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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