SPE-173378-MS

Applications of Geomechanics to Hydraulic Fracturing - Case Studies fromCoal Stimulations

Vibhas J. Pandey, ConocoPhillips and Thomas Flottmann, Origin Energy

Copyright 2015, Society of Petroleum Engineers

This paper was prepared for presentation at the SPE Hydraulic Fracturing Technology Conference held in The Woodlands, Texas, USA, 35 February 2015.

This paper was selected for presentation by an SPE program committee following review of information contained in an abstract submitted by the author(s). Contentsof 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 reflectany position of the Society of Petroleum Engineers, its officers, or members. Electronic reproduction, distribution, or storage of any part of this paper without the writtenconsent 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 maynot be copied. The abstract must contain conspicuous acknowledgment of SPE copyright.

Abstract

Modern hydraulic fracture treatments rely heavily on the implementation of formation property detailssuch as in-situ stresses and rock mechanical properties, in order to optimize stimulation designs forspecific reservoir targets. Log derived strain and strength calibrated in-situ properties provide criticaldescription of stress variations in different lithologies and at varying depths. From a practical standpointhowever, most of the hydraulic fracture simulators that are used for fracturing treatment design purposestoday can accommodate only a limited portion of a geologic-based rock mechanical property character-ization which targets optimal data integration thus resulting in complexity. By using examples fromhydraulic fracture stimulations of coals in a complex but well characterized stress environment (SuratBasin, Eastern Australia) we distil out the reservoir rock related input parameters that are determinants ofhydraulic fracture designs and identify those that are not immediately used. In order to understand theimpact on improving future fracture stimulation designs, the authors present workflows such as pressurehistory matching of fracture stimulation treatments and the calibration process of key rock mechanicalparameters such as Poissons ratio, Youngs modulus, and fracture toughness. The authors also presentexamples to discuss synergies, discrepancies and gaps that currently exist between geologic geome-chanical concepts (i.e. variations in the geometry and magnitude of stress tensors and their interaction withpre-existing anisotropies) in contrast to the geomechanical descriptions and concepts that are used andimplemented in hydraulic fracturing stimulations.

In the absence of a unifying hydraulic fracture design that honors well established geologic complexity,various scenarios that allow assessing the criticality, usefulness and weighting of geologic/mechanicalproperty input parameters that reflect critical reservoir complexity, whilst maintaining applicability tohydraulic fracturing theory, are presented in the paper. Ultimately it remains paramount to constrain asmany critical variables as realistically and uniquely possible. Significant emphasis is placed on reservoir-specific pre-job data acquisition and post-job analysis. The approach presented in this paper can be usedto refine hydraulic fracture treatment designs in similar complex reservoirs worldwide.

IntroductionThe design and success of hydraulic fracture stimulations depends critically on the correct implementationof models that account for in-situ stresses and physical properties of rocks such as Youngs modulus and

Poissons ratio. In particular, basin wide variationsof stress geometry can be challenging for fracturestimulations as is seen to be the case in easternAustralia. In the basin, the horizontal stresses arecommonly the maximum principal stress resultingin dominance of reverse and/or strike slip stressregime (HmaxV hmin and HMaxhminV,respectively), whereas a normal stress regime(VHmaxhmin) is less common. Variations instress geometry occur both laterally throughout theeast Australia Surat basin as well as with depth(Flottman et al. 2013). Fig. 1 shows a schematic ofvarious stress regimes typically observed in the Su-rat basin.

Hydraulic fracturing treatments in coal seams ofSurat basin are influenced by the high Poissonsratio (greater than 0.3) and low Youngs Moduluscombination which is commonly observed through-out the basin. It is of primary importance to accountfor all critical variables during treatment modelingand design phase in order to ensure fracture containment in the target coal zones to prevent excessivegrowth of hydraulic fractures out of the coals into the non-productive and often fluid-sensitive inter-burden. Using examples from the Jurassic Surat Basin in eastern Australia, the authors present workflowcase studies showing the need for detailed calibration of reservoir rock parameters and stresses and theirinfluence on design improvement loops in successive fracture stimulation treatments. Previous work(Flottman et al. 2013) has shown a significant influence of horizontal differential stresses and fracturingfluid selection on the hydraulic fracture geometry, where the influence of stress regime on hydraulicfracturing geometry in light of their vertical and horizontal orientation is demonstrated.

Strain-derived stress models, also termed as Wellbore Stress Models (WSM), were developed tocharacterize the stress variability over the region (Brooke Barnett et al. 2012, Flottman et al. 2013). Stressor rock strength calibrated Hmin from WSMs are routinely used as key stress input in fracture designs.The case studies presented in this paper show that log-derived and strain calibrated stress models have tobe further refined or shifted using pressure matched data from offset wells in order to obtain best-fitrealistic stress models for predictive fracturing treatment designs. The majority of results, in particularfrom fracture diagnostic tests show that coals have the lowest bulk stress. Our observations suggest thatlog based stress implementations, especially Poissons ratio and to a certain extent Youngs modulus,must be viewed with caution in areas where the greatest principal stress is horizontal.

Hydraulic Fracture ModelingModeling of hydraulic fractures is a critical step in the fracture design process. Fracture treatment designsaim at achieving optimized target fracture lengths, vertical coverage or fracture height, and fractureconductivity. These main characteristics allow a design engineer to plan for total treatment volume andexecution pattern. However, the actual design of hydraulic fractures is far from this simplistic overview.Depending on the application, the fracture designs are modeled using one or several of the commerciallyavailable fracture simulators in the industry today. Most of these models are grid-based and rely onnumerical simulation to generate fracture geometry for a given set of inputs. The inputs primarily includegeomechanical attributes but are not limited to, vertical stress distribution in target and surrounding layers,mechanical properties of rocks, critical fluid and proppant characteristics, and lastly a treatment schedule

Figure 1Stress regime prevalent in Surat Basin, Eastern Australia.

2 SPE-173378-MS

that provides the pumping rates, volumes and proppant concentration. The output from the models mayvary depending on the underlying assumptions, but typically these models are designed to honor thefundamental laws of conservation of mass, momentum and energy. They also follow the constitutive lawsrelated to stress-strain relationships and flux laws. The mathematics and computer codes involved insimulations are rigorous but the user is seldom burdened with intricacies of calculations and internalsolution schemes, and is only required to have a general understanding of critical inputs to the simulatorthat govern the output.

In the last decade, the industry has seen a rapid expansion of hydraulic fracturing activities inunconventional reservoirs, mostly driven by shale exploration and development activity in USA (King2010). Fracture initiation and propagation in these unique geological settings and rock fabrics haspurportedly resulted in increased awareness of the complexity that entails some of the hydraulic fracturingtreatments. Qualitative evidence from alternate measurements like microseimic surveys and mine-backsshow that in unconventional reservoirs rocks, fracturing can result in a highly complex network ofpathways (Fisher and Warpinksi 2011) which are not easy to predict. Though attempts to model thesecomplex fracture networks are currently ongoing industry wide, it is understood that solutions may notbe anywhere near owing to the heterogeneity and uncertainty involved.

Typical Simulator InputsThe modeling of hydraulic fractures in coal seams was understood to be a fairly challenging task evenbefore the advent of shale fracturing. Most of the coal deposits worldwide that are potential candidates forhydraulic fracturing occur in shallow depths often ranging from 800 to 2,500 ft [243.8 to 762 m]. Stressregimes in these reservoirs could range from lithostatic conditions with near similar magnitudes ofprincipal stresses to complex stress regimes resulting from the influence of regional tectonics. In astrike-slip or reverse-stress scenario, additional complexity related to orientation and rotation of hydraulicfractures during the treatment can be expected. Hydraulically induced fractures open in the directionperpendicular to minimum principal stress, 3, which if in a horizontal plane is denoted as hmin andpropagate in the direction of maximum horizontal principal stresses, 2 or Hmax which is the intermediateprincipal stress. The implementation of stress regimes, is therefore of primary importance in fracturedesigns. In strike slip and normal regimes, the hydraulic fractures propagate vertically whereas a reversestress regime tends to promote horizontal fracture propagation. Most commercially available fracturesimulators however, do not take into account for this 3 dimensionality of stresses.

Critical parameters in Geomechanical modelsMost fracturing simulators require formation in-situ stresses to be input along the depth axis and assumea constant stress regime along a given horizontal plane. Some more recent versions of popular fracturesimulator available in the industry also allow the user to vary stresses, mechanical properties and otherpetrophysical property inputs along the horizontal plane. This feature allows for better handling ofhydraulic fracturing modeling in horizontal wells where there may be significant variations of propertiesalong the lateral length of the wellbore, for e.g. depletion or residual stress from adjacent fractures.

In the workflow utilized to generate log based in-situ stresses, Poissons ratio v, is determined firstusing incremental changes in shear and compressional wave travel times ts and tc as shown in Eq. 1below:

(1)

Shear modulus G, which is the measure of a material response to deforming shear stresses, is calculatednext using both Poissons ratio and bulk density, b as inputs as shown in Eq. 2 below:

SPE-173378-MS 3

(2)

where, d is some known distance over which the measurements are made. Poissons ratio and Shearmodulus are then used to compute dynamic Youngs modulus, E using the following relation of Eq. 3:

(3)

Several correlations (Morales and Marcinew 2007) have been reported in various studies that allowtransforming dynamic E measurements to static values. The values obtained from static tests in thelaboratory experiments on representative rocks samples may also be used for calibration purposes andcorrecting the log-derived values.

As a last step in log calculations, in-situ stresses are computed using the following poro-elastic stressrelation (Hubbert and Willis 1957) in Eq. 4 below that has been in traditionally use by the industry togenerate log based in-situ stress:

(4)

where, h is calculated minimum in-situ stress, v is Poissons ratio, v is vertical stress (overburden),Pp is pore pressure, is Biots poro-elastic constant, E is static Youngs modulus, and h & H are strainsin minimum and maximum principal stress directions respectively. The first two terms on the right sideof the equation reflect stress conditions under a uniaxial environment where little stress anisotropy mayexist in horizontal plane which is generally the case for tectonically relaxed extensional environments. Thelast two terms on the right side account for additional stresses due to regional tectonics. Initially they weredenoted by only tectonic stress t, which in the current form of equation is elaborated further. Themulticomponent equation provides the first approximation of formation stresses and thus a close estimateof fracture closure pressures for given conditions.

Both, Poissons ratio and Youngs modulus are extensively used in fracture mechanics computations,with the latter being more influential in fracture widths and net pressure calculations. The effects ofPoissons ratio are generally diluted in these mechanics calculations owing to the plane strain assumptionwhere the strain resulting from deforming forces existing in a 3D plane are simplified by neglecting strain(assumed to be infinitesimally small) in length direction, thus assuming that the planes remain parallelbefore and after deformation.

Fracture widths are calculated on the basis of a width equation (Sneddon and Elliot 1946) for mode Ifractures given by Eq. 5 in the text below.

(5)

where, pf is average fracture pressure, L is the length of the fracture, min is minimum principal stressand is a dimensionless constant that depends on the shape. If net pressure given by the relation (pf min) is substituted by relation for the critical stress intensity factor KIc, Eq. 5 can be modified to calculatewidth at the wellbore given by Eq. 6 as:

(6)

KIc is also referred to as fracture toughness and is considered as a material property for a perfectlyelastic medium. When the width equation is combined with fluid equation, the following relation for netpressure Pnet presented by Eq. 7 is arrived at (Nolte 1991):

(7)

4 SPE-173378-MS

where EE/(1-v2) is plane strain modulus and Ptip are fracture tip pressures that can be calculated fromthe fracture toughness defined above. The above equation clearly shows the dependence of net pressureon pumping rates and fluid viscosity. If it is solved for fracture width, one gets the relation ww {qiL/E=}1/4.

For a case where the stresses in bounding layers (2), are higher than the ones in pay interval (1) fromwhere the fractures would initiate, and also higher (21), the following relation represents anequilibrium condition as shown by Simonson et al. (1978) in Eq. 8 follows:

(8)

where, P is the net pressure in the fracture, h is the pay zone thickness and H is the total fracture height.Eq. 8 takes a conservative approach in height prediction but with similar relations developed fornon-symmetric stress cases, the simulators account for flow resistances offered by in narrow width regionsin fractures and tend to limit fracture heights.

Fracture Complexity and Fracturing SimulatorsThe more simplified two dimensional (2D) analytical models assumed a constant fracture height andcalculated evolution of fracture widths with time. With the introduction of high-speed computers, thesemodels eventually made way for numerical models that heavily rely on the increased computational abilityto carry out complex numerical schemes, that additionally incorporate 2D fluid low effects in the fractureand fluid leak-offs in the formation to account for material balance and net pressure calculations whichinfluences fracture geometry. Layered models were introduced and fracture heights were no longerassumed but were calculated during the simulation. Four major parameters that have an effect on fractureheight are layered stresses, modulus, fracture toughness and slippage at weak interfaces. Amongst these,the first 3 are generally included in calculations in most simulators but owing to the uncertaintiesassociated with the failure pattern and ensuing computational complexity, shear slippage is not currentlyaccounted for adequately in most simulators. This particular shortcoming prevents accurate fracture heightgrowth and/or containment prediction in heavily layered formations. Also, the individual influence ofthese parameters on actual geometry will vary from region to region. For example in ultra-soft rockformations of Youngs modulus of less than 5x105 psi [3,447.4 MPa] fracture toughness KIc plays acritical role in net pressure computation and consequently fracture propagation; similarly in layeredformations with high contrast in modulus and weak interfaces, interfacial slippage may have moreinfluence on dictating the vertical propagation of fracture.

Complexity in fractures generally arises when conditions that favor fracture propagation in multipleplanes exist; this could range from presence of low stress anisotropy between principal stresses that affectorientation of fractures, highly fractured reservoirs that could lead to ample interaction between hydraulicand natural fractures, high in-situ stresses in comparison to overburden which is generally the case inshallow formations, to regions that are heavily influenced by tectonic stresses or several other similarfactors. Microseismic mapping can aid in determining the complexity of network created by hydraulicfracturing though this is often open to interpretations and many believe that most fractures are still planarin nature (Fisher and Warpinski 2012); other source is fracture excavations via mine-backs. Fracturediagnostic tests can also help in detecting non-ideal behavior prior to the main pumping often they arethe precursors to the pressure behaviors observed during the actual fracture treatment. However, inter-pretation and forecasting requires considerable expertise and experience for a given field. In an idealsetup, to accurately predict fracture geometries from simulation, geomechancis should be intertwined withfracture mechanics. In the sections that follow the authors address some of the limitations and gaps thatcurrently exist in fracture modeling and the potential areas that are relevant to hydraulic fracturing in coalseams.

SPE-173378-MS 5

Geological BackgroundThe Jurassic age Surat Basin of south-east Queensland, Fig. 2, formed as part of an extensive intra-continental sag basin (Cook and Draper 2013). Surat Basin sediments are dominated by siltstones andmudstones with minor sandstones all of which were deposited in a fluvio-lacustrine depositionalenvironment which was affected by intermittent volcanic activity. Inter-burden (non-coal) rocks havecharacteristically low porosity and permeability which generally results in low fluid leak-off for typicalpolymeric fracturing fluid systems. The Surat Basin contains multiple coal seams, on average 60, with anaverage thickness of 0.4 m [1.3 ft]. Fig. 3 shows location map of Walloons fairway (Flottmann et al. theirFig. 1).

Contrasting permeabilities in coals appear related to drape of the Walloons sequence over theunderlying Triassic structures. Dome-like drape over structural highs leads to regional curvature resultingin multiple fracture orientations, typical for regions with high permeability. Poorer permeability regionsare characterized by a unidirectional single fracture orientation which appears to result from hinge-likemovement on a monoclinal flexure. These features are predominant where the Walloons fairway overliesstructural lows of the underlying Bowen Basin.

Stress CharacterizationThis paper focuses on low permeability coals that are generally less than 10 mD though higherpermeability coals seams may be seen in the various coal packages infrequently. Image log data from 30wells (Flottman et al. 2013, see also Brooke-Barnett et al. 2012) were interpreted to identify stressindicators. Three principal stress regimes were identified with depth based on one dimensional stressprofiles. Log-derived input data include bulk density, compressional sonic, shear sonic, and gamma ray.Poissons ratio and Youngs modulus measurements were calculated using sonic and density wirelinedata, and a dynamic to static conversion relationship was derived regionally from rock mechanicslaboratory measurements. Pore pressure was calculated based on a fresh water hydrostatic gradient of0.433 psi/ft [9.795 kP/m], which is commonly observed in non-depleted reservoirs where coals have notbeen produced at a large scale. Minimum and maximum horizontal stresses were calculated using

Figure 2Geology of Surat Basin, Australia.

6 SPE-173378-MS

poro-elastic stress equations (Zoback 2007, Brooke-Barnett et al. 2012), which incorporate static Pois-sons ratio, vertical stress, pore pressure, staticYoungs modulus, a Biots constant (equal to 1),and tectonic strain in the minimum (min) and max-imum (max) horizontal stress directions. More de-tails on these are presented in the literature reviewin the later sections of the paper.

Calibration of the stress profiles was undertakenusing either image logs (stress polygon method) orfracture diagnostic injection test data from individ-ual wells or rock strength calibrations. Wheneveravailable, fracture closure pressures were derivedfrom pressure data such as injection tests, ModularDynamic Testing (MDT) based small scale fracturesand pre-treatment injection tests in order to estimateminimum principal stresses (Baree et al. 2007,2009).

StressOverburden stress in the Surat Basin remains con-stant at close to 1.0 psi/ft [22.621 kPa/m]. However,most regions display characteristic stress regime transitions with depth (Fig. 1). The stress regimeshallower than around 400 to 500 m [1,312.3 to 1,640.4 ft] is characterized by reverse stress fielddescribed in the order, vhminHmax, where v vertical stress, hmin minimum horizontal stress;Hmax maximum horizontal stress. At deeper depths, the stress field is typically of strike slip stressregime described above (Johnson et al. 2002). In some areas a second transition from strike slip to anormal stress regime (hminHmaxV) can occur around 650-800 m [1,968.5 to 2,624.7 ft] as shownin Fig. 1. In particular, the transition between reverse and strike slip regimes is corroborated by tilt meterdata. In-situ stresses are the principal guiding parameter for hydraulic fracture geometry and propagation,differential stress magnitude, as well as Hmax orientation.

Generating Log-Based ModelsThe stress curves calculated from logs are generally represented in a continuous format around the zonesof interest as seen in the Fig. 4 below. Data from Tracks 1 to 4 (L to R), including depth and theperforation track on the extreme left, shows some of the measured properties, and tracks 5 onwards to theright show calculated properties based on the equations mentioned in the earlier section. The data pertainsto Well A, drilled and completed across several of the coal seams in the Walloons coal measures in easternAustralia. The lower most perforations are in a section termed as Tarooms that is generally associated withlow permeability coal seams with poorly developed cleat systems. Moving up in the well, higherpermeability coal seams with an enhanced fractured system are more commonly seen and are categorizedunder zone named Juandah. These are further broken in to lower, middle and upper Juandah based ondepth.

It is a standard practice to calibrate log derived initial stresses and mechanical properties with measuredor analytically determined values in order to gain confidence in the geo-mechanical model. To accomplishthis important step, tests are conducted prior to the main fracturing treatment by first injecting apre-determined volume in the perforated coal interval at a planned rate and later, observing the pressureresponse during the decline phase after the well is shut in. The primary objective of these injection tests

Figure 3Location map Walloons freeway. Color ramps shows depthsof top basement.

SPE-173378-MS 7

is to estimate fracture closure pressures which provide an approximation of minimum horizontal principalstress based on pressure fall-off diagnostic techniques (Nolte 1979, Castillo 1987).

Injection tests were pumped down a 7 inch [17.78 mm], 20 lbm/ft [29.76 kg/m] casing cemented at3,638.45 ft [1,109 m] at 5 to 6 bbl/min [0.01325 to 0. 01589 m3/s] for an average of 14 bbl [2.241 m3]per injection test. As is known, results from one injection test results in a single data point in comparisonto the continuous log curve; this approach is thus sometimes inadequate to characterize the stress andmechanical property behavior over the entire zone of interest. Nevertheless, tests are conducted whereverfeasible so that the working model can be adjusted to actually observed results. Closure stresses derivedfrom diagnostic tests on 4 perforated test intervals are shown in the extreme right track in Fig. 4. Youngsmodulus calibrated on the basis of the 2D analytical model is also represented in the fifth track from leftas discrete data points.

Figure 4Log section of Well A showing measured and calculated log properties over gross interval from 400 to 1,050 m [1,312.34 to 3,444.88 ft].

Figure 5Closure pressure was determined to be 1,432psi based on GdP/dG analysis. Alternative possible late time closure pick is highlighted bygreen line at 1,200psi.

8 SPE-173378-MS

Preliminary Data CalibrationIn the initial phase of fracture modeling process in Walloons coal measures, during which the field-widestress characterization were still ongoing, some disagreement between initial estimates and observedvalues was seen as would be normally expected. However, it was envisaged that over a period of time themodels would improve as additional data was being incorporated, ultimately leading to treatment designsthat could be placed precisely within the coal seams in order to maximize productivity.

The superposition derivative GdP/dG is often used in identifying the fracture closure pressure as seenin Fig. 5; it is an accepted norm (Baree et.al. 2009) to consider the deviation from straight line behavioras onset of the fracture closure event and the use of the derivative magnifies this effect. Correct closureidentification requires experience in the field. In complex rock structures such as coals, one may expecta late closure of the main fracture shown by the late rise in derivative and an eventual recession, but itis the higher stresses that tend to dominate the pressure behavior during the treatment. The plot shown inFig. 6 shows as pressure match using the values derived from closure analysis. Here the leak-off wasmatched to 0.00692 ft/min0.5 [0.0002723 m/s0.5].

The early closure and associated hump seen in the early part of the GdP/dG curve also points to apotential pressure dependent leak-off mechanism. The closure pressure thus identified also primarilyrepresents the closure of natural fracture system.

Figure 6Pressure History Match of Injection Test on Upper Juandah coal interval in Well A. Closure pressure, Pc1,417 psi was used in the modelfor simulation.

Table 1Summary of results from various diagnostic tests conducted on Well A.

Depth m Rock Type Data Source

Rate Pc Pr F.G. Modeled Pc Modeled E Perm. Leak-off

bbl/min psi psi psi/ft psi MMpsi mD ft/min0.5

1015.0 Silt Inj. Test 5.4 2,485 2,368 0.746 2,487 1.39 0.0044

992.2 Coal Inj. Test 9.96 2,340 1,441 0.719 2,085 1 0.004546

686.3 Coal Inj. Test 5.2 1,432 972 0.636 1,417 0.65 0.00692

640.0 Sand Inj. Test 5 1,782 1,476 0.844 1,780 2.1 0.0061

680.27 Coal DST 848 26.68

637.27 Coal DST 0.15

*Pc Closure pressure, Pr Reservoir pressure, Perm. Permeability, E Youngs modulus

SPE-173378-MS 9

Table 1 below summarizes the results from Drill stem Test (DST), Injection Test and main treatmentsconducted at various depth intervals. Note that the tests were carried out in both coal seams andinter-burden for stress estimation purposes.

During the calibration process of Well A, revised pore pressure estimates derived from injection testswere used to apply base correction to log derived stresses. The revised curve is shown in Fig. 7 as LogStress and as shown the values are marginally different than the original estimates shown in Fig. 4 earlier.Results from DST conducted during drilling phase were also used to validate the pore pressure data.Further adjustments were then made to log stress curve by incorporating the effects of Youngs modulusand strain. Static Youngs modulus curve was calibrated using the calibrated elastic moduli from injectiontests and shows a good agreement. Note that the regional stress curve generated to an offset field wasfound to be inappropriate for use in this field as is shown under SHMIN_REG curve mentioned in Fig.7.

Small fluid volumes pumped during injection tests allow for better initial estimates of in-situ propertiesof the targeted intervals because by design, the fractures generated are confined to the zone of interest.However, because of these smaller volumes, the near well region which is yet to fully clean up, canpotentially impose a choke effect and near-well tortuosity that can dominate the pressure response bothduring the injection and also in the decline phase. Such a behavior often introduces uncertainty in theanalysis since it is difficult to quantify and account for accurately. As a practice thus, it was advised topump up to 20 bbl [3.18 m3] at at least 5 to 8 bbl/min [0.01325 to 0.0212 m3/s] in future injection teststo ensure that most of near well entry restrictions are sufficiently minimized.

Additional Corrections to the Mechanical Property ModelFracture treatments designed on the basis of initially developed stress and mechanical property models arerequired to be corrected at least one more time after pumping of the main fracturing treatment. The extentto which the correction is applied depends on how accurately the model has forecasted the pressurebehavior. The pressure behavior that is matched here is the calculated bottom hole pressure (BHP) using

Figure 7Log section displaying Youngs modulus and in-situ stress curves after calibration process in Well A. Coal picks are based on Bulk Density< 1.75 g/cm3.

10 SPE-173378-MS

surface treating pressures, hydrostatic and friction pressures as inputs. Pressure history matching from allstages was carried out using commercially available third party fracture simulator. Original stress modelsdeveloped from preliminary injection data were used as a baseline and adjustments were made wherevernecessary. In most cases only nominal changes had to be made in the stress values and the fluid leak-offsin order to obtain a good match. A summary of results from all the matches is shown in Table 2. Stages1 and 3 screened out at the tail end of the job; in stage 4 the operations were curtailed due fluid gellingissues.

In Table 2 above, mechanical properties and stress data are averaged across the perforations only. Fig.8 shows the pressure history match plot for stage 5 of Well A, and the corresponding fracture geometriesfrom pressure matches on stage 3 and 5 are shown in Fig. 9 and 10 respectively. The fractures are shownto be propagating in a vertical plane and planar in nature as would be expected as outputs from typicalsimulators. The complexities associated with fracture stimulation in coal seams is not truly captured herethough the equivalent geometries resulting from pressure history matches are presented after processingthe material balance and proppant placement.

The case history in Well A was mostly used to present the work flow that is traditionally practiced infracture design process in coal seams stimulation designs. The fracture mechanics and rock geomechanicsinteraction along with existing gaps in the simulators will be addressed in few other case histories whereadditional data were collected to characterize and estimate fracture dimensions.

Stress and mechanical property data averaged for all layers that were constructed for the simulator wascollected from 5 simulation loadcases and merged in a single data file. This provided a continuous data

Table 2Summary from Fracture Stimulation in Coal Seams.

Stage*

Depth

Formation Name

Rate Pc Pr F.G. E_Stat Perm. Leak-off

m bbl/min psi psi psi/ft MMpsi mD ft/min0.5

1 1,058.54 Tarooms 20.5 2102.9 1,410.0 0.606 0.494 0.10 0.001562

2 856.06 Lower Juandah 20.0 1968.0 1,067.3 0.701 0.43 1 0.01177

3 787.99 Lower Juandah 19.75 1795.9 982.4 0.695 0.383 5 0.002756

4 735.89 Mid. Juandah 10 to 13 1766.4 917.4 0.732 0.444 0.005376

5 685.76 Upper Juandah 20.25 1415.6 855.0 0.793 0.377 26 0.01177

Figure 8Plots shows Pressure History Match of fracture stimulation treatment in stage 5 in Upper Juandah.

SPE-173378-MS 11

set representing the critical properties on which thepressure history matches were carried out. Whenincluded in log file display, they appeared to agreewell with the constructed model, indicating thatinitial model provided good estimation of in-situproperties. As seen in the log section of Fig. 11above, the maximum departure of predicted versusthe actual properties was seen in the upper Juandah.Youngs modulus was also revised, but there is littleinfluence of this parameter on simulation results,especially on treating pressures when the rockstrength is less than 500,000 psi [3,447.38MPa].

Case HistoriesA number of wells in the Surat Basin were fracturestimulated in 2011 to unlock gas reserves in lowpermeability Walloons coals. During the initialphase of the well stimulation campaign a number ofpilot wells were completed with various stimulationtechniques to aid in understanding how fracturestimulation would influence well productivity. Ingeneral, it was known that with higher Poissonsratio reaching up to 0.4 in static measurements and Youngs modulus traditionally below 1.0E6 psi[6.8948 MPa], the coals were softer and more ductile in comparison to their counterparts worldwide, thusmaking them unique. The cleat structure in these Surat Basin low permeability coals has not developedextensively though vitrine reflectance and gas content point to ample presence of exploitable gas.

Case History: Well BWell B was the first well to be hydraulically fractured in the low permeability coal seam fracturingcampaign and was also a part of the pilot program where apart from gathering extensive log data, othermeasurements such as microseismic survey and tiltmeter surveys were done. The well was drilled andcemented with 5- inch [139.7 mm] N-80 casing to 758.0 m [2,486.9 ft]. The well lies in a region whichis characterized by a unidirectional fracture system ubiquitously seen in all of the wells drilled andcompleted in this area. From the in-situ stress standpoint, there is a presence of high differential stresswhich is evident in the image logs where bore hole breakouts in long vertical sections were seen to beoccurring commonly. The regional stresses also show a distinct presence of strike slip environment around430 m [1,410.8 ft] where hmin is almost same as v. Calculations based on mechanical property logsindicated a low Youngs modulus and higher Poissons ratio which was consistent with general obser-vations in the Surat Basin coals.

The microseismic and tiltmeter data obtained at the end of the 7-stage treatment were very helpful inindependently verifying the ability of simulator to model fractures. Treatments were pumped to target theTarrooms, Lower Juandah, McAlister and Upper Juandah coal seams in the order mentioned. All 7 stageof Well B were treated with a 20 lbm/Mgal [2.4 kg/m3] Borate cross-linked gel and 16/30 U.S.Mesh size[1.194 0.584 mm] sand. Fine 100 U.S. Mesh size [0.043mm] was used occasionally in pre-pad and padstages for near well clean up and also to serve as a bridging agent. The observation well for microseismicmeasurements was located around 100 m [328.1 ft] south and with the maximum principal stress directionbeing N17W, some bias in fracture-wing dimensions may be expected. As a first step, based on the logdata, a preliminary model was constructed and treatments for various stages were designed on that basis.

Figure 9Pressure History Match of fracture treatment in lower Juan-dah (stage 3) of Well A.

Figure 10Pressure History Match of fracture stimulation treatment inupper Juandah (stage 5) of Well A.

12 SPE-173378-MS

Proppant concentrations were designed up to a maximum of 5 lbm/gal [599 kg/m3] to provide optimalfracture conductivity in low moduli coals.

Fracture diagnostic tests were conducted prior to some of the treatments for determining fractureclosure and fluid efficiency. Pressure history matching was carried out on all treatments and the resultsof fracture geometry were compared with the ones obtained from microseismic interpreted geometry.Table 3 below summarizes the pressure history match and microseismic survey derived fracture geometry.

In the Table 3, pressure-match and Microseismic are abbreviated as PM and MS respectively.Proppant concentrations are shown in lbm/gal [kg/m3] or PPA and Hz denote the percent horizontalcomponent observed from tiltmeter survey data. Contrary to what maybe be expected, some of theshallower stages had lower horizontal fracture component especially in last 3 stages located at the depthsfrom 427 to 567 m [1,401 to 1,860 ft]. Permeability and Net Coal data was obtained as an input fromsubsurface team.

Figure 11Log section displaying Youngs modulus and in-situ stress curves at the end of calibration process concluding after pumping oftreatments.

Table 3Well B Summary from Injection Tests and Treatment Analysis compared to results from MS Survey.

From Logs Treatment Analysis Fracture Stimulation Details Xf, m hf, m Hz

StgNetm

PermmD

Perfm

Leak-offft/min0.5

Stresspsi

DFITpsi

F.G.psi/ft

Ratebpm

Fluidbbls

Propklbm

MaxPPA PM MS PM MS %

1 3.58 2.24 752.9 0.0032 1,963 2,071 0.795 40 1,160 66 4 33.4 61 99.4 110 37

2 1.38 5.89 711.8 0.00177 1,950 1,934 0.836 35 1,182 39 3 91.5 52.5 105.5 47 23

3 1.68 0.13 686.2 0.00175 1,650 1,707 0.734 36 1,042 32 3.35 73.2 74 96.1 77 17

4 1.06 615.7 0.00175 1,770 0.877 35 770 19 3.5 61 63.5 61.6 52 31

5 1.91 2.32 567 0.00255 1,517 1,421 0.816 35 1,661 87 4.5 129 94 94.2 89 15

6 3.51 11.9 463.3 0.0035 1,470 1,338 0.968 35 1,312 83 5 58.8 70 47.2 55 35

7 3.81 3.48 427.1 0.0041 1,536 1,552 1.097 35 1,160 66 5 39.8 90 81 50 14

SPE-173378-MS 13

Pressure Match AnalysisStage 1 of Well B was treated with 166,000 lbm [75 t] of 16/30 U.S. Mesh size proppant at 35.0 bb/min[0.0927 m3/s] at a maximum wellhead pressure of 1,990 psi [13,720.6 kPa]. A limited entry approach wasused to treat 3 of the Tarooms Coal seams perforated at depths ranging from 749.5 to 757.6 m [2,459 to2,485.6 ft] at 3.0 to 6.0 spf at 60 to 120o phasing. Fracture pressure history matching of surface data wasobtained using conventional pseudo-3D models that simulate 2D fluid flow inside the fracture. Thepressure plot on the left in Fig. 12 shows the pressure match of surface data and an overburden pressureline across the plot indicating that a large portion of the treatment the effective BHP was above theoverburden pressure; this may not be an accurate representation of pressure state inside the fracturehowever, because the near well bore related friction pressure of nearly 380 psi [2,620 kPa] is included inthe simulated bottomhole (BHP) pressure curve. If this excess pressure is removed, only a small portionof treatment prior to onset of proppant appears to treat above overburden pressure. Resultant fracturegeometry is shown on the right, where the brown dots represent microseismic events recorded during thetreatment. The simulated fracture lengths are only 55% of observed activity whereas the height is within10% of the observed values.

From a material balance standpoint if the fractures were contained vertically, the half-lengths wouldhave been longer and possibly result in geometries that could match fracture lengths inferred frommicroseismic data. In all simulation runs, a symmetrical bi-wing fracture was assumed for simplicity.Hydraulic fracturing in coal is difficult to model, but in this case it is apparent that the thin coal seamsdo not dominate the fracture growth mechanism in either direction. The fracture complexity is introducedonly by the presence of a horizontal fracture component up to 37% measured by tiltmeters, which is nottraditionally accounted for in most fracture simulators. Simulated BHP clearly shows that there was ampleenergy in the system to raise the overburden and re-orient the fractures in the horizontal plane, especiallyduring early stages of injection.

The pressure history match of Stage 5 on the other hand resulted in fracture geometries that wereextremely close to the observed values. One plausible explanation of this is the limited presence of smallhorizontal fractures (15%) and lower in-situ stresses. A diagnostic test was pumped in the zone prior tothe main treatment where a fracture closure pressure of 1,421 psi [9,797.5 kPa] was identified. This wasclose to the log derived value of 1,410 psi [9,721.6 kPa] but lower than averaged matched value of 1,517psi [10,459.2 kPa]. Fracture pressure history match and associated geometry are shown in Fig. 13.

The fact that most fracture simulators are designed to handle relatively simple cases of homogenousrock fabric is evident here. The reasonably good pressure history match of this treatment is not acoincidence but a proof that most simulators can provide a reasonably good and agreeable results if theyare used in applications they are designed for. The pay interval that is fracture stimulated in this stage liesin a depth range that corresponds to normal stress regime where in-situ stresses can be easily defined bythe uniaxial stress equation presented in the section above. There is only a 6% difference between

Figure 12Pressure history match of treatment data in Well B shows a good match but inaccurate representation of geometry. The fluid section inthe fracture is shown in blue shade and the proppant is depicted with shades of yellow and brown with increasing proppant concentrations insidethe fractures.

14 SPE-173378-MS

calculated and measured stresses and the overburden line drawn on pressure plot above clearly shows thatafter initial near wellbore clean up, the remaining BHP was considerably lower than overburdencorroborating the findings from tiltmeter survey that showed a mere 15% horizontal fracture component.

Diagnostic injection tests pumped prior to the treatment in stage 6 showed a usually high fracturegradient of 0.961 psi/ft [21.738kP/m]. To accommodate this, the stress profile in the geomechanical modelhad to be changed considerably in order to obtain a match as shown in Fig. 14 below. The stage forcreating and propagating horizontal fractures was thus already set and much of it was observed in themircoseismic survey during the treatment.

As seen in the pressure plot on the left of Fig. 14, the start of the treatment is marked by high surfacepressures mainly due to near well restrictions which are eventually removed with 100 mesh sand sweeps.In the later part of the treatment as the higher proppant concentrations are admitted in the perforations,the pressure resurges, indicating restrictions in the entryway to the hydraulic fractures created duringpumping. The restricted width is also a characteristic of horizontal fracture component that readily acceptsfluid but due to low width may not accept proppant easily (Daneshy 2003). The horizontal componentdetermined from tiltmeter survey is around 35% which puts most of the microseismic events close in ahorizontal plane around the perforated depth interval. Fracture height from microseismic survey is around55 m [180.45 ft] which is close to the matched value of 47.2 m [154.85ft]. However, the simulated fracturelengths are shorter by 16%. Under these conditions where the minimum horizontal stresses are close tovertical stresses, a small gain in net pressure has a potential to re-orient the fractures in the horizontalplane.

The last stage of Well B was treated with similar design as first stage but with higher maximum sandconcentration of 5.0 PPA [599.13 kg/m3] and nearly 40.0 bbl/min [0.10599 m3/s] with cross-linked gel.

Figure 13Pressure history match of stage 5 in Well B is shown above. Both pressure match and corresponding fracture geometry show a favorablesimulator performance.

Figure 14Pressure history match and corresponding geometry of stage 6 in Well B is shown above. Note that the simulated BHP shown in thepressure plot in the left even after removing near well choke effects are considerably higher than the overburden and falls marginally below that onlyafter the treatments ends, as seen in ISIP.

SPE-173378-MS 15

The treatment was placed successfully in the shallowest upper Juandah coal seam. Prior to the maininjection, a fluid efficiency test was performed with 2% w/w Potassium Chloride (KCl) as is shown in Fig.15 below. Fracture closure pressure was identified at 1,552 psi [10,700.7 kPa] resulting in a fracturegradient of 1.08 psi/ft [25.064 kPa/m] which is higher than the known 1.0 psi/ft overburden pressuregradient. For majority of the treatment, the effective BHP exceeded overburden pressure which is alsoevident from end of treatment ISIP. This remains the case even if friction pressures of 560 psi [3,861 kPa]are removed from simulated BHP. The fracture geometry indicates a well contained vertical fracturewithin the bounds defined by microseismic events and in sharp contrast to observed fracture gradients andBH injection pressures, the tiltmeter survey indicates only 14% horizontal component. The fracturecontainment may also be because of the limited pad volume used despite at higher leak-off observed inthe diagnostic tests.

The log section shown in Fig. 16 compares the measured and calibrated properties used in fracturemodels for Well B. As was noted in the discussion above, the log-based stress model predicts the stressesclosely and depths greater than 550 m [1804.46 ft] but in shallower regions close to 400 m [1,312.34 ft]higher fracture gradients are observed. This is observation is consistent throughout the field as shown byschematic in Fig. 17 (courtesy Paul, P. 2011).

Figure 15Pressure history match and corresponding geometry of stage 7 in Well B is shown above. The microseismic events show a verticallycontained fracture.

Figure 16Log section shows the summary rock mechanical properties and stresses used in modeling after calibrating them with measure data. Thedeparture from predicted stresses is evident in shallower depths.

16 SPE-173378-MS

Case History: Well CWell C was drilled to 1,032 m [3,385.8 ft] and a 7inch [177. 8 mm], 20 lbm/ft [29.76 kg/m] casingwas set and cemented. The region is characterizedby intermediate differential stresses that fall in therange of 600 to 750 psi [4,136.85 to 5,171.1 kPa].The maximum horizontal principal stresses and coalfracture orientation are mostly aligned and trendingin WNW-ESE, N60W direction. However coal frac-ture analysis from image logs indicates the presenceof a pronounced fracture sub-set which trends WSW ENE, at N80E. The 1D Stress profile shows apossible transition from reverse to strike slip stressregime below 400 m. All fracture treatments were atdepth with a dominant strike-slip stress regime.

All the 3 stages in the hydraulic fracturing treat-ment were pumped with only water treated with 2%w/w KCl solution for clay control. The objectivewas to study the effect of treatment type on wellperformance. 16/30 U.S. Mesh size proppant wasused in concentrations to provide conductivity. Asin previous case, 100 U.S.Mesh size sand was pumped in initial stages for removing any near wellrestrictions. The treatments were pumped at various rates ranging from 40 to 50 bbl/min [0.10599 to0.1325 m3/s]. Table 4 below summarizes the critical data from Well C.

Pressure Match AnalysisFracture diagnostic tests were conducted prior to the main treatment on the first stage and the results fromanalysis showed the fracture gradients to be nearly 0.864 psi/ft [19.554 kPa/m]. During the treatment, thepumping rates were increased up to 45 bbl/min [0.11924 m3/s] in an attempt to pump the proppant awaybut ultimately the treatment was prematurely flushed because of continuously increasing surface pres-sures. A total of 50,000 lbm [22.7 t] sand was pumped using nearly 6,021 bbls [957.3 m3] treated fluid.

Microseimic survey in the stage shows dense cluster of events and despite a known presence of strongstress anisotropy and a well-defined maximum principal stress and coal fracture orientation, the inducedfractures do not show a particular fracture azimuth. A cloud of microseismic events roughly shows thefractures trending in E-W direction. As in traditional slickwater treatments, pressure matching is not easyowing to several undulations in pressures which are responses from fluid/rock interaction and also toproppant admittance in the formation via semi-open perforations. Fracture widths are a strong function offluid viscosity as shown earlier, the lack of which results in smaller fracture widths that hinders the entryof proppant in the fractures. This results in abrupt increases in treating pressures which was also seen inmost of the treatment stages in Well C.

Fracture pressure history match and associated geometry for stage 1 is shown in (Fig. 18). Simulatedfracture half lengths are close to the geometry inferred through microseismic events. Despite severalattempts a good surface pressure history match could not be obtained owing to the inability of fracturesimulator to accurately predict the pressure responses, especially for slickwater treatments. The BHP datapresented in pressure plot of Fig. 18 suggests that for majority of treatment the pressures were above theoverburden pressure though it must be noted that the data is calculated and not from downhole pressuregage. Despite complexity in fractures as is evident with layout of microseismic events, vertical component

Figure 17Field calibrated stress map for Well B shows general char-acteristics and stress regimes. Plot was constructed on basis of variousdata sources mentioned in the legend.

SPE-173378-MS 17

of fracture would tend to dominate the fracture composition due to fracture gradient that remains belowthe overburden pressure if near well related pressures are removed from simulated BHP.

Pressure history matches based on conventional models build for stages 2 and 3 were far fromrepresentative of the geometries obtained from microseismic survey. This was mostly expected, based onthe knowledge of stress regime in the region which puts the upper 2 stages in the strike-slip region wherecomplex fracturing with a large horizontal component would occur readily.

The stress profile picture on the right in Fig. 19 below shows the increase in the upper barrier stresscarried out on the model to achieve the fracture geometry that resembles closely with the geometry frommicroseismic survey. It is unrealistic to have stress differences of this magnitude in bounding layers as isshown in the schematic on right; however most simulators are sensitive to these and offer stress contrastas the only dominant mechanism to contain vertical fracture growth. Most modern day fracture simulatorsoffer limited options for height growth control other than stress manipulation. Those that do offer such afeature, handle relatively simple layering formats that were found to be inapplicable here.

In addition to the data presented in the paper, analysis of several other wells that were fracturestimulated in the campaign was carried out to improve the understanding of stress environment in theSurat Basin. This analysis also led to changes in legacy pump schedules that were mostly adapted fromcoal bed methane fracturing treatments worldwide but were eventually altered after realizing the unique-

Table 4Well C Summary of Results and comparison with microseismic survey.

From Logs Treatment Analysis Fracture Stimulation Details Xf, m hf, m Stg

StgNetm

PermmD

Perfm

Leakoffft/min0.5

Stresspsi

DFITpsi

F.G.psi/ft

Ratebpm

Fluidbbls

Prop1bm

MaxPPA PM MS PM MS

1 7.74 0.45 982.4 0.0053 2,784 2,778 0.864 40 6,021 50,000 0.75 97.5 110 106.7 45

2 3.67 0.028 806.6 0.0105 2,975 3,163 1.125 51.5 2,820 31,500 1 171.5 300 85.7 40

3 1.41 0.3 672.7 0.02626 3,074 3,074 1.393 50 4,323 34,400 1 131 185 69.7 48

Figure 18Pressure history match and corresponding geometry of stage 1 in Well C is shown above. Simulated fracture half lengths agree withobserved values, however simulated fracture height is nearly twice of observed values.

Figure 19Well C Fracture geometry details from pressure match on stage 1. Stress profile shown in the left picture was altered to obtain the matchon geometry. Most modern-day simulators offer limited options for height-growth control.

18 SPE-173378-MS

ness of Surat basin coals. In order to create a base-line for fracture geometries and for purpose of com-parison, the above exercise was repeated using adifferent simulator commercially available in theindustry.

The results from the findings are presented inTable 5 above and show that in most cases thedifferences in the geometry persisted. In the table,column headers, Sim A and Sim B representfracture simulators A and B.

Fracture Vertical GrowthIn complex stress regimes such as seen in the ex-amples presented in the paper, the role of geome-chanics should be integrated in fracture simulators.Due to shallow depths and presence of strike-slipand reverse-slip stress regimes, the induced frac-tures are multi-component and are not wholly rep-resented by planar fracture models both in geom-etry and pressure responses. However, as noted byprevious researchers (Palmer and Sparks 1991) thefracture behavior in thin coals measures will bedominated by the properties of interburden andhence the fracture growth in vertical direction willbe influenced by the mechanical properties of the surrounding layers as well. This however does notprevent the fractures from bifurcating into horizontal and vertical components, as was seen amply invarious tiltmeter surveys.

Observations from Microseismic SurveyMicroseismic survey was carried out in some of the pilot wells and the results offered a great insight intofracture behavior under various treatment types. When microseismic events from survey data werearranged next to formation mechanical property data obtained from logs, as shown in Fig. 20 and 21 forWell B (cross-linked gel) and C (slickwater) respectively, it was seen that the events tended to stay withinthe bounds created by modulus layer contrast. This is highlighted in both plots by blue circles. The effects

Table 5Comparison of Fracture Geometries utilizing various fracture simulators.

Stg Well Perf m

Fracture Half Lengths, Xf (m) Fracture Height, hf (m)

MS Sim A Diff. % Sim B Diff. % MS Sim A Diff. % Sim B Diff. %

1 B 752.9 61 33.4 -45% 67.1 10% 110 99.4 -10% 114.3 3.9%

2 711.8 52.5 91.5 74% 91.5 74% 47 105.5 124% 105.5 124.5%

3 686.2 74 73.2 -1% 73.2 -1% 77 96.1 25% 96.1 24.8%

4 615.7 63.5 61 -4% 61 -4% 52 61.6 18% 61.6 18.5%

5 567 94 129 37% 122 30% 89 94.2 6% 119.8 34.6%

6 463.3 70 58.8 -16% 54.9 -22% 55 47.2 -14% 115.9 110.7%

7 427.1 90 39.8 -56% 61 -32% 50 81 62% 122 144.0%

1 C 982.4 110 97.5 -11% 140.9 28% 45 106.7 137% 120.8 168%

2 806.6 300 171.5 -43% 47.3 -84% 40 85.7 114% 100.6 152%

3 672.7 185 131 -29% 61 -67% 48 69.7 45% 60.4 26%

Figure 20Microseismic events on all treatments on Well B are pro-jected alongside the Youngs Modulus and Poissons ratio curve to seepossible effect of property changes on vertical growth containment.

SPE-173378-MS 19

of modulus layer in vertical growth containment have been studied extensively in past (Cleary 1980, Guand Siebrits 2008).

The effect is however not uniform throughout because of the variation in response. This only indicatesthat the fracture vertical growth is controlled by a multitude of factors and the data can be interpreted inmany ways. Note that the fracturing treatments pumped with cross-linked fluid as in Well B exhibitedhigher vertical growth in comparison to the jobs pumped with only 2% KCl water in Well C.

Rock Mechanical PropertiesHigher Poissons ratio in coals (see PR track in Fig. 20 and Fig. 21 above) usually results in normallypressured formations to have higher stresses than the bounding inter-burden sandstones as is also reflectedin Eq. (4). Thus a fracture initiating from higher stressed coals would be attracted to relatively lowerstressed surrounding layers of inter-burden because it requires relatively less energy to propagate inlow-stress environment. This can potentially result in an uncontrolled height growth in lower stressedbarriers. It must be noted here that in majority of diagnostics test, the coals seams exhibited a lower bulkstress which is somewhat anomalous when strictly following Hubbert and Willis relation for stresscalculations shown in Eq. 4 above.

Fracture propagation across interfaces of varying mechanical properties also affects the fracture growthand may abruptly blunt the fracture (Simonson et al. 1978). Gu and Siebrits (2008) also note thatdepending on whether the fractures are crossing from low to high Youngs Modulus or vice-versa, somehindrance to growth may be expected although it is governed by different mechanisms. In the former case,both, the resulting fluid pressure inside smaller fracture widths in higher Youngs Modulus rock, andhigher stress intensity factor associated, as shown in Eq. (6), dominates fracture propagation. In the latterhowever, the growth is mostly influenced by the smaller stress intensity factors associated with lowYoungs Modulus rock that prevents it from matching the formation fracture toughness, thus limitingfracture propagation. In their simulations during parametric study, Gu and Siebrits showed higher growthwhen the fractures traversed form low modulus to higher modulus rocks, which is relevant to Surat coalseams where interburden has higher Youngs Modulus than coals by a factor of 6 or more in some cases.

In another mechanism influencing height growth, when fracturing across layered formations, anyinterface with low cohesive strength and friction coefficient, can act as a plane of weakness and result in

Figure 21Microseismic events on all treatments on Well C are projected alongside the Youngs Modulus and Poissons ratio curve from logs. Thesetreatments were pumped with only treated water in a region that is characterized by strike-slip and reverse stress regimes.

20 SPE-173378-MS

slippage which can cause a fracture to thus terminate at the plane of weakness (Warpinski 1981). A mixof horizontal and vertical fractures has been routinely seen in mine back operations in coals (Jeffery et al.1992); however, this phenomenon cannot be modeled very effectively though some researchers (Gu et al.2008) have recently made an attempt by creating an arbitrary variable of shear stiffness that ultimatelycalculates the amount of deformation between formation layers and thereby determines the fracture widthprofile where a slip could potentially occur. A high shear stiffness value implies perfect bonding andno-slip conditions whereas low values can result in slippage.

Fracture Plane Orientation and Back StressAs noted earlier, for most of the completions in Surat Basin where the in-situ stresses start transitioningto strike-slip regime around 500 to 600 m depths, the fractures no longer remain in vertical plane but aregenerally a mix of vertical and horizontal component to almost 100% horizontal in shallower depthsstarting from 400 m and less, where the reverse stress regime sets in. Even in the deeper depths seen sofar, there was always a presence of horizontal component in the fracture system mapped using tiltmeters.This can be attributed to the structural make up of coal that is generally complex, layered and with a cleatsystem that provides ample sites for shear failures related to slippage. Such effects are not adequatelyaddressed in most of the commercially available fracture simulators. Furthermore, at depths where theminimum principal horizontal stresses are only marginally lower than vertical stresses, any excess netpressure that is generated during fracturing process, can cause the fractures to re-orient in horizontal planeby lifting the overburden.

In a heavily fractured or cleated rock system such as coals, injection of low viscosity fluids incombination with other factors can sometimes result in a pressure signature that mostly points to anapparent net pressure gain or what is generally termed as Back Stress. Also, higher effective pressuresand vertical fractures in coal seams can result in cleat-compression and subsequent loss of permeability(Palmer 1993) which can further exacerbate the situation if the pumping continues. This apparent stressgenerated under these conditions has little influence on fracture geometry as it is not directly applied tothe fracture. In these cases, the BHP generated in excess of in-situ stress is not pure net pressure but alsoreflects fractured systems inability to effectively transmit the pressures to surroundings thus creating apressure trap that enhances the local stresses in wellbore area and gives a false sense of net pressure gain.

Figure 22Injection in Well B prior to main treatment on lower Juandah shows increasing pressure response with subsequent injections. Red arrowshows the increase in ISIP without using proppants.

SPE-173378-MS 21

If these excessive pressures are not dissipated effi-ciently in the formation the resulting surface pres-sures would continue to rise as more volume ispumped, which would ultimately lead to a prema-ture screen out. The effect is more pronounced inhigh permeability softer rocks such as the coalseams in Surat Basin and also where the formationfluid has low compressibility which again is true formost coal seams where free gas is not present.

This behavior was seen during diagnostic testscarried out just prior to the treatment in stage 1 ofWell B, as shown in Fig. 22, where two subsequentinjection tests that were carried out after a brief shut-down, resulted in higher fracture closures. The initialinjection was carried out with 100 bbls [15.89 m3] of 2% KCl water pumped at 20 bbl/min [3.18 m3/min]which was later on followed by a mini-frac of 440 bbls [69.95m3] of 20 lbm/Mgal [2.38 kg/m3] Boratecross-linked fluid. While some gain in net pressure is expected when higher viscosity fluid enters thefracture, it is generally not expected that these injections would re-stress the coal in excess of 650 psi [4.48MPa] as was observed here. It is believed that the initial injection of low viscosity fluid aided in enhancingthe complexity in the near well region which was also corroborated by pressure responses seen in earlyportion of pressure decline after shut-in. The fully-coupled mode in some of the fracture simulators allowsfor poro-elastic affects to be included in the simulation. These generally result in higher net pressure gainswhen back stresses induced by rock poro-elasticity and thermal conductivity are taken into account.Attempts to simulate the behavior using these features were moderately successful as the quality ofpressure-match is average. In all the simulations shown in Fig. 22, the observed net pressure increase of650 psi could not be obtained the simulated net pressures as the end of second injection are nearly 350psi less. However, the late period pressure decline simulated by the simulator under pore-elastic orcoupled model, matches well with the actual decline observed.

Fracture Design OptimizationDespite their limitations seen during the fracture modeling and analysis process in coals, it was generallyobserved that in the depth ranges where the vertical fractures dominated, the planar mode fracturesimulators provided a good estimate of fracture parameters. A typical simulation run in the simulator oftensuggested a vertical growth for the given conditions which was often viewed as over prediction of fractureheight; however after modeling efforts and comparison with results from microseismic survey, it wasapparent that vertical growth does occur and that apart from mechanical properties of relatively thin coalseams, even the inter-burden properties played a significant role in fracture propagation.

Figure 23Simulated fracture geometry when using existing pump schedules on calibrated geomechanical model. Note the excessive height growthand proppant placement in non-pay.

Figure 24Fracture geometry simulated after reduced the rate andoverall job volume. The fracture vertical growths are contained andproppant distribution inside the fracture shows improvement.

22 SPE-173378-MS

Improving Existing ModelsThe ultimate aim of the modeling exercise is to develop representative earth models that are able to predictplausible fracture geometries when applied in fracture simulators even outside the ranges that were usedto calibrate them. These models are also crucial in generating optimized treatment designs. In case ofWalloons coals, as noted earlier, it was most beneficial if the fractures remained contained and, thatmajority of the treatment was placed in the targeted coal seams.

Using the techniques described above, the continuous log based model was first calibrated using fieldand injection diagnostics data to generate a calibrated geomechanical model. The model was then used inpressure history matching exercise and the resultant geometries were taken as baseline for the givenconditions. In the next step aimed at optimizing fracture designs, with the an added objective of limitingfracture vertical growth and maximizing conductivity, basic net pressure principals described in Eq. 7above were utilized. Pumping rates and fluid viscosity were lowered and an improved pump schedule tomaximize fracture conductivity was employed similar to the approach (Pandey and Agreda 2010) adoptedduring fracturing treatment campaign carried on low permeability shallow sandstone reservoirs in ChittimField, south Texas, USA.

The output from simulator runs showed that for the same base fracture model, the new designsprovided a better placement with improved proppant distribution up to 3.0 lbm/ft2 [14.65 kg/m2] insteadof 2.0 lbm/ft2 [9.76 kg/m2]earlier and better containment of fracture height. The designs not only usedlower fluid and proppant volumes but also reduced equipment and horsepower requirements. Fig. 23shows fracture geometry simulated using current designs and Fig. 24 shows fracture geometry resultingfrom an altered pump schedule and fluid selection when applied on identical model.

Well PerformanceThe above exercise was a continuous process and helped in understanding the limitations of fracturestimulators used for modeling, but nevertheless the improved understanding also allowed the engineers tomodify some of the existing legacy pumping schedules to the ones that were perceived as moreengineering solutions. As the campaign progressed, it was increasingly clear that substantial portion of

Figure 25Plot indicates improvement in well performance with lowering of pumping rates. Gel loadings were also lowered in subsequent treatments(not shown here).

SPE-173378-MS 23

fracture treatment was ending up in non-productive interburden which resulted in concerted efforts toavoid that. It was felt that by reducing treatment rates and fluid viscosity, and by modifying the pumpingschedules to allow large volumes of higher concentration slurry, the treatment would be more successful.This resulted in modification of fracture treatment designs with the major limitation only being the extentto which the rates could be reduced given the larger diameter (7.0 inch) casing.

The changes made in the schedule ultimately resulted in a favorable well performance as can be seenin the gas rate vs. fracture conductivity plot shown in Fig. 25. In some cases however, premature screenouts were also witnessed. In-depth analysis showed that most of these were related to fracturing fluidinstability arising out of source water inconsistency. The issues were addressed and majority of treatmentswere placed as designed.

ConclusionsDuring the current study geomechanical models were generated for several wells under the pilot wellprogram. Pertinent data obtained from multiple sources was used to carry out the analysis mainly toevaluate the ability of various fracture simulators to accurately model the observed fracture geometrytrends based on external measurement. At the end of the study, the authors made the followingconclusions:

1. Use of geomechanical models is necessary to accurately model hydraulic fractures in coal seams.2. At the end of each step in geomechanical model generation, necessary shifts in stress data had to beapplied to match observed values. Adjustments were made locally as opposed to shifting the stressesacross entire section.3. During the calibration and model building phase, reservoir pressures obtained from extendedpost-injection declines and from DST with downhole pressure gages were found to be more useful.Accurate measurement of pore pressures is strongly recommended in model building instead ofassuming a pore pressure gradient.4. It was observed that depth greater than 650 m [1,968.5 ft] where low fracture gradients existed andmajority of the hydraulically created fractures were vertical, most simulators could match the pressuresand geometry with fairly good accuracy, provided the treatments were pumped with viscous fluids. Ina nutshell, 2 of the fracture simulators used in the study could predict fracture half lengths within /-20% of observed values provided the depths exceed 615 m [2,017.7 ft].5. In shallower depths, with increasing fracture gradients and higher reported horizontal components,the variation in the geometry increased considerably.6. The treatments pumped with treated water were difficult to pressure match and there was a largediscrepancy between the predicted geometry and the observed values mostly due to the complexitiesin the fractured systems that the fracture simulators do not address efficiently.7. The presence of non-traditional stress regimes contribute to fracture complexity which can rangefrom re-orientation of fractures in horizontal planes due to lifting of overburden to abrupt truncationof fracture growth due to rapidly changing geomechanical properties. If these effects are effectivelyaccounted in the fracture simulators, a more representative fracture geometry and azimuth predictioncan be made.8. For depth ranges where predictions were reasonably good, the fracture simulators can be construc-tively used in improving placement designs.

The learnings from this study can be applied to similar shallow coal bed methane or other unconven-tional reservoirs that face a similar challenge from rock mechanics and stress regime perspective.

24 SPE-173378-MS

AcknowledgementsThe authors wish to thank the management of ConocoPhillips and Origin Energy for their permission topublish this work.

Nomenclature

d known distance, L, ft [m]E Youngs Modulus, M/Lt2, MMpsi [MPa]E Plane strain Modulus, M/Lt2, MMpsi [MPa]G Shear Modulus, M/Lt2, MMpsi [GPa]H,hf Total Fracture Height, L, ft [m]h Height of Pay, L, ft [m]KIc Critical Stress Intensity Factor, M/L

0.5t2

L Fracture Length, ft [m]P Net pressure, M/Lt2, psi [kPa]Pc Fracture Closure Pressure, M/Lt

2, psi [kPa]Pf Fracture Pressure, M/Lt

2, psi [kPa]Pp Pore Pressure, M/Lt

2, psi [kPa]Pr Reservoir Pressure, M/Lt

2, psi [kPa]Ptip Pressure at Fracture Tip, M/Lt

2, psi [kPa]qi Injection Rate, L

3/t, bbl/min [m3/s]w Fracture Width, L, inch [mm]ww Fracture width at wellbore, L, inch [mm]tc Incremental travel time compressional wave, t/L, s/ft [s/m]ts Incremental travel time shear wave, t/L, s/ft [s/m] Biots Constant, dimensionlessh Strain in minimum principal horizontal stress direction, dimensionlessH Strain in maximum principal horizontal stress direction, dimensionlessv Poissons ratio, dimensionless Equation Constant Fluid Viscosity, m/Lt, cP [Pa.s]b Bulk Density, M/L

3, lbm/gal [kg/m3]1 Maximum Principal Stress & Payzone Stress in Eq. (8), M/Lt

2, psi [kPa]2 Intermediate Principal Stress & Bounding Layer Stress in Eq. (8), M/Lt

2, psi [kPa]3,min Minimum Principal Stress, M/Lt

2, psi [kPa]Hmax Maximum Principal Horizontal Stress, M/Lt

2, psi [kPa]hmin Minimum Principal Horizontal Stress, M/Lt

2, psi [kPa]t Tectonic Stress, M/Lt

2, psi [kPa]v Vertical Principal Stress, M/Lt

2, psi [kPa]

ReferencesBarree, R. D., Barree, V. L., & Craig, D. 2009. Holistic Fracture Diagnostics: Consistent Interpre-

tation of Prefrac Injection Tests Using Multiple Analysis Methods. SPE. doi: 10.2118/107877-PA.Barree, R. D., Gilbert, J. V., & Conway, M. 2009. Stress and Rock Property Profiling for Uncon-

ventional Reservoir Stimulation. SPE. doi: 10.2118/118703-MS.Castillo, J. L. 1987. Modified Fracture Pressure Decline Analysis Including Pressure-Dependent

Leakoff. SPE. doi: 10.2118/16417-MS.

SPE-173378-MS 25

Cleary, M.P. 1980. Analysis of Mechanisms and Procedures for Producing Favourable Shapes ofHydraulic Fractures. Paper SPE 9260 presented at the 55th Annual Fall Technical Conference andExhibition, Dallas, Texas, USA, 2124 September. doi: 10.2118/9260-MS.

Cook, A.G. and Draper, J.J. 2013, in: Jell, P.A Geology of Queensland, Geological Survey ofQueensland, Australia.

Daneshy, A. 2003: Off-Balance Growth: A New Concept in Hydraulic Fracturing. J. Pet Tech (Apr.,2003) 7885. http://dx.doi.org/10.2118/80992-JPT.

Draper, J.J. 2013, in: Jell, P.A. (ed.) Geology of Queensland, Geological Survey of Queensland,Australia.

Brooke-Barnett et al 2012, PESA East Australian Basins Symposium, Brisbane September 11-14extended abstracts.

Fisher, M. K., & Warpinski, N. R. 2012. Hydraulic-Fracture-Height Growth: Real Data. SPE. doi:10.2118/145949-PA.

Brooke-Barnett, S., Naidu, S. K., Paul, P. K., Flottman, T., Kirk-Burnnand, E., Busetti, S., Hennings,P., Trubshaw, R. L. 2013. Influence of in Situ Stresses on Fracture Stimulation in the Surat Basin,Southeast Queensland. SPE. doi: 10.2118/167064-MS.

Gu, H. and Siebrits, E. 2008. Effect of Formation Modulus Contrast on Hydraulic Fracture HeightContainment. SPE Production and Operations 23 (2): 170176. SPE-103822-PA. doi: 10.2118/103822-PA.

Gu, H., Siebrits, E. and Sabourov, A. 2008. Hydraulic-Fracture Modeling with Bedding PlaneInterfacial Slip. Paper SPE 117445 presented at the Eastern Regional/AAPG Eastern Section JointMeeting, Pittsburgh, Pennsylvania, USA, 1115 October. doi: 10.2118/117445-MS.

Hubbert, M.K. and Willis, D.G. 1957. Mechanics Of Hydraulic Fracturing, 210. Petroleum Trans-actions, AIME.

Jeffrey, R. G., Brynes, R. P., Lynch, P. J., & Ling, D. J. 1992. An Analysis of Hydraulic Fracture andMineback Data for a Treatment in the German Creek Coal Seam. SPE. doi: 10.2118/24362-MS.

Johnson, R. L., Glassborow, B., Datey, A., Pallikathekathil, Z. J., & Meyer, J. J. 2010. UtilizingCurrent Technologies to Understand Permeability, Stress Azimuths and Magnitudes and theirImpact on Hydraulic Fracturing Success in a Coal Seam Gas Reservoir. SPE. doi: 10.2118/133066-MS.

King, G. E. 2010. Thirty Years of Gas Shale Fracturing: What Have We Learned? SPE. doi:10.2118/133456-MS.

Morales, R. H., & Marcinew, R. P. 1993. Fracturing of High-Permeability Formations: MechanicalProperties Correlations. SPE. doi: 10.2118/26561-MS.

Nolte, K.G. 1991: Fracturing-Pressure Analysis for Non-Ideal Behavior. J. Pet Tech (Feb., 1991)210218. http://dx.doi.org/10.2118/20704-PA

Nolte, K. G. 1986. Determination of Proppant and Fluid Schedules From Fracturing-PressureDecline. SPE. doi: 10.2118/13278-PA.

Palmer, I.D. and Sparks, D.P. 1991. Measurement of Induced Fractures by Downhole TV Camera inBlack Warrior Basin Coalbeds. JPT 43 (3): 270275; 326-328. SPE-20660-PA. doi: 10.2118/20660-PA.

Palmer, I. D. 1993. Induced Stresses Due to Propped Hydraulic Fracture in Coalbed Methane Wells.SPE. doi: 10.2118/25861-MS.

Pandey, V. J., & Agreda, A. J. 2014. New Fracture-Stimulation Designs and Completion TechniquesResult In Better Performance of Shallow Chittim Ranch Wells. SPE. doi: 10.2118/147389-PA.

Simonson, E. R., Abou-Sayed, A. S., & Clifton, R. J. 1978. Containment of Massive HydraulicFractures. JPT 18 (1): 2732. SPE. doi: 10.2118/6089-PAent.

26 SPE-173378-MS

Sneddon I.N. Elliot H.A. 1946. The opening of a Griffith crack under internal pressure. Applied Math1946;4:2627.

Warpinski, N.R., Tyler, L.D., Vollendorf, W.C., and Northrop, D.A. 1981. Direct Observation of aSand Propped Hydraulic Fracture. Sandia National Laboratories Report No. SAND81 0225.Livermore, CA (May).

Zoback, M.D. 2007. Reservoir Geomechanics, Cambridge University Press. 449pp.

SI Metric Conversion Factors

cP 1.0* E-03 Pa.sin 2.54* E-01 cmft 3.048* E-01 mft2 9.290 304* E-02 m2

ft3 2.831 685 E-02 m3

gal 3.785 412 E-03 m3

lbm 4.535 924 E-01 kgpsi 6.894 757 E00 kPabbl 1.589 873 E-01 m3

bbl/min 2.6497 884 E-03 m3/s

SPE-173378-MS 27

Applications of Geomechanics to Hydraulic Fracturing - Case Studies from Coal StimulationsIntroductionHydraulic Fracture ModelingTypical Simulator Inputs

Critical parameters in Geomechanical modelsFracture Complexity and Fracturing SimulatorsGeological BackgroundStress CharacterizationStress

Generating Log-Based ModelsPreliminary Data CalibrationAdditional Corrections to the Mechanical Property Model

Case HistoriesCase History: Well B

Pressure Match AnalysisCase History: Well C

Pressure Match AnalysisFracture Vertical GrowthObservations from Microseismic SurveyRock Mechanical PropertiesFracture Plane Orientation and Back Stress

Fracture Design OptimizationImproving Existing ModelsWell Performance

ConclusionsAcknowledgements

References