Estimation of Stress and Geomechanical Properties Using 3D Seismic Data

8/10/2019 Estimation of Stress and Geomechanical Properties Using 3D Seismic Data

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2012 EAGE www.firstbreak.org

first breakvolume 30, March 2012

Estimation of stress and geomechanicalproperties using 3D seismic data

David Gray,1*Paul Anderson,2John Logel,3Franck Delbecq,4Darren Schmidt4and Ron Schmid5

Introduction

In 2008, the lead author was asked to derive a method thatwould increase the relevance of seismic data in shale plays.

After a little research, it became apparent that geomechanical

parameters derived from seismic data could be very important

in shale plays. In most shale plays, and indeed in many other

plays, stimulation of the reservoir by hydraulic fracturing is the

primary mechanism used to increase rates of oil and gas returns

to the surface. In tight plays, such as shale gas, shale oil, and

coal-bed methane, stimulation is required to make the wells eco-

nomically viable. Rickman et al. (2008) described four geome-

chanical considerations necessary for the design of a stimulation

treatment. These are: brittleness, closure pressure, proppant size

and volume, and the location of the initiation of the fracture.

Seismic data allow for estimation of all of these values between

existing wells except the proppant size and volume.

The term brittle is defined by the Oxford Dictionary as

hard but liable to break easily and by Websters New World

Dictionary as easily broken or shattered. Both of these defini-

tions are appropriate for use in fracture stimulation, but are

subjective. Although the term brittleness is used frequently in

tight plays, an objective definition was missing until Rickman

et al. (2008) defined a relationship expressing brittleness as a

percentage and related it to Youngs modulus and Poissons

ratio, which can both be derived from seismic data (e.g.,

Mallick, 1995 for Poissons ratio; Gray, 2005a for Youngs

modulus). In this paper, a generalized form of the Rickmanet al. (2008) percentage brittleness is estimated from Youngs

modulus and Poissons ratio, which are both derived from

inversion of seismic data.

Closure pressure or closure stress is defined in the

Schlumberger Oilfield Glossary as an analysis parameter usedin hydraulic fracture design to indicate the pressure at which

the fracture effectively closes without proppant in place. In

general it is empirically related to the minimum horizontal

stress (e.g., Iverson, 1995). Expanding on Gray (2010b), a

method for the estimation from seismic data of all three prin-

cipal stresses, the vertical stress, v, the maximum horizontal

stress,H, and the minimum horizontal stress,

h, is introduced

here.

Warpinski and Smith (1989) state that in-situ stresses

are clearly the most important factor controlling hydraulic

fracturing. Iverson (1995) shows that knowledge of shear

anisotropy allows for a reformulation of the closure stress

equation to account for non-equal horizontal stresses,

which is generally the case in the earths crust, e.g., Bell et

al. (1994). A simplification of Hookes law using linear slip

theory (Schoenberg and Sayers, 1995) allows the estimation

of principal stresses from wide-angle, wide-azimuth seismic

data (Gray, 2011). The rock properties required in its imple-

mentation are derived from wide-angle seismic data, e.g.,

Gray (2005a). The method is demonstrated by estimating the

principal stresses and rock properties for the Second White

Speckled Shale using seismic data acquired in central Alberta,

Canada. The results show that only about one quarter of the

Second White Speckled Shale in the survey area will fracture

as a network, while most of the rest will fracture linearly andsome areas will not fracture at all, which implies that this

information can assist in the location of both wells and the

optimal location to initiate fractures, which is the last of the

AbstractPrincipal stresses, that is vertical, maximum horizontal and minimum horizontal stresses, and elastic moduli related to rock

brittleness, like Youngs modulus and Poissons ratio, can be estimated from wide-angle, wide-azimuth seismic data. This

is established using a small 3D seismic survey over the Colorado shale gas play of Alberta, Canada. It is shown that this

information can be used to optimize the placement and direction of horizontal wells and hydraulic fracture stimulations.

1 Nexen, 801 - 7th Avenue S.W., Calgary, Alberta, Canada, T2P 3P7.2 Apache Energy, Level 9, 100 St Georges Terrace, Perth W. Australia, 6000.3 Talisman Energy Norge, Verven 4, Sentrum, 4003 Stavanger, Norway.4 Hampson-Russell, Suite 510, 715 - 5th Avenue SW, Calgary, Alberta, Canada, T2P 2X6.5 CGGVeritas Canada Land Library, 715 - 5th Avenue S.W., #2200, Calgary, Alberta, Canada, T2P 5A2.* Corresponding author, E-mail: [email protected]


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say, the area of a seismic survey. This is because the seismic

response is calibrated to the well moduli through the process of

amplitude versus offset (AVO) inversion. AVO inversion using

wide angles can also be used to estimate density from which

we can, in turn, calculate the vertical stress, v, through integra-

tion. From v and the theory presented below, the minimum

and maximum horizontal stresses, hand H, respectively, canbe estimated from wide-angle, 3D seismic data.

If we assume that the rocks in-situ in the subsurface are

constrained horizontally, i.e., the horizontal strain is zero in

their natural state, and that the rocks are undergoing elastic

deformation, then we can estimate the in-situ stress state of

these rocks from elastic information (Iverson, 1995). In fact,

estimates of the three principal stresses can be obtained from

anisotropic elastic parameters (Iverson, 1995). Since elastic

information is derivable from seismic data via AVO inversion,

then the in-situ stress state can be estimated from anywhere

where seismic waves have intersected the rocks at a wide

(>40) angle. Furthermore, the anisotropic stress equations of

Iversen (1995) can be recast using parameters from linear sliptheory (Schoenberg and Sayers, 1995), which can be derived

from wide-angle, wide-azimuth, 3D seismic data (e.g., Lefeuvre

et al., 1992; Varela et al., 2009), as shown here.

Using linear slip theory, Schoenberg and Sayers (1995)

showed that Hookes Law can be simplified to:

(1)

where, iare the strains in the rock,

jare the stresses in the

rock, and S represents the compliance of the rock. Linear

slip theory simplifies the compliance terms by separating

it into two independent parts: Sb

the compliance of the

background rock, and Sf the compliance of the fractures

and micro-fractures in the rock (Schoenberg and Sayers,

1995). The incorporation of the concept of micro-fractures is

important because it allows for the relationship of fractures

to stress (e.g., Crampin, 1994), which is required for this

formulation relating linear slip theory to the in-situ principal

stresses. It is assumed that the maximum horizontal stress is

parallel to a single set of parallel vertical fractures or micro-

cracks and the minimum horizontal stress is perpendicular to

these fractures or micro-cracks (e.g., Schoenberg and Sayers,

1995). Expanding Equation (1) with linear slip theory leads

to the following system of equations:

(2)

Rickman et al. (2008) geomechanical parameters derivable

from seismic data for this shale gas reservoir.

In order to calibrate the closure stress to actual measure-

ments taken in the field, an additional term, called the tectonic

stress term, is often required to be added to the closure stress

equation. Blanton and Olson (1999) state: When independent

measures of horizontal stress magnitudes are available frommicro-fracs or extended leak-off tests, there is often a discrep-

ancy between the log-derived and measured values, leading to

the conclusion that the uniaxial strain assumption inherent to

[their] Eq. 1 is inadequate. In order to improve the estimated

stress values, an adjustment (calibration) is made by adding an

additional stress term to [their] Eq. 1, thereby shifting the profile

to match the measured values. In this paper, the strain-corrected

method of Blanton and Olson (1999) is used to calibrate the clo-

sure stress to known values. This method is adopted because it is

expected that strain will change smoothly across bedding planes,

whereas horizontal stress can change rapidly from formation to

formation due to changes in elastic rock properties.

MethodSeismic waves travelling through the earth create small, short-

term, strains in the rock that lie in the elastic regime of the

rocks. Therefore, using the assumptions outlined below, we are

able to calculate useful elastic moduli such as Youngs modulus

and Poissons ratio (Rickman et al., 2008) or the LMR (Lams

modulus, shear modulus, and density) parameters of Goodway

et al. (1997) (e.g., Gray, 2002). These moduli are described

as dynamic because they are measured by relatively high-

frequency measurements of velocities of elastic waves (Fjaer,

2009). These dynamic moduli measured by seismic and well

logs occur in the high frequency range and with low strain

amplitudes (Olsen et al., 2004).

When the rock is subject to long-term strain in geotechnical

tests, such as in compressive failure tests used to judge the

strength of rocks, static moduli are estimated from the slope

of the stress-strain relationship (Fjaer, 2009). Therefore, the

moduli related to hydraulic fracturing are most likely the

static moduli, because hydraulic fracturing takes some time to

build up the pressure required to fracture the rock. Olsen et

al. (2004) suggested that the static modulus is a combination

of the dynamic modulus and a non-elastic modulus related

to permanent deformation. The correction of the dynamic

moduli to equivalent static moduli is often done via such a

method or by scaling (e.g., Fjaer, 2009). In addition, there canbe a frequency-dependent effect related to the pore size, the

squirt-flow mechanism described by Dvorkin and Nur (1993).

Seismic-derived dynamic moduli should indicate lateral

changes in elastic moduli and brittleness, which is related to

them (Rickman et al., 2008) between wells. There are many

relationships between static and elastic moduli in the petro-

physical literature, suggesting that the best way to calibrate

them is by comparing local measurements of both. If such rela-

tionships can be determined, then they can be used to constrain

the extrapolation of static moduli away from wells within,


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by assuming that the vertical stress is set equal to the overbur-

den stress and horizontal strains are set to zero. Thus, the only

deformation allowed is uniaxial strain in the vertical direction.

When in-situ minimum horizontal stress measurements

such as micro-fracture(1) tests or extended leak-off tests are

available, there is often a discrepancy between the log-derived

values (and therefore, seismic-derived values, since they arebased on inversions to match log properties) and these meas-

ured values, leading to the conclusion that the uniaxial strain

assumption inherent is inadequate. In order to improve the

estimated stress values, the stress is shifted by adding an

additional tectonic stress term to the equation to match the

measured values (Blanton and Olson, 1999). Rather than

adding a tectonic stress term, we use the tectonic strain method

described by Blanton and Olsen (1999) to estimate a vertically

variable shift in stress. The primary rationale for using tectonic

strain rather than tectonic stress is that the horizontal strains

are expected to be more continuous than the horizontal stress-

es. This can be conceptualized through the realization, from

Equations (5) and (6), that the horizontal stresses are functionsof the continuous vertical stress multiplied by a function of the

discontinuous parameters, E, v, and ZN. Then again, the fact

that this calibration needs to be done implies that the rocks in

question are undergoing horizontal strain, thereby revising our

earlier assumption that the rocks are horizontally constrained.

Nevertheless, this strain can be captured in the above equations

by incorporating the tectonic strain term of Blanton and Olsen

(1999). Thereafter, at the well, the horizontal stresses are

calibrated to the well measurements and can then be used as

estimates of inter-well stresses and, therefore, for well planning.

It turns out that a differential horizontal stress ratio

(DHSR), i.e., the differential ratio of the maximum and

minimum horizontal stresses as shown in Equation (7), can

be calculated from seismic parameters derived from these

equations alone, without any knowledge of the stress state of

the reservoir, because vin Equations (1) and (2) cancels when

calculating it:

(7)

DHSR is a very important parameter in determining how a res-

ervoir is likely to fracture. In general, in hydraulic fracturing, it

is preferable if it is small. When the DHSR is large, hydraulic

fractures will tend to occur as non-intersecting planes parallel

to the maximum horizontal stress, since fractures tend to becreated parallel to it. In contrast, when the DHSR is small,

fractures induced by hydraulic fracturing will tend to grow

in a variety of directions and therefore intersect. This multi-

directional fracture network tends to provide much better

access to the hydrocarbons in the reservoir.

The knowledge of elastic parameters, such as Youngs

modulus or the shear modulus, indicates which rocks are brit-

tle and therefore likely to fail. Rickman et al. (2008) derived a

means of estimating brittleness, B, from logs. Equation (8) is a

generalized form of these equations. Brittleness is expressed

where E is Youngs modulus, v is Poissons ratio, and is

the shear modulus. The parameters ZNand Z

T represent the

normal and tangential compliances, respectively.

Compliance is defined by the Merriam-Webster Dictionary

as the ability of an object to yield elastically when a force is

applied. In the case of linear slip theory, this definition should

be applied to both the background material and the faces offractures, i.e., it is the ability of the background material and/

or a fracture in it to yield elastically when a force is applied.

The normal strain component perpendicular to a fracture or

a plane of weakness in the material is related to the materials

normal compliance, ZN. Shear strain components tangential to

a fracture or a plane of weakness in the material are related to

the materials tangential compliance, ZT.

Making the assumption that one principal stress is vertical,

so the other two are horizontal, Equation (2) may be used

to write the horizontal strains as functions of these stresses.

Given the assumption that the rocks, in-situ, are constrained

horizontally, these horizontal strains are equal to zero:

(3)

and

(4)

Solving Equations (3) and (4) for the principal horizontal

stresses yields the following equations:

(5)

and

(6)

All of the parameters in Equations (5) and (6) can be derived

from seismic data (e.g., Mallick, 1995 for v; Gray, 2005a for

E). Downton and Roure (2010) use modern wide-angle, 3D,

seismic data to estimate ZN. The vertical stress is generally

estimated by integrating logged density over depth and mul-

tiplying by the acceleration due to gravity. As density can be

estimated from seismic data (e.g., Van Koughnet et al., 2003),

the vertical stress can also be estimated integrating the density

estimated from seismic data. This means that the anisotropic

in-situ stress state of the rock and its elastic moduli and brittle-ness can be estimated between wells through the use of modern

3D seismic data.

Since we know how to derive all these parameters from

seismic data, we can also estimate all three principal stresses

from seismic data. These stresses need to be calibrated to

static stress measurements obtained from wells, and when this

is done it is found that the horizontal stresses are frequently

underestimated. Fortunately, the concept of tectonic stress has

already been introduced in the engineering world to deal with

this discrepancy. The formula for solving for stress is obtained


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Knowledge of the stress state prior to drilling can also

be used to predict areas at risk for wellbore failure, thereby

allowing for bypassing of these areas or preparation for the

drilling problems likely to be encountered therein. For example,

note that any of the formation breakdown pressures could be

negative, then the formation will likely fracture solely due to the

presence of the borehole. It is important to know this possibilitybefore drilling because there is a risk of lost circulation in that

borehole. This scenario does occur and is shown in the example

below. The hoop stress can also be significantly higher than

the closure stress. Therefore, it is important to be aware of this

prior to attempting to initiate hydraulic fracture. Wide-angle,

wide-azimuth, 3D conventional P-wave, or multi-component

seismic data allow the estimation of these parameters before

wells are drilled. For conventional seismic data, azimuthal

inversion is used. For multi-component seismic data, birefrin-

gence, registration, and inversion can be used. These parameters

must be calibrated to known points of stress and elastic moduli

within the reservoir. Then, using this additional knowledge, bet-

ter well planning should be achievable in order to optimize welllocation, direction and location of hydraulic fractures. How this

might be done is demonstrated in the following example.

ExampleA small, 9 km2, conventional P-wave, wide-azimuth, 3D

seismic survey shot southeast of Red Deer, Alberta, Canada

in the Western Canadian Sedimentary Basin (WCSB) is used

to demonstrate the method. The target area is the Cretaceous

Colorado Shale Group, highlighted by a dashed box in the

figures, which sits above weak shales of the Joli Fou Formation

and sandier Lower Cretaceous Mannville Formation. The

Mannville Formation sits above an unconformity, below which

the strata consist predominantly of carbonate rocks. It will be

shown that the Second White Speckled Shale unit is the most

brittle part of the Colorado Shale Group and will be the focus

of this example. Figure 1 shows the DHSR as plates displayed

over estimates of Youngs modulus for the entire 3D volume.

The direction of the plates indicates the estimated direction of

H, and their size, the magnitude of DHSR (Figure 2). These

show significant variations over this very small area, largely

driven by h(Figures 3 and 4).

Estimates of the principal stresses are derived as described

above and calibrated to stress estimates for the whole WCSB

available from the WCSB Atlas (Bell et al., 1994) using the

tectonic strain concept of Blanton and Olsen (1999). Localcalibration is preferred, but no wells with stress estimates in the

Colorado Shale Group are available in this area. For example,

subsequent stress estimation projects performed by the authors

have used information derived from local well-based closure

stress estimates to calibrate the minimum horizontal stresses.

Figures 3 and 4 show significant vertical and horizontal

variations inh. Very low values are associated with Mannville

Formation coals and the weak shales of the Joli Fou Formation.

High values are associated with carbonates in the bottom of the

figures below the unconformity.

as a percentage. These same equations can be applied to the

inversion results because they are tied to these same logs:

(8a)

(8b)

and

(8c)

where BEis brittleness estimated from Youngs modulus, B

nis

brittleness estimated from Poissons ratio and subscripts min

and max denote minimum and maximum values.

In order to determine how these rocks will fracture under

the stresses induced by hydraulic fracturing, knowledge of all

these parameters is important. To fracture the rock, the pres-

sure in the well must first overcome the hoop stress created in

the rocks around the borehole. Then it must be greater than

the far-field stresses away from the borehole in order to con-tinue its growth. The hoop stress and far-field stresses may be

similar, but the possibility exists that they can be completely

different from each other in both maximum stress direction

and magnitude. In the example below, the hoop stress is about

twice the far-field stress, so knowledge of both is critical. Such

differences can have a significant impact on wellbore design.

The hoop stress is the additional tangential stress in the

rock close to the borehole wall that is induced by the presence

of the borehole. It can be estimated once the principal stresses

are known. Since it has been shown above that the principal

stresses can be estimated from seismic data, the hoop stress

can also be estimated. The hoop stress,

, at the borehole

wall for three cases is considered here. For a vertical borehole,

the minimum hoop stress is oriented parallel to hand is given

by

(9)

For the top of a horizontal borehole oriented perpendicular to

H, with

v>

H,

(10)

For the side of a horizontal borehole oriented perpendicular to

H, with

H >

v,

(11)

The general case was given by Kirsch (1898). Following Lund

(2000) and in the example below, it is assumed that the differ-

ence, P, between the fluid pressure in the borehole and the

formation pore pressure is zero. It is necessary to overcome

the hoop stress in order to initiate a fracture in the formation;

therefore, these stresses can be considered as the formation

breakdown pressure, PFB

.


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estimated using the generalization of the approach of Rickman

et al. (2008), described above, combining Youngs modulus and

Poissons ratio as shown for these data in Figure 5. Furthermore,

there are significant variations in the DHSR ranging from

zero to over 100% (Figure 6). Both of these parameters have

significant impact on whether and how the rock will fracture:

higher values of brittleness indicate rocks that are more likely

to fracture and lower values of the DHSR indicate areas where

rocks will have a greater tendency to fracture into a network.

Clearly, we want to find areas where both these properties

These variations are probably due to different litholo-

gies being stressed differently as they drape over underlying

pinnacle reefs of the Leduc Formation (Gray, 2005b), dif-

ferential compaction stresses, stresses induced by underlying

salt collapse, or stresses due to the presence of open fractures

in this formation. The horizontal slice in Figure 1 shows 100%

variations in Youngs modulus ranging from 1224 MPa.

Variations in Youngs modulus and Poissons ratio should be

expected due to variations in lithology, porosity, fluid content,

fractures and cement in any sedimentary rock. Brittleness is

Figure 1Dynamic Youngs modulus from the 3D seismic volume shown in colour, with the scale numbered in units of GPa. Plates, indicated by the arrow, show

the differential horizontal stress ratio (DHSR). The size of the plate is proportional to the magnitude of the DHSR and the direction of the plate shows the

direction of the local maximum horizontal stress. The long axis of the survey is E-W and survey area is 9 km 2.

Figure 2Maximum horizontal stress, H, showing the target Colorado Shale and the Second White Speckled Shale (2WS) formation within it. The coloured stripes

at the well locations are the vertical stress, v, for reference.


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zone in the middle of Figure 7, should be drilled first, which

should move the best production forward, thereby increasing

net present value.

It is significant that there are such large differences in the

properties that are important for hydraulic fracturing over veryshort distances. Examination of the variations to the southwest

of Well 14-13 in the north-central part of Figures 7 and 4 show

a change from a very good area for hydraulic fracturing to a

bad area over a distance of less than 200 m, much shorter than

the length of most horizontal wells drilled in these plays. The

results indicate that most of the Second White Speckled Shale

will fracture with parallel fractures, implying that it will be very

important to direct the horizontal wells intended to be fractured

as nearly parallel to the average h direction as possible.

Therefore, knowledge of the rapid variation in the direction of

occur in order to find the best areas for hydraulic fracturing.

Youngs modulus is used as a proxy for brittleness throughout

the remainder of this study.

This requirement for high brittleness and low DHSR

suggests that a crossplot of these values should indicate areasthat are suitable for the creation of fracture networks. Figure 6

is a demonstration of such a crossplot using the seismic data

for the Colorado Shale Group, which consist primarily of

Late Cretaceous shales. The result of applying this crossplot to

the Second White Speckled Shale Formation of the Colorado

Group is shown in Figure 7. The zones and cut-offs in the

crossplot should be optimized through well control as the field

is developed. Areas where the DHSR is small and Youngs

modulus is large (green in Figure 7) are confined to small areas

of this already small survey. These areas, such as the green

Figure 3Minimum horizontal stress, h, showing the target Colorado Shale and the Second White Speckled Shale (2WS) formation within it. The coloured stripes

at the well locations are the vertical stress, v, for reference.

Figure 4Map of minimum horizontal stress, h, over the Second White Speckled Shale. Note its variability over a short distance from about 20 MPa around

well 14-13 to 26 MPa around well 6-13. North is to the top and east to the right. The red line towards the top of the figure shows the location of the sections

shown in other figures. After Gray 2010a.


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Figure 5Brittleness in percent, estimated using our generalization of the methods of Rickman et al. (2008). The green stripes at the well locations are there

because there is no equivalent brittleness log in the project.

Figure 6 Crossplot of DHSR versus Youngs

modulus. Preferred areas for hydraulic fractur-

ing are indicated in green, less desirable areas

in yellow, and poor areas in red.

Figure 7Map of Second White Speckled Shale showing zones highlighted in the crossplot in Figure 6. Green suggests where fracture swarms will form, red sug-

gests the rocks are more ductile and thus less likely to fracture, and yellow suggests where aligned fractures are likely to occur. There are considerable variations

in the north-central part of the survey, where the data suggest areas good and bad for hydraulic fracturing within about 100 m of each other.


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Kirschs (1898) concept of hoop stress (Figure 8) can be

used to estimate PFB

given the principal stresses that have been

estimated already. Hoop stress is generated by the removal of a

cylinder of material caused by the drilling of a well. By estimat-ing hoop stresses from the principal stresses derived earlier, we

can get an idea of what will happen while drilling before a well

is drilled. Here we assume that the pressure in the borehole is

close to the formation pressure in this estimation (although if

wellbore pressures, e.g. mudweights, are known then they can

be used). Since from the above analysis we now have estimates

of principal stresses everywhere, we can see what will happen

everywhere before a well is drilled and thereby avoid areas

where there are potential wellbore stability issues.

In Figure 9, we can see that there are potential vertical

wellbore stability issues (green zones indicating very low PFB

)

in vertical wells in the Mannville coalbeds (below the Colorado

h, or

H, as shown in Figure 1, is important information for

optimal hydraulic fracturing of this reservoir. This rapid varia-

tion in the stress direction is consistent with the interpretation

of the causes of fracture orientation in underlying coalbeds and

sandstones described by Gray (2005b). He ascribed these frac-

tures to local stress induced by drape over underlying pinnacle

reefs and differences in brittleness due to lithology. They couldalso be caused by differential compaction or collapse associated

with underlying salt dissolution.

Areas indicated in red in Figure 7 have a low likelihood

of fracturing and therefore should be assessed carefully before

drilling. There will likely be difficulty fracturing these rocks.

However, one possible reason for the low level of brittleness is

high total organic carbon content, which is potentially beneficial

to production. This reason is just one example of why all levels

of brittleness should be properly assessed before proceeding

with drilling, which can only be done with seismic data. Assume

that one well per square kilometre is required to develop this

shale gas play with drilling and completion costs of US$8 mil-

lion per well, which are similar to numbers that are commonlyreported (e.g., Crum, 2008), and assume that the areas in red

in Figure 7 will not fracture. This study shows that only three-

quarters of the prospect will fracture, meaning that two of the

nine wells should not be drilled. The cost saving, by not drilling

the two wells, would be $16 million, reducing the total cost to

develop this 9 km2area from $72 million to $56 million. These

savings easily pay for the acquisition, processing, and analysis

of the seismic data used to derive this information, and are in

addition to the uplift in net present value derived by drilling and

completing the best areas first and additional value of deriving

field scale development plans (e.g., orientation of horizontal

wells on a large scale for optimum pad placement and planning).

Figure 8The hoop stress concept: If a circular hole is made in a homogeneous

body experiencing a homogeneous stress field, stress will concentrate around

the hole since no force can be carried through the interior void. [This] Figure

shows the stress concentration around the hole in a body under uniaxial

compression, of magnitude 1Rin the far-field, in the x-direction (Lund, 2000).

Figure 9Fracture breakdown pressure (PFB) at the side of a vertical borehole. Areas shown in green indicate areas of very low or negative P

FBindicating a sig-

nificant risk of borehole failure at these locations. Many of these are in the Mannville coals at about 1000 ms, which is not surprising, but there are also some

in the primarily carbonate section under the unconformity marked by the blue line at about 1075 ms. This information has potential importance for drilling.

The coloured stripes at the well locations are the vertical stress, v, for reference. After Gray 2010a.


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DiscussionIt has been demonstrated that seismic data can be used to

estimate rock brittleness and stresses away from boreholes.The combination of these estimates allows for assessment of

the potential for hydraulic fractures and geomechanical issues

in boreholes before drilling any wells. An example from the

Colorado Shale of Alberta is used to demonstrate the method.

This method is based on physics and so is applicable in any shale

gas play as well as any other play where hydraulic fracturing is

being considered, such as tight gas sands, coalbed methane, and

carbonates, and where stress or geomechanics are at issue, such

as in heavy oil plays and new exploration. The seismic data

should be used to extrapolate information derived at wellbores

Shale), which are expected, and in the carbonate section below

the unconformity at the base of the Mannville section, which

is unexpected. We can also drill wells in areas where the hoopstress is in a range such that the pressure generated in the well-

bore during drilling is lower and the pressure generated during

hydraulic fracturing is sufficient to overcome it and break the

rock without damaging the casing. Since horizontal wellbores

will be drilled here, we should examine the fracture breakdown

pressure for a horizontal wellbore (Figure 10) before drilling.

We can also estimate whether the fracture will initiate in the

top of the borehole or on its side (Figure 11). The closure stress

and rock properties, derived earlier, predict how the fracture

will behave away from the borehole.

Figure 10PFB

at the side of a horizontal borehole. Lower values indicate where it is easier to initiate fractures from the side of the borehole. Values ranging

from about 20 MPa to over 100 MPa show that it is important this information be considered in well planning. The target Second White Speckled Shale (2WS)

Formation has moderate PFBof 40-50 MPa, which is significantly greater than its closure stress, indicating that a significant amount of force will be required toinitiate the fracture at the borehole, but that once the fracture is initiated, then it should continue to propagate until the pressure drops below the closure

pressure of 20-50 MPa. The coloured stripes at the well locations are the vertical stress, v, for reference. After Gray (2010a).

Figure 11Difference of fracture breakdown pressure for a horizontal well, PFB

(side) PFB

(top). Positive values mean that the fracture will initiate out of the sides

of a horizontal borehole. Negative values mean that fractures will initiate from the top of the borehole.


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Received 24 January 2011; accepted 10 January 2012.

doi: 10.3997/1365-2397.2011042

to the inter-well regions. However, this analysis can be done

without well information using measured seismic velocities and

assumed petrophysical relationships. Once principal stresses are

estimated, other useful stress estimates, such as hoop stress, can

be used to predict how the well will behave while drilling and

under stimulation.

ConclusionsThere is a tremendous amount of information on stresses and

rock properties that can be estimated from wide-angle, wide-

azimuth, 3D seismic data. The horizontal stresses derived from

this method need to be calibrated to stress values estimated

from well data. Once this is done, these stresses can be used to

estimate various stresses likely to be encountered between wells.

Furthermore, the elastic properties derived during this process,

such as shear modulus, Youngs modulus, and Poissons ratio,

which also require static moduli for calibration, can be used to

estimate the brittleness of the rock between wells. This informa-

tion can then be used to plan well paths and optimize hydraulic

fracture programmes.

AcknowledgementsWe thank CGGVeritas, EnCana, Apache, Talisman Energy,

Magnitude, Fairborne Energy, Nexen, Bill Goodway, Doug

Anderson, Ron Larson, Jonathan Miller, Louis Chabot, Eric

Andersen, Jared Atkinson, John Varsek, Tobin Marchand,

Dominique Holy, Colin Wright, Wayne Nowry, Jessie Arthur,

Philip Janse, Christophe Maison, Dragana Todorovic-Marinic,

Christian Abaco, Lee Hunt, Scott Reynolds and Jon Downton.

Note(1) A short duration, small volume fracturing operations

where a small amount (

Estimation of Stress and Geomechanical Properties Using 3D Seismic Data

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