SPE 166332-MS Characterizing Hydraulic Fracturing …...SPE 166332-MS 3 relationships are not well defined, and it is not clear how the importance of shear stimulation for a formation

SPE 166332-MS

Characterizing Hydraulic Fracturing with a Tendency for Shear Stimulation Test Mark McClure, SPE, University of Texas at Austin, Roland Horne, SPE, Stanford University

Copyright 2013, Society of Petroleum Engineers This paper was prepared for presentation at the SPE Annual Technical Conference and Exhibition held in New Orleans, Louisiana, USA, 30 September–2 October 2013. This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contents of the paper have not been reviewed by the Society of Petroleum Engineers and are subject to correction by the author(s). The material does not necessarily reflect any position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the written consent of the Society of Petroleum Engineers is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract The classical concept of hydraulic fracturing is that a single, planar, opening mode fracture forms. In recent years, there has

been a growing consensus that in many formations, natural fractures play an important role during stimulation. There is not

universal agreement on the mechanisms by which natural fractures affect stimulation, and these mechanisms vary depending

on formation properties. One potentially important mechanism is shear stimulation, where an increase in fluid pressure

induces slip and permeability enhancement on preexisting fractures. We propose a Tendency for Shear Stimulation (TSS) test

as a direct, relatively unambiguous method for determining the degree to which shear stimulation contributes to stimulation in

a particular formation. In the TSS test, fluid is injected at a bottomhole pressure that is intentionally maintained below the

minimum principal stress, ideally at a constant pressure. Under these conditions, shear stimulation is the only possible

mechanism for permeability enhancement (except perhaps thermally induced tensile fracturing). Standard pressure transient

tests could be performed before and after the TSS test to estimate formation permeability. The flow rate rate transient during

injection may also be interpreted to identify shear stimulation. Numerical simulations of shear stimulation were performed

with a discrete fracture network model that couples fluid flow with the stresses induced by fracture deformation. These

simulations were used to qualitatively investigate how shear stimulation and fracture connectivity affect the results of a TSS

test. The simulations neglected matrix flow and were two-dimensional, which made it impossible to forward simulate the

transients that would be expected in practical application. Modeling improvements will make this possible in future work.

Two specific field projects are discussed as examples of a TSS test, the Enhanced Geothermal System (EGS) projects at Desert

Peak and Soultz-sous-Forêts. At Soultz, the formation had a high TSS, and at Desert Peak, formation TSS was minimal.

Introduction Classically, hydraulic fracturing has been conceptualized as creating a single, planar, opening mode tensile fracture. But in

low matrix permeability applications such as oil or gas production from shale or geothermal production from granite, the

process of hydraulic stimulation has been conceptualized as creating a complex network of newly forming fractures and/or

natural fractures that slip and open in response to injection (Fisher et al., 2004; Bowker, 2007; Gale et al., 2007; Cipolla et al.,

2008; King, 2010; Pine and Batchelor, 1984; Murphy and Fehler, 1986; Brown, 1989; Ito, 2003; Ito and Hayashi, 2003; Evans,

Moriya, et al., 2005; Ledésert et al., 2010). The precise geometry of these networks is a major uncertainty. The networks

cannot easily be observed directly in the subsurface; it is difficult to know how laboratory experiments relate to the reservoir

scale, and microseismic interpretations with respect to network geometry are nonunique.

In shale, it is widely believed that new fractures form and propagate through the formation, but apparently there is

disagreement about the role of preexisting fractures and how they contribute to production.

One potentially important process is termination of propagating natural fractures against preexisting fractures. This has been

observed in laboratory experiments (Blanton, 1982; Renshaw and Pollard, 1995; Zhou et al., 2008; Gu et al., 2011), mine-back

experiments (Warpinski and Teufel, 1987; Warpinski et al., 1993; Mahrer, 1999; Jeffrey et al., 2009), and computational

investigations (Dahi-Taleghani and Olson, 2009; Gu and Weng, 2010; Fu et al., 2012). If termination occurs, then it may be

difficult for a single, continuous, large fracture to propagate across the formation, and pathways for flow through the reservoir

may occur through both new and preexisting fractures (a process we refer to as Mixed-Mechanism Stimulation, MMS). This

process could play an important role in generating stimulated fracture surface area and therefore increasing recovery. MMS

2 SPE 166332-MS

has been modeled at the field scale by several authors (Damjanac et al., 2010; Weng et al., 2011; Wu et al., 2012; Section

2.3.3.2 of McClure, 2012).

In contrast to the MMS concept, some authors have modeled stimulation in shale with a single, large, continuous tensile

fracture per stage (Warpinski et al., 2001; Palmer et al., 2007; Rogers et al., 2010; Nagel et al., 2011; Roussel and Sharma,

2011). With this approach, a problem arises because high production rates from low permeability shale formations apparently

require more stimulated fracture surface area than can be explained by a single, linear fracture per stage (Mayerhofer et al.,

2010; Fan et al., 2010; Cipolla et al., 2010). This problem can be resolved by postulating that there are secondary fractures

surrounding the large primary fracture that contribute significantly to production. Some modelers are agnostic about the

nature of the secondary fractures (Warpinski et al., 2001), and others suggest the secondary fractures may be newly forming

tensile fractures (Roussel and Sharma, 2011). Other authors have modeled secondary fractures as shear stimulating (or

possibly opening) preexisting fractures (Palmer et al., 2007; Rogers et al., 2010; Nagel et al., 2011). We refer to this latter

mechanism as Primary Fracturing with Shear Stimulation Leakoff (PFSSL). Other combinations of mechanisms could be

Primary Fracturing with Mixed-Mechanism Leakoff or Primary Fracturing with Secondary Tensile Fracturing.

Projects where hydraulic stimulation is performed for geothermal energy production are often referred to as "Enhanced

Geothermal Systems," or EGS. The original concept of EGS, which remains the most common, was to perform hydraulic

fracturing in deep wells drilled into the crystalline basement (3 - 5 km depth). The potential size of the geothermal resource is

very large, because temperatures at this depth are high enough for geothermal energy production across a significant

percentage of the Earth's surface. However, the natural permeability in the crystalline basement is typically very low, and so

hydraulic stimulation is needed to improve economic performance (Tester, 2007). EGS is most often performed by injecting

liquid water into a long openhole section of a wellbore (vertical or gently inclined) without using proppant.

Most authors believe that during EGS stimulation in crystalline formations, the dominant mechanism of stimulation is induced

slip on preexisting fractures (which we refer to as Pure Shear Stimulation, PSS). Early EGS experience indicated that flow

from the wellbores was localized at preexisting fractures and that microseismic hypocenter locations were not consistent with

the vertical, penny-shaped tensile crack model of hydraulic fracturing (Murphy and Fehler, 1986; Pine and Batchelor, 1984).

Some early authors postulated a "dendritic" network model of stimulation (Murphy and Fehler, 1986), and authors eventually

converged on the shear stimulation idea, at the exclusion of new propagating fractures (Pine and Batchelor, 1984; Lanyon et

al., 1993; Willis-Richard et al., 1996; Ito and Hayashi, 2003; Tester, 2007). Since then, most EGS modeling has used this

conceptual model. The modeling workflow is to stochastically generate a realization of the preexisting fracture network and

then simulate flow and shear stimulation in the network (Kohl and Hopkirk, 1995; Bruel, 1995; Bruel, 2007; Kohl and Mégel,

2007; Rahman et al., 2002; Jing et al., 2000; Cladouhos et al., 2011; Zhou and Ghassemi, 2011; Rachez and Gentier, 2010;

Riahi and Damjanac, 2013).

McClure and Horne (2013) argued that the Pure Shear Stimulation is not as universal in crystalline EGS as the conventional

wisdom suggests, and that in many or most projects, Mixed-Mechanism Stimulation occurs, with both new and preexisting

fractures playing an important role. McClure and Horne (2013) pointed out that many geological conditions must be present

for Pure Shear Stimulation to be possible, and these conditions cannot always be expected to be satisfied. Furthermore, in

most EGS projects, the bottomhole pressure has exceeded the minimum principal stress, for example, the projects at Hijiori,

Fjallbacka, Le Mayet, Rosemanowes, Fenton Hill (Willis-Richards et al, 1995), Ogachi (assuming vertical stress gradient of 25

MPa/km) (Kaieda et al., 2010), Desert Peak (Chabora et al., 2012), and Groβ Schonebeck (Zimmermann et al., 2008).

Overall, shear stimulation is suspected of being important for hydraulic stimulation in both shale and geothermal resources, but

the role of shear stimulation is not fully understood. If shear stimulation contributes significantly to production in shale, this

would have important implications for stimulation design and formation assessment. TSS should depend on various

geological parameters, and geologists need to know whether to incorporate these variables into their resource assessments.

Modelers need to know whether to incorporate shear stimulation into their simulations. Generally, concepts about shear

stimulation shape the physical intuition of engineers making design decisions.

In geothermal, most EGS modeling neglects propagation of new fractures, and recent EGS projects have been focused on

trying to intersect large faults because they are seen as being most favorable for shear stimulation. If tensile fracturing

(perhaps Mixed-Mechanism Stimulation) was reconsidered as a viable mechanism, it would open up new possibilities for

overall system design (such as using proppant).

The tendency for shear stimulation (TSS) must depend on many geological factors. At a minimum, shear stimulation (either

PSS or PFSSL) cannot occur without self-propping fractures that are well oriented in the local stress state to slip in response to

fluid increase. For Pure Shear Stimulation to occur, the formation must be capable of accepting fluid rapidly enough to

prevent excessive pressure buildup, which would result in propagation of new fractures (McClure and Horne, 2013). The

importance (or lack therof) of shear stimulation in hydraulic stimulation must depend on the geological parameters, but these

SPE 166332-MS 3

relationships are not well defined, and it is not clear how the importance of shear stimulation for a formation could be

measured or quantified.

Because the tendency for shear stimulation to occur depends on geological setting, it could be considered a formation property.

TSS could be estimated through indirect analyses such as Coulomb stress analyses of the local fracture network (Evans, 2005;

Ito and Hayashi, 2003) and rock mechanics testing of core to evaluate the tendency for self-propping (Lutz et al., 2010). But

ultimately, these techniques require interpretation, there are important factors that could be difficult to characterize, and it is

unclear how different factors could be integrated into a single assessment. It may be possible to develop methodologies to

assess TSS, but these efforts will be hampered without a way to calibrate them with direct measurements of TSS.

We propose that a "Tendency to Shear Stimulation Test" (TSS Test) could be used in the field to evaluate the importance of

shear stimulation practically and unambiguously. In a TSS Test, fluid would be injected into an openhole section of the

wellbore at a fluid pressure near to, but less than, the minimum principal stress. Under these conditions, shear stimulation

would be the only possible mechanism of stimulation. The formation permeability could be measured with pressure transient

techniques before and after the stimulation treatment, and the change in permeability could be used to assess TSS. The

behavior of the injection rate over time during the TSS test could be used to diagnose TSS and possibly some additional

information about the properties of the formation.

To investigate the properties of TSS Tests, three simulations were performed using CFRAC, a two-dimensional discrete

fracture network simulator that fully couples fluid flow and the stresses induced by fracture deformation (McClure, 2012).

The simulations were configured to loosely resemble the reservoir parameters at the Desert Peak EGS project. At the Desert

Peak project, fluid injection was intentionally performed with a bottomhole pressure less than the minimum principal stress

(Chabora et al., 2012; Benato et al., 2013), which makes it a prototype example of a TSS test.

Several simplifications are made by CFRAC (most importantly, it neglects matrix flow and is two-dimensional), which limit

its ability to be used for forward modeling of reservoir transients (either wellbore pressure or production rate). Therefore, the

simulations in this paper are intended to be interpreted qualitatively. In future work, we plan to repeat these simulations with a

three-dimensional model that includes matrix flow to do realistic forward models of the pressure and rate transients before,

during, and after the TSS test. CFRAC is used rather than a more conventional code because the character of the overall shear

stimulation process is significantly affected by (1) idiosyncracies of flow in fracture networks and (2) stresses induced by

deformation.

Methodology

Computational Model The full details of CFRAC are summarized in Chapter 2 of McClure (2012), and only a brief overview is given in this section.

The model assumes single-phase liquid water (no proppant), isothermal, Darcy flow in the fractures, and no flow in the matrix

around the fractures. Gravity was neglected, but this had a minimal effect on the simulations because fluid density variations

were small. Stresses induced by fracture deformation are calculated with the Shou and Crouch (1995) Displacement

Discontinuity (boundary element) method using quadratic basis functions assuming homogeneous, isotropic, linear elastic

deformation. A code called Hmmvp (Bradley, 2012) is used to very accurately and efficiently approximate the matrices of

interaction coefficients arising from the Displacement Discontinuity method, which increases efficiency significantly. When

creating the matrix approximations for this study, a relative error, εtol, equal to 10-6

was used (defined in Section 2.3.5 of

McClure, 2012).

Stresses induced by normal displacement of closed fractures are neglected. For a crack, these displacements are due to

fracture stiffness and are quite small. For a thicker, fault-zone like feature, displacements may be bigger, but they are spread

over a larger volume, reducing stress and strain (see Section 2.2.3.3 in McClure, 2012 for more discussion).

The simulations are two-dimensional, and in this paper should be interpreted as showing normal faults viewed from the side,

looking in the direction of the maximum horizontal stress. In this paper, the vertical direction is referred to as the y-axis

direction and the horizontal direction is referred to as the x-axis direction. The Shou and Crouch (1995) method assumes plane

strain deformation, implying infinite fracture size in the out-of-plane dimension, but in the study described in this paper, the

Olson (2004) adjustment was used to approximate the effect of a finite sized out-of-plane dimension (given by the variable h).

Flow is not upscaled to an effective continuum model. Because flow in the matrix is neglected and the boundary element

method is used to calculate stresses induced by deformation, it is only necessary to discretize the fractures, not the matrix.

Implicit time-stepping is used. During every time-step, the fluid pressure and (if the element is opening and/or sliding)

opening and sliding displacements are calculated to satisfy simultaneously for all elements the unsteady-state mass balance

equation and appropriate stress conditions. Elements may be closed (walls in contact) or open (walls out of contact),

4 SPE 166332-MS

depending on whether the fluid pressure has reached the normal stress. If the walls are in contact, Coulomb's law with

constant coefficient of friction is used to determine if the fracture should slide, and if so, displacements are calculated so that

Coulomb's law is satisfied. If walls are out of contact, displacements are calculated so that the walls bear zero shear stress. A

radiation damping term (Rice, 1993; Segall, 2010) is included for shear stress to approximate the effect of inertia at high

slipping velocity (though high slipping velocity is uncommon if a constant coefficient of friction is used) and to prevent

sliding from happening instantaneously.

The Coulomb failure criterion with a radiation damping term is (Jaeger et al., 2007; Segall, 2010):

0

'|| Sv nf , ............................................................................................................................. ...... (1)

where τ is the shear stress, η is the radiation damping coefficient, v is the sliding velocity of the fracture, μf is the coefficient of

friction (assumed constant in this study), S0 is fracture cohesion, and σn’ is the effective normal stress, defined as (Jaeger et al.,

2007; Segall, 2010):

Pnn ', ............................................................................................................................. ..................... (2)

where compressive stresses are taken to be positive. For fractures with shear stress less than the frictional resistance to slip,

shear deformation is assumed to be negligible.

Nonlinear relationships are used between fracture stress, fluid pressure, opening displacement, sliding displacement, hydraulic

aperture, and void aperture (modified from Willis-Richards et al, 1996):

Erefnn

Edil

effE

Erefnn

DE

E,

',

,

'

0

/91tan

/91

, ..................................................................................... (3)

where E0, σn,Eref, and φEdil are specified constants. DE,eff is defined as equal to D if D < DE,eff,max, and equal to DE,eff,max

otherwise. The constants are allowed to be different for hydraulic aperture, e, and void aperture E. Nonzero φEdil corresponds

to pore volume dilation with slip, and non-zero φedil corresponds to transmissivity enhancement with slip.

Hydraulic aperture is equal to void aperture between two smooth plates but is lower than void aperture for rough surfaces such

as rock fractures (Liu, 2005). A "fracture" in a Discrete Fracture Network (DFN) model may represent a crack, but it may also

represent a more complex feature such as a fault zone (Section 2.2.3.3 in McClure, 2012). In the latter case, the void aperture

may be much larger than the hydraulic aperture, which is why the model allows e and E to be different. An elevated void

aperture E may also loosely approximate the effect of fluid leakoff into the matrix, which is not currently included in the

model.

The cubic law for fracture transmissivity (the product of permeability and hydraulic aperture) is (Jaeger et al., 2007):

12

3ekeT . ............................................................................................................................. ..................... (4)

In the simulations in this paper, it was assumed that no new fractures could form. Even though the injection pressure was

below the minimum principal stress, it was a simplification to neglect fracture propagation because concentrations of tensile

stress could locally develop from sliding fractures, causing tensile fractures. In geology, this type of fracture is called a splay

crack or wing crack (Mutlu and Pollard, 2008).

Details of the Simulations Three simulations (A, B, and C) were performed to investigate the behavior of a TSS Test under different conditions.

Simulation A was the baseline simulation in which the conditions needed for shear stimulation were met: coupling of slip to

transmissivity enhancement, adequate initial transmissivity, and a percolating fracture network. In Simulation B, a non-

percolating fracture network was used. Shear stimulation was possible, but fluid was unable to propagate far from the

wellbore due to the lack of continuous pathways for flow. The total number of fractures intersecting the wellbore was roughly

the same in Simulations A and B, but Simulation B had a lower average fracture length. Simulation C used the same fracture

network as Simulation A, but there was no coupling between slip and transmissivity (φedil equal to zero), making shear

stimulation impossible.

SPE 166332-MS 5

In Simulations A and B, the initial fracture transmissivity was very low, causing the fracture transmissivity to increase very

substantially during slip, from around 10-18

m3 to around 5×10

-14 m

3. The initial fracture transmissivity was set to be higher in

Simulation C than in Simulations A and B (around 10-16

m3) because otherwise very little flow would have occurred (since

there was no shear stimulation to increase transmissivity).

The simulations were designed to loosely resemble the shear stimulation performed in Well 27-15 at the Desert Peak EGS

project. The simulations represent a vertical cross-section viewed from the side looking in the direction of the maximum

principal stress. At Desert Peak, the openhole section was roughly 150 m long and centered at a depth of 990.5 m. According

to the stress profile of Hickman and Davatzes (2010), at the center of the openhole section, at a depth of 990.5 m, σhmin = 14.5

MPa, σv = 23.8 MPa, and P = 8.7 MPa. The gradients of effective σhmin and σv with depth (stress value minus in-situ fluid

pressure) were 0.005 MPa/m and 0.014 MPa/m, respectively. Fracture orientation data was not available for the Desert Peak

project. In the simulations, the initial stress was initialized with a vertical gradient in σxx and σyy of 0.005 MPa/m and 0.014

MPa/m, respectively, and with σxx and σyy equal to 14.5 MPa and 23.8 MPa at y = 0.

During the low rate stimulation of Well 27-15, injection was performed at a roughly constant wellhead pressure of 3.1 MPa

(roughly 13 MPa at 990.5 m). In the simulations, injection was performed at a constant pressure of 12.4 MPa. Because the

simulations were two-dimensional and neglected matrix flow, no attempt was made to match the injection rate trends from the

Desert Peak data.

The fracture networks in the simulations were not necessarily intended to appear geologically realistic. To enable shear

stimulation, the networks contained abundant fractures that were well-oriented to slip.

The simulations were performed for seven days. Table 1 gives the settings that were common to all the simulations. Table 2

gives the settings that were different between the simulations.

Results Figure 1, Figure 2, and Figure 3 show the final pressure distribution at the end of simulations for Simulations A, B, and C.

Figure 4 and Figure 5 show the final pressure distribution from Simulation A with contours of induced change in Coulomb

Stress and shear stress (on a fracture oriented 30° clockwise/counterclockwise from the y-axis direction). Figure 6 shows the

normalized flow rate versus time for Simulations A, B, and C.

Figure 1: The final pressure distribution for Simulation A. The black line represents the wellbore. The blue/red lines are

natural fractures with color proportional to fluid pressure.

6 SPE 166332-MS

Figure 2: The final pressure distribution for Simulation B. The black line represents the wellbore. The blue/red lines are

natural fractures with color proportional to fluid pressure.

Figure 3: The final pressure distribution for Simulation C. The black line represents the wellbore. The blue/red lines are

natural fractures with color proportional to fluid pressure.

SPE 166332-MS 7

Figure 4: Gold/green contours in the background show the change in Coulomb stress at the end of Simulation A for fractures

oriented 30° clockwise/counterclockwise from the y-axis. The black line represents the wellbore, and the blue/red lines

represent natural fractures with color proportional to fluid pressure.

Figure 5: Gold/green contours in the background show the change in the absolute value of shear stress at the end of Simulation

A for fractures oriented 30° clockwise/counterclockwise from the y-axis. The black line represents the wellbore, and the

blue/red lines represent natural fractures with color proportional to fluid pressure.

8 SPE 166332-MS

Figure 6: Normalized flow rate versus time for Simulations A (red), B (blue), and C (green). Flow rates for each simulation

are normalized by dividing by their flow rate after one hour, 0.164 kg/s, 0.114 kg/s, and 1.077 kg/s, respectively.

Discussion

Overall Behavior In Simulation A, the final fracture network was more spatially dispersed and sparsely connected than in Simulation B (Figure

1 and Figure 3). This result is typical for simulations of shear stimulation that couple flow, stresses induced by shear, and

transmissivity coupling to shear (McClure and Horne, 2010; Section 3.4.2.2 of McClure, 2012). Sparsely connected networks

form from shear stimulation because of a process that we refer to as Crack-like Shear Stimulation (CSS) (Section 3.4.2.2 in

McClure, 2012; McClure and Horne, 2011). Figure 6 illustrates the CSS mechanism.

Crack-like Shear Stimulation arises because of the interaction between induced stresses, transmissivity enhancement, and fluid

flow. Along a particular fault, a concentration of shear stress develops at the boundary between where slip has occurred and

slip has not occurred (effectively, this is a shear crack tip). The concentration of shear stress causes slip and transmissivity

enhancement to propagate ahead of the fluid pressure front. This allows the fluid pressure front to propagate along the fracture

at a rate related to the stimulated, not the initial, fracture transmissivity.

Figure 7 shows various fracture properties along a fracture in a network that is experiencing shear stimulation. Fluid is

generally flowing from right to left. The fluid pressure front is at around 80 m, and the front of shear displacement and

transmissivity enhancement is at around 40 m. The transmissivity at the fluid pressure front is much higher than the initial

transmissivity (which was extremely low in this particular simulation and is seen at the far left side of the fracture).

CSS can help stimulation propagate along a fracture, but cannot cause the first patch of slip to occur on a fracture. Initiation of

slip on a fracture requires fluid to flow into it at the initial transmissivity. If the initial transmissivity is much lower than the

stimulated transmissivity, slip will tend to propagate along fractures much more rapidly than slip can initiate on fractures. This

creates an episodic behavior where individual fractures are stimulated in relatively short durations of time, separated by

periods of relatively slow propagation of stimulation (Section 3.4.2.2 of McClure, 2012).

SPE 166332-MS 9

Figure 7: Illustration of crack-like shear stimulation. Reproduced from Figure 3-33 in McClure (2012). The distribution of

transmissivity, shear stress, frictional strength, pressure, and shear displacement is shown along a particular fracture in a

fracture network simulation involving shear stimulation. The fluid is moving from right to left.

Changes in Coulomb Stress, ΔCS, can be calculated to estimate whether induced stresses, Δτ and Δσn', on a fracture will

encourage discourage slip, where positive changes encourage slip:

| | . ............................................................................................................................. ........... (4)

Figure 4 shows contours of induced changes in Coulomb Stress for μ equal to 0.6 on a fracture oriented 30° clockwise or

counterclockwise from the y-axis direction (equivalent to a fault dipping at 60°), which are roughly the orientations of the

fractures in Simulations A, B, and C.

The stresses in Figure 4 were calculated assuming that there were no fluid pressure changes induced in response to the induced

stresses. But actually, there can be a poroelastic response to changes in normal stress, Δσn. This occurs because void aperture,

E, is proportional to effective normal stress (Equation 3), and the water contained in the fractures (in the model) is only

slightly compressible. The fluid pressure changes in response to the induced normal stresses in order to keep the effective

normal stress nearly constant. With liquid water filling the fractures, as would occur in EGS applications, the poroelastic

response would almost completely counteract the induced normal stress. Over time, the fluid pressure would reequilibrate

with the surroundings, and induced change in effective normal stress would become equal to the induced change in normal

stress. In fact, this behavior has been proposed as one explanation for the time delay in earthquake aftershocks (King, 2007).

If the fractures were full of gas, as in a gas shale reservoir, the much greater compressibility of the infillling fluid would make

the poroelastic response on fluid pressure less significant. The poroelastic response is determined by the relative

compressibility of fluid density and the void aperture. Figure 5 shows contours of induced changes in the absolute value of

10 SPE 166332-MS

shear stress, which is equal to the change in Coulomb stress in the limiting case of the fully undrained response for an

incompressible fluid (which reasonably approximates water).

Figure 4 and Figure 5 show that when the fractures slip, they reduce Coulomb and shear stress along their sides, creating a

stress shadow that inhibits their neighbors from slipping. The Coulomb and shear stress changes are positive ahead of the

crack tips. These stresses encourage the further propagation of slip along the fractures, as described earlier. Shear fractures

should not be expected to propagate further in their own plane (Segall and Pollard, 1983), because the strength of intact rock is

much greater than the strength of preexisting flaws.

The result of these processes is that stimulation tends to localize into a smaller number of fractures, but propagate further from

the wellbore, than would be expected from a continuum model, or a model that behaves similarly to a continuum model, such

as Simulation C. The tendency for localization to occur depends on the average fracture length because with shorter fractures,

it is necessary for flow to initiate on new fractures more frequently. In Simulation A, individual fractures were quite long and

the difference between the initial and stimulated transmissivity was quite high, both factors that encouraged localization of

stimulation.

In Simulation B, shear stimulation occurred readily, as in Simulation A. However, stimulation remained confined close to the

wellbore because the fracture network was not percolating (Figure 2). If injection had been performed at constant rate, rather

than constant pressure, the fluid pressure would have eventually been forced to rise, eventually leading to propagation of new

fractures through the formation and the generation of continuous pathways for flow. With constant pressure injection, the

injection rate tended to zero as the fluid pressure become nearly equal to the injection pressure everywhere in the fractures

connected to the wellbore.

Flow Rate In Figure 6, flow rate during the simulations is shown. Injection rates are normalized by the flow rate at one hour, which was

0.11 kg/s in Simulation A, 0.17 kg/s in Simulation B, and 1.08 kg/s in Simulation C. The qualitative behavior of flow rate

with time was different for the three models. In practice, it may be possible to use flow rate behavior over time to diagnose the

effectiveness of shear stimulation during a TSS Test. However, a fully realistic simulation of these transients would require a

three-dimensional simulation that included flow in the matrix.

In Simulation C (no coupling of slip and transmissivity), the injection rate had a negative one-half slope on the log-log plot

(Figure 6), indicating decay with the inverse of the square root of time. This behavior is consistent with the one-dimensional

solution to the diffusivity equation for a constant pressure boundary adjacent to an infinite half-space (Bird et al., 2006). This

is the same behavior that would have been expected in a continuum pressure transient model, in analogy to the matrix linear,

ellipsoidal, and late radial flow regime sequence expected from a hydraulically fractured well (Chapter 11 of Kamal, 2009).

In Simulations A and B, shear stimulation occurred, arresting the decay in injection rate. The shape of the normalized rate

curve for these two simulations started identically. The actual rate was initially slightly higher in Simulation B because a few

more fractures were intersecting the wellbore than in Simulation A. In Simulation B, the boundary of the "reservoir" (the

fractures connected to the wellbore through a percolating flow pathway) began to be felt after a few hours, causing a

downward deviation in the flow rate curve. After around 100 hours, the rate dropped with a slope much more rapidly than the

-1/2 slope observed in Simulation C.

In practice, comparison of the observed flow rate versus time curve to the flow rate versus time curve expected from a

standard continuum model (assuming constant transmissivity) could be used to diagnose the presence of shear stimulation. In

two-dimensions, the continuum result was linear (for early time), and in three-dimensions, the continuum result would be

radial. The well test solution for radial constant pressure injection was given by Ehlig-Economides (1979). In practice, this

solution would probably need to include dual-porosity behavior. Shear stimulation would be indicated by an upward deviation

in rate above the expected result. An anomolously rapid decay in rate could be an indication of a poorly connected network.

These trends in rate could be caused by other reservoir effects, such as boundary effects, and so it would be useful to perform

an injectivity test some period after the TSS test (using a constant pressure low enough to avoid shear stimulation) and

compare between the two transients.

Thermal Stresses Thermal stresses have the potential to be important if long-term injection of colder fluid is performed. Thermal contraction

could cause the formation and propagation of tensile fractures through the formation. If tensile fractures form, it could

increase the injectivity of the well, arresting the expected decline in injection rate, and creating an effect that could be

mistaken for shear stimulation. Presumably, this increase in permeability would be reversible. This behavior needs to be

investigated in future work.

SPE 166332-MS 11

Combining TSS Tests with Standard Well Tests The simplest way to interpret a TSS Test would be to perform standard pressure transient tests, such as injection/falloff tests,

before and after the TSS Test. Shear stimulation creates a permanent increase in formation permeability, and this could be

observed by comparing the permeabilities estimated from these transients. The falloff that occurs at the end of the TSS Test

probably could not be used because the redistribution of fluid pressure after injection could cause shear stimulation to occur at

the periphery of the stimulated region, creating nonlinearity that is not included in standard well test models.

The injection/falloff test performed prior to the TSS Test would need to be performed with a bottomhole pressure low enough

to avoid causing shear stimulation to occur. The injection/falloff test performed after the TSS Test would not be expected to

cause further shear stimulation as long as pressures and volumes were kept below the values used during the TSS Test because

fractures that have already slipped in response to a particular fluid pressure will not slip again when returned to that same fluid

pressure.

A production/buildup transient test could be useful after the TSS Test because the production of fluid from the formation

would tend to reheat the region of the formation that was cooled by injection, which would reduce any potential impact from

thermal stresses.

Desert Peak EGS Project At the low rate stimulation at the Desert Peak project (described in the Details of the Simulations section above), the injection

rate was roughly constant at about 0.45 l/s for around five days, and then showed a gradual increase to around 1.89 l/s over the

subsequent week. During this period, injection pressure was mostly between 2.76 and 3.1 MPa (Chabora et al., 2012).

Assuming an injection pressure of 3.0 MPa, the well demonstrated an increasing injectivity from around 0.15 (l/s)/MPa to 0.63

(l/s)/MPa. As stated above, no attempt was made to match these trends in the modeling because the simplified dimensionality

of the simulations makes it impossible to use them to match real data.

A period of time after the low rate stimulation, an injectivity test was performed that estimated the injectivity at 0.37 (l/s)/MPa,

indicating a somewhat lower injectivity than before. The partial reversibility of the injectivity increase may indicate that

thermal fracturing, rather than shear stimulation, was responsible for the increase in injectivity during the test. Thermal

fracturing would be expected to be reversible because reheating of the formation would be expected after shut-in, which would

reclose some of the fractures unloaded by thermal stresses.

Overall, the results at the Desert Peak project indicate that the formation had minimal TSS. Low rate injection increased the

injectivity by perhaps a factor of four, but this increase was from a low initial injectivity, and was not fully retained during a

subsequent injectivity test. The low TSS was recognized by the project managers, who subsequently injected at high rate with

the intention of performing tensile fracturing (Chabora et al., 2012).

Soultz-sous-Forêts EGS Project The EGS project at Soultz-sous-Forêts involves several wells drilled and stimulated to depths of 3.5 and 5 km in granite. All

wells were stimulated by injecting water with no proppant into long openhole wellbore sections. During the June 2000

stimulation of the well GPK2, fluid was injected at rates up to 50 l/s (Weidler et al., 2002) without the fluid pressure reaching

the minimum principal stress (Valley and Evans, 2007). Hydraulic tests prior to the stimulation estimated an injectivity

around 0.2 (l/s)/MPa. Hydraulic tests immediately after the test did not give conclusive estimates of injectivity (Weidler,

2000), but a test in 2003 (with no intervening stimulations having been performed) showed a peak overpressure of 5 MPa after

several days of injection at 15 l/s, equivalent to an injectivity of 3.0 (l/s)/MPa (Hettkamp et al., 2004). Wellbore observations

in GPK2 were not possible due to a wellbore obstruction, but in neighboring GPK3, production logs confirmed that flow from

the wellbore was concentrated at preexisting, large scale fault zones, and critical stress analysis and caliper logs confirmed that

these faults had failed in shear due to injection (Evans, 2005; Evans et al., 2005).

Overall, the results at the Soultz project indicate that the formation had a high TSS. Injection at pressure less than the

minimum principal stress resulted in an enduring, large increase in the well injectivity, and wellbore observations confirmed

that this increase was due to induced slip on the preexisting faults.

Conclusions Shear stimulation is a potentially important process in hydraulic stimulation of shale formations and in EGS. However in

practice, the role of shear stimulation is inferred and subject to interpretation. The tendency for shear stimulation should be

highly dependent on local geological factors such as fracture orientation and ability to self-prop, and could be considered a

formation property.

Understanding the importance of shear stimulation will have important implications for modeling, stimulation design, and

resource assessment in low matrix permeability shale and geothermal resources. The Tendency for Shear Stimulation Test is a

12 SPE 166332-MS

simple, unambiguous way to directly measure the effect of shear stimulation in-situ. Using modeling, we showed qualitatively

how a TSS Test might be interpreted, showed how geological parameters could affect the results, and described how shear

stimulation can affect the process of fluid propagation in a fracture network. We reviewed two projects as examples of TSS

Tests, the EGS projects at Desert Peak and Soultz, and showed how their results clearly demonstrated the difference between

high and low TSS.

TSS Tests could be interpreted by performing pressure transient tests before and after the TSS Test and comparing the

interpreted formation permeability. It may also be possible to interpret TSS tests directly by analyzing the trends in rate over

time, but developing this technique in future work will require three-dimensional simulations that include matrix flow.

Acknowledgements Thank you to the Precourt Institute for Energy for supporting this research from 2009-2012.

Nomenclature CS = Coulomb stress, MPa

D = cumulative fracture sliding displacement, m

DE,eff, De,eff = Effective cumulative fracture sliding displacement in Equation 3, m

DE,eff,max,, De,eff,max = Maximum effective cumulative sliding displacement in Equation 3, m

e = hydraulic aperture (m)

E = void aperture (m)

E0, e0 = reference aperture in Equation 3, m

h = out-of-plane dimension in the two-dimensional simulations, m

k = permeability, m2

P = fluid pressure, MPa

S0 = fracture cohesion, MPa

T = transmissivity, m3

v = fracture sliding velocity, m/s

η = radiation damping coefficient, MPa/(m/s)

μf = coefficient of friction, unitless

σn = normal stress, MPa

σn’ = effective normal stress, MPa

σn,Eref, σn,eref = 90% fracture closure stress in Equation 3, MPa

τ = shear stress, MPa

φEdil, φedil = shear dilation angle, °

SPE 166332-MS 13

Tables Table 1: Simulation settings used in Simulations A, B, and C.

De,eff,max 0.005 m η 3 MPa/(m/s)

E0 .005 m

G (shear modulus) 15 GPa ηtarg (for time stepping,

Section 2.2.3.9 in

McClure, 2012)

0.5 MPa

h 100 m μf 0.6

Pinit (initial fluid pressure) 8.7 MPa σn,Eref 20 MPa

S0 0.5 MPa σn,eref 20 MPa

mechtol (error tolerance

used in solving shear

stress equations, Section

2.2.3.5 in McClure, 2012)

.003 MPa σxx (initial x-direction

principal stress at y = 0)

14.5 MPa

itertol mechtol (error

tolerance used in iterative

coupling scheme, Section

2.2.3.1 in McClure, 2012)

0.01 MPa σyy (initial y-direction

principal stress at y = 0)

23.8 MPa

φEdil 0° σxx,trend (trend in initial σxx

with distance in y-axis

direction)

0.005 MPa/m

υp (Poisson's ratio) 0.25 σyy,trend (trend initial σxx

with distance in y-axis

direction)

0.014 MPa/m

Table 2: Simulation settings specific to Simulations A, B, and C

A B C

φedil 2.5° 2.5° 0°

e0 .00001 m .00001 m .00005 m

14 SPE 166332-MS

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SPE 166332-MS 17

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