow C-wave
polarization is typically much greater than P-wave
anisotropy (travel time variations) although complex
surface statics, complex (orthorhombic) fracture patterns,
slow velocities, and other processing issues can cause C-
wave images to degrade.
Within the survey area, C-wave anisotropy azimuth is
predominantly easterly, although 10°-20° of northward
deviation is common (Figure 2). Given that σh-max is
almost due east, the east-northeast deviation of C-wave
anisotropy can be assumed to reflect northeasterly-oriented
faults and fractures associated with the large regional fault
in this vicinity (center of Figure 2). This azimuth data
seems to indicate that C-wave anisotropy in the survey area
primarily responds to regional stress and is only
secondarily affected by fracturing. However, before that
conclusion is reached we point out that the magnitude of
anisotropy (travel time variations) as detected and removed
by splitting estimation and compensation (indicated by
vectors in Figure 2) is about 6-8 msec, reaching about 15
msec in only one area. On the other hand, the magnitude of
transverse energy present in the Mississippi Lime section is
between 20-45 msec. This is a considerable difference and
indicates that the HTI assumption, or perhaps the velocity
model used in the processing of this data, is only partially
valid, representing only about 25% of the energy that has
been transferred to the transverse section.
So, therefore, the best measure of shear anisotropy in this
area would appear to be the transverse data. In section
view, this data clearly shows a large amount of energy
(amplitude) in the Mississippi Lime layer (up to 40-50
msec of differential travel-time) with some of that energy
also in the Woodford layer (Figure 3). Aerially this energy
is not uniform, with concentrations of transverse energy
generally to the south and west of the George well pad
(Figure 2). Given the theory outlined above regarding the
mechanism by which energy is transferred from a radially-
polarized orientation to a transversely-polarized orientation,
we might conclude that significant variations in fracture
density exist in this area. Calibration with FMI
substantiates this. The vertical FMI has fracture density
averaging 14-18 fractures/ft within the Mississippi Lime
which correlates to PS transverse energy magnitudes of
about 42-44 msec (Figures 3 and 4). The lateral FMI has
fracture density in the heel of about 3-5 fractures/ft (~34-36
msec) and 1 fracture/ft in the toe (~26-30 msec).
Conclusions
Seismic anisotropy is an important contributor to
unconventional reservoir characterization. It allows the
identification and quantification of fractures and/or stress to
be made away from well control, allowing decisions to be
made about favorable areas to drill within a prospect. In
this case, FMI and Sonic Scanner calibrated with both PP
and PS seismic anisotropy, allowing interpretation of
attribute responses that indicate greater or lesser fracture
density in the reservoir unit.
Acknowledgments
The authors thank EnerVest for allowing this work to be
published. There are a number of individuals at ION that
contributed to this work, including Rob Jefferson, Mark
Herb, Randy Thomas, Mike Stewart and Scott Schapper in
the processing group; and Felix Diaz, Howard Rael and
Jhon Rivas in the reservoir group.
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Multi-Component Seismic Anisotropy
Figure 1: PP Vfast (base colors) with PP velocity anisotropy vectors overlain for the Woodford. Top colorbar is anisotropy
magnitude from 0-8% (for vector colors), lower colorbar is Vfast magnitude from 14000 ft/sec to 19500 ft/sec. Wellbores used in
the survey are shown in left center with surface locations indicated by arrows. Note that PP anisotropy is significantly higher on
east side of fault while Vfast magnitudes overall are much less. For scale, the left lateral is 4,800’ long.
Figure 2: PS transverse energy (base colors) with PS anisotropy vectors overlain for the Mississippian and Woodford. Horizon shown is the Mississippi Lime (which is above the laterals) so the laterals are hidden (surface locations are indicated by arrows). Black line shows location of IL 266 which is used in Figure 3. Top colorbar is anisotropy magnitude from PS anisotropy
estimation (0-14 msec of differential travel-time), lower colorbar is PS transverse energy in amplitude units. Note transverse energy magnitude is somewhat different than anisotropy magnitude. This is because anisotropy estimation was calculated using
an HTI assumption which leaves a significant amount of birefringence unaccounted for.
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Multi-Component Seismic Anisotropy
Figure 4: Left basemap shows PP Vfast (brighter colors=slower velocities), right basemap shows C-wave transverse
energy (bright colors=large magnitude). Each figure shows two lateral wells; left well shows LWD gamma ray log (dark
gray) and FMI fracture density (red), right well shows microseismic events with their associated focal planes, sized by magnitude and colored by Hudson event type (open = purple, close = blue, shear + open = red, shear + close = orange,
undefined = green). Fault traces (in 3D) from seismic fault detection are in green. For scale, the left lateral is 4,800’ long.
Figure 3: PS transverse energy volume along IL 266 showing relevant horizons. See Figure 2 for location of this line.
Vertical well FMI shown; arrow indicates average max value which is approximately 14-18 fractures/ft. Lateral well FMI and LWD gamma ray shown on lateral. Arrow points to area with maximum fracture density, which is about 3-5
fractures/ft. The vertical and lateral FMI fracture densities calibrate to the PS transverse energy signature as shown
on the colorbar (1 fracture/ft ~ 26-30 msec, 3-5 fractures/ft ~ 34-36 msec, 14-18 fractures/ft ~ 42-44 msec). For
horizontal scale, the lateral is 4,800’ long. For vertical scale, the Mississippi Lime is about 200’ thick.
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EDITED REFERENCES Note: This reference list is a copyedited version of the reference list submitted by the author. Reference lists for the 2015 SEG Technical Program Expanded Abstracts have been copyedited so that references provided with the online metadata for each paper will achieve a high degree of linking to cited sources that appear on the Web. REFERENCES
Crampin, S., and S. Chastin, 2003, A review of shear wave splitting in the crack-critical crust: Geophysical Journal International, 155, no. 1, 221–240. http://dx.doi.org/10.1046/j.1365-246X.2003.02037.x.
Schapper, S., R. Jefferson, A. Calvert, and M. Williams, 2009, Anisotropic velocities and offset vector tile prestack migration processing of the Durham Ranch 3D, Northwest Colorado: The Leading Edge, 28, 1352–1361. http://dx.doi.org/10.1190/1.3259614.
Simmons, J., 2008, Case history: Converted-wave splitting estimation and compensation: 78th Annual International Meeting, SEG, Expanded Abstracts, 1033–1037.
Simmons, J. L. Jr., 2009, Converted-wave splitting estimation and compensation: Geophysics, 74, no. 1, D37–D48. http://dx.doi.org/10.1190/1.3036009.
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