IPA13-G-144

PROCEEDINGS, INDONESIAN PETROLEUM ASSOCIATION Thirty-Seventh Annual Convention & Exhibition, May 2013

FROM PETROPHYSICS TO ROCK MECHANICAL PROPERTIES: A SUPPORT TO SHALE-

GAS HYDRAULIC FRACTURING PROGRAM IN COOPER BASIN, AUSTRALIA

Naslin*

ABSTRACT Unconventional shale-gas reservoirs are emerging exploration targets for the petroleum industry in the Cooper Basin, South Australia. This interest derives from the recent success of the Permian Roseneath and Murteree shales that are thermally mature and contain high-organic source rocks. This paper presents a case study of mechanical rock properties for a shale-gas reservoir within the Cooper Basin. Acoustic and nuclear wireline petrophysical log data was used to determine the dynamic rock moduli that improved our understanding of the rock parameters. The rock dynamic moduli were calibrated to the static Young’s Modulus and Poisson’s Ratio from core tri-axial tests to determine mechanical properties of the targeted reservoir. Young’s Modulus and Poisson’s Ratio are also combined to predict induced fracture complexity (‘pseudo brittleness’). Lower values of Poisson’s Ratio indicate the rock will be more brittle (Rickman et al., 2008). To design a hydraulic fracturing program, an estimation of fracture closure pressure is an important requirement. This pressure is determined by the overburden pressure (a function of depth and rock density), pore pressure, Poisson’s Ratio, porosity, and tectonic stresses. To validate the calculated closure pressure, a calibration from a mini-frac diagnostic is performed. The results of this case have improved our understanding of how shale gas in the Cooper Basin should be completed and commercially produced.

INTRODUCTION Numerous oil and gas fields in the Cooper Basin point to the Permian shale as the effective source rocks. These shales now are emerging exploration targets for unconventional shale-gas plays, where the Roseneath, Epsilon, and Murteree formation (REM) is the most prolific shale-gas identified in

* Halliburton

the basin. Based on the same deposition, stratigraphy, and lithological similarities, the Roseneath and Murteree shale have the same geochemical, petrophysical, and geomechanical characteristics. The REM source rocks are dominated by Type III kerogens derived from plant assemblages. Initial mineralogical data indicate that these shales consist mainly of quartz, feldspar, carbonate (mainly iron-rich siderite) and clay (predominately illite). In spite of the lacustrine depositional origin, this lithology appears brittle and could respond well to hydraulic fracturing. As part of a shale-gas exploration program in recent well drilling, a wireline logging program has successfully completed through the Permian section and core samples from the Roseneath and Murteree shale have been obtained. These data have been integrated with existing data to improve our understanding of the characteristics of these potential shale reservoirs. This is essential to complete the wells and commercially produce the hydrocarbons.

METHODOLOGY Visual interpretation of logs for shale gas is not simple. High resistivity with high gamma ray and low density are usually the first indicators of shale gas. Resistivity and gamma ray measurements are higher than in surrounding shales due to the increased organic material. Bulk density measurements are lower than in the surrounding shales for the same reason. However, in shale reservoirs, petrophysical evaluation cannot be performed using conventional methods. Figure 1 shows a petrophysical evaluation for shale-gas also includes geochemical and geomechanical evaluations. A practical method, the DeltalogR technique, for identifying and calculating total organic carbon in organic-rich rocks has been developed by Passey et al. (1990) using well logs. The method as represented by Figure 2, overlays a properly scaled porosity log onto a resistivity curve (preferably from a deep-reading tool). In water-saturated,

© IPA, 2013 - 37th Annual Convention Proceedings, 2013

organic-lean rocks, the two curves parallel each other and can be overlain, since both curves respond to variations in formation porosity. However, in either hydrocarbon reservoir rocks or organic-rich non-reservoir rocks, a separation between the curves occurs. Using the gamma-ray curve, reservoir intervals can be identified and eliminated from the analysis. The separation in organic-rich intervals results from two effects: the porosity curve responds to the presence of low-density, low-velocity kerogen, and the resistivity curve responds to the formation fluid. The DeltalogR separation is linearly related to total organic carbon (TOC) and is a function of maturity. Using a DeltalogR vs. TOC diagram (Figure 3), the DeltalogR separation can be transformed directly to TOC if the maturity can be determined or estimated. In practice, Level of Organic Maturity (LOM) is obtained from a variety of sample analyses (e.g., vitrinite reflectance, thermal alteration index, or Tmax) or from estimates of burial and thermal history. The prediction of mineralogy, kerogen, porosity, and gas saturation in shale gas reservoirs from wireline logs is the next step needed to support the mechanical properties analysis. We propose to use petrophyisical probabilistic error minimization methods to derive gas-shale volumetrics from various types of log data, including: conventional density, neutron porosity, acoustic, resistivity, natural gamma ray, and calculated TOC. Performing the calculations using this technique requires theoretical log response equations for each sensor used. Response equations have been constructed for formation mineral and fluid volumes and the response parameters for each constituent. Linear mixing laws were followed for most sensors but some, such as neutron, resistivity, and acoustic involved more complicated non-linear functions. The idea is to solve the system of simultaneous theoretical tool response equations for the mineral and fluid volumes that gave the best match to the logs. Then a mathematical solver is used to derive the solution for the formation volumes corresponding to the smallest differences between the theoretical tool responses and the logs. The output provides independent volumes of free (non-clay-bound) water, gas, and oil in the invaded and undisturbed zones, a total volume of clay-bound water, and mineral volumes (Figure 4).

To illustrate the concept, below is a simple model involving density and photoelectric absorption logs to solve for free water (VXWA), gas (VXG), quartz

(VQTZ), and illite clay (VILL). The theoretical density response, ρbth, for this simple model can be expressed as:

Where ρmf is the mud filtrate density (assuming it represents the free water density in the invaded zone investigated by the density tool), ρg is the density of gas, ρquartz represents the density of quartz, ρillite is the density of dry illite, ρcbw stands for the density of clay-bound water, and WCLPillite is the wet clay porosity of illite. A similar linear construction can be made to express the theoretical photoelectric response, Uth:

where Umf, Ug, Uquartz, Uillite, and Ucbw are the mud filtrate, gas, quartz, illite, and clay-bound water photoelectric response parameters, respectively. If a sum of volumes constraint on the two previous response equations is expressed as: Then the volume of minerals and fluids can be solved by simultaneous equations expressed in matrix form as:

Brittleness is a key factor in the formation evaluation of shale gas reservoirs, particularly for fracture stimulation design. As previously mentioned, shale is characterized by very low permeability therefore unexpelled gas in shale can be produced if sufficient fractures are introduced in wellbore. Understanding the mechanical properties of shale can guide the placement of perforations and fracture stages. The property of rock mechanics that reflects the ability of the rock to fail under stress and maintain a fracture is called brittleness (Rickman et al., 2008). Brittle shale is more likely to be naturally fractured and also more likely to respond well to hydraulic fracturing treatments. Ductile shale on the other hand, is not a good

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producer because the formation will tend to heal any natural or hydraulic fractures. Ductile shale, however, makes a good seal, trapping the hydrocarbons and preventing migration out of the more brittle shale. Sonic logs are often used to explore rock mechanic properties and the resulting moduli during formation evaluation, by converting compressional and shear wave velocity (together with density logs) to Young’s modulus and Poisson’s ratio. This moduli parameter is converted to the brittleness index of the formation as shown by Figure 5, to help quantify areas where fracture conductivity is easier to achieve.

Where: DTC = Sonic compressional delta-time (microseconds per foot) DTS = Sonic shear delta-time (microseconds per

foot) RHOB = bulk density (gram per cc)

Apart from brittleness, fracture closure stress determination is also needed when designing fracture stimulation programs. This case will use the model from Barree et al. (2009) and shown below as:

Where: Pc = Closure pressure (psi) ν = Poisson’s ratio Pob = Overburden pressure, psi Ppore = Pore pressure, psi

α = Biott coefficient ε = Strain coefficient E = Young’s Modulus

σt = regional horizontal stress According to Barree et al., closure pressure is assumed to be equal to the horizontal stresses. In fracture design only the minimum stresses are required. These may need to be adjusted to match observed treating pressure or fracture containment. The observed stresses can deviate from the theoretical stresses for several reasons. A major cause of variation is tectonic stress; which can be induced by regional or local earth movements.

Closure pressure is also controlled by net ‘intergranular’ rock stresses and pore pressure. As a productive reservoir layer is depleted it may compact as more of the total overburden stress is transferred to the rock framework. This redistribution of stress causes the horizontal net stress to increase, but at the same time the pore pressure is decreased. RESULTS AND ANALYSIS TOC Estimation A conventional triple combo log is provided from the X-1 well for petropysical shale-gas evaluation. This log is supported by 13 core samples for TOC measurement both from Roseneath and Murteree shale. As mentioned earlier, the Passey technique attempts to predict TOC weight percentage from continuous log data. Figure 6 shows the results from this approach compared with the TOC weight percentage measured from core samples. On this log, we overlay the resistivity curve onto the porosity curve (sonic, density and neutron) to get the deltalogR separation. In the interval where there is no deltalogR separation, the TOC percentage is close to zero, meaning that the interval is not a rich-organic zone. Calculated TOC from the deltalogR method is then compared to the TOC from core pyrolysis showing good correlation between the continuous calculated TOC vs. the TOC measurements. We may see some mismatch, such as on the deltalogR from neutron log on the Roseneath shale or on the deltalogR from the sonic log on the Murteree shale. This error is minimized by averaging using the Hodges-Lehman method as seen on the last track. Thus, using the deltalogR method we have a continuous TOC log as a mineral input in the petrophysical calculation for the kerogen volumetric. Mineral and Fluid Volumetric An XRD analysis was performed on an X-1 core sample to obtain matrix weight percentage. The sample is dominated by clay minerals of more than 40% in both the Roseneath and Murteree shale. Quartz is also observed at up to 30 % with moderate siderite of about 5-15 %. Other carbonate minerals, such as calcite and dolomite are also present but in trace amounts thus they are not considered for mineral calculations using the petrophysical probabilistic error minimization approach as described in the methodology section.

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Figure 7 provides a good review of the results obtained from the probabilistic approach. The plot shows most of the outputs and provides a visual rendering of the measured log reconstruction. The red curves on tracks 3-8 are the reconstruction logs which mostly match the log inputs (black curves). To validate the result, the weight percentages of some minerals from the XRD analysis are plotted along with the output curves as seen on the last track. The orange curve on this track is a continuous weight percentage of quartz, calculated from the probabilistic method. It is a good match with the quartz weight percentage from the XRD measurement (black triangle dots). Similar matching is also observed on siderite (magenta curve vs. black circle dots) and clay minerals (green curve vs black diamond dots). Final rock volumetrics for the Roseneath and Murteree shale is presented on the first track, showing the matrix is dominanted by clay and quartz with small amounts of siderite and K-feldspar. The solid kerogen volume is around 5-15% based on the TOC calculation, and there is the potential to release sorbed gas if Langmuir pressure is achieved. Total porosity is about 9-16 pu, dominanted by clay-bound water up to 8 pu and free gas has a maximum 6 pu which is the same as the free water volume.

There is an opportunity to calculate gas resources based on the above fluid volumetrics. The resources will be calculated from both free gas and sorbed gas. Free gas is the amount of gas stored in effective porosity, defined as follows:

Where: FGton = free gas per ton (scf/ton) RHOB = bulk density (g/cc) volGas = free gas volume (decp) Bg = Formation gas volume factor (rcf/scf), calculated from:

Ftemp = Formation temperature Ppore = Pore pressure Zfactor = compressibility factor for natural gas Flag = net pay interval, defined by

Swe<80%, effective porosity>2pu, and Vclay+clay-bound water<80%

Sorbed gas is the amount of gas that adsorbed onto the kerogen surface under equilibrium conditions at a given pressure and temperature. To predict the amount of sorbed gas that can be released from the kerogen, the Langmuir adsorption isotherm is applied in the formula: where: SGton = Sorbed gas per ton (scf/ton) Lv = Langmuir volume (scf/ton) adjusted for TOC Lp = Langmuir pressure (psi) Ppore = reservoir pressure (psi) TOC = total Organic Carbon (decp) Based on these equations, the gas potential for the Roseneath shale is 47.05 scf/ton for free gas and 29.87 scf/ton for sorbed gas while Murteree shale is 38.59 scf/ton for free gas and 29.08 scf/ton for sorbed gas. Mechanical Properties To determine mechanical properties being the input for pseudo brittleness, the elastic moduli (Young’s modulus and Poisson’s ratio) are required as shown in Figure 8. These elastic moduli are calculated from the sonic slowness (compressional and shear delta-time) and density logs, calibrated to the static moduli using core triaxial test data. Track 6 shows the dynamic moduli from the sonic log overlaid with static moduli from core data. The dynamic moduli logs have been converted to static moduli using a regression relationship as defined by the crossplot in Figure 9. Pseudo brittleness is defined by combining Young’s Modulus and Poisson’s Ratio as previously described by Figure 4. In terms of Poisson’s Ratio, the lower the value, the more brittle the rock. For Young’s Modulus as values increase, the more brittle the rock (Rickman et al., 2008). Figure 10 shows the brittleness in the X-1 well. The southwest corner is the quadrant where brittleness is increasing and the northeast corner is the ductile quadrant. This acoustic pseudo brittleness is also adjusted by the brittleness obtained from core measurements.

Using calibrated mechanical properties as calculated above, closure pressure can be determined. An equation from Barree (2002) is applied by incorporating static Young’s modulus,

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static Poisson’s ratio, overburden pressure, pore pressure, and porosity. The calculated closure pressure is presented on Figure 8 along with estimated pore pressure and overburden pressure. The closure pressure should be adjusted to the actual injection test or mini-frac diagnostic to accurate reflect delta stress due to regional geological strain.

Supporting a Hydraulic Fracturing Program Based on the results of the X-1 well petrophysical rock mechanical determination, a hydraulic fracturing program can be supported for shale gas in this basin. However, the X-1 well is just an offset well to the X-2 well where the hydraulic fracturing program will be implemented. Core TOC and XRD data to calibrate kerogen and mineral volume was not available yet in X-2 well, thus a petrophysical evaluation is performed based on parameters applied to X-1 as presented previously. Rock mechanical properties have a better chance to be calibrated since X-2 has mini-frac diagnostic data. Figure 11 shows the G-function of the mini-frac data used to get actual closure pressure by adjusting calculated closure pressure from rock mechanical properties. There is a delta stress between actual vs. calculated closure pressure of about 1700 psi. It may be induced by regional or local earth movement. A composite result of petrophysical and rock mechanical properties of X-2 is shown in Figure 12, including recommendations for hydraulic fracturing design. Based on formation brittleness, selection of fluid type and proppant volumes are recommended as shown in Table 1 (after Rickman et al., 2008). This table is a compilation from frac jobs previously run in US shale gas formations. If the brittleness is high like in the Barnett shale, proppant concentrations need to be low and the fluid system needs to be high-volume water since the fracture geometry becomes more complex. Therefore the proppant may act more as a wedge, providing a high conductivity flow path. As the brittleness decreases or gets more ductile like the Eagleford shale, the proppant concentrations need to be higher (embedment) and placed in the formation with less fluid (a hybrid or even an x-linked fluid). This will insure good conductivity for a possible bi-wing fracture geometry. In this case, the Roseneath and Murteree shale are in the range of 30–40% brittleness. Therefore the treatment is recommended as per the Eagleford shale. The recommendations for proppant type are based on closure pressure as

per Figure 13 (Economides et al., 1998). The calibrated closure pressure for both Roseneath and Murteree shale is 7600-8600 psi suggesting a proppant type of resin-coated sand to intermediate strength ceramic or bauxite. CONCLUSIONS As shown through the extensive petrophysical evaluations performed, Roseneath and Murteree shales are ‘sweet spots’ for shale-gas exploration and production in Cooper Basin, Australia. TOC is in the range of a good hydrocarbon producer (> 2 %). The petrophysical probabilistic method has demonstrated a good match of mineral volumetrics compared to core XRD analysis. The Roseneath and Murteree shales are moderately occupied by brittle minerals such as quartz and siderites, suggesting these shales are fracture-inducible. Rock mechanic analysis provides continuous brittleness estimation along all formations, calibrated with static moduli from core triaxial compressive tests. This shows that the Roseneath and Murteree shales are in the range of 30-40% brittleness. Rock mechanic analysis also gives a calculated closure pressure of around 7600 to 8600 psi, calibrated by a mini-frac diagnostic. A number of recommendations based on mechanical properties have been demonstrated. The recommendations are expected to obtain the best design for a shale-gas hydraulic fracturing program in the Cooper Basin, Australia. ACKNOWLEDGEMENT The author gratefully acknowledges the participation and release of data by Senex Energy Ltd., Australia. Acknowledgement is also presented to the Halliburton Production Enhancement team in Australia for their kind cooperation. This paper could not have been written without their full support. REFERENCES Barree, R.D., Gilbert, J.V., and Conway, M.W., 2009, Stress and Rock Property Profiling For Unconventional Reservoir Stimulation, SPE Hydraulic Fracturing Technology Conference, The Woodlands, Texas, USA, 19-21 January 2009. Buller, D., Hughes, S., Market, J., Petre, E., Spain, D., and Odumosu, T., 2010, Petrophysical Evaluation For Enhancing Hydraulic Stimulation in Horizontal Shale Gas Wells, SPE Annual Technical

Conference and Exhibition, Florence, Italy, 19-22 September 2010. Economides, M.J., Watters, L.T., and Dunn-Norman, S., 1998, Well Stimulation in Wiley, J., and Sons, Petroleum Well Construction, Chap 17, in Rickman, R., Mullen, M., Petre, E., Grieser, B., and Kundert, D., 2008, A Practical use of Shale Petrophysics for Stimulation Design Optimization, SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 21-24 September 2008.

Passey, Q.R., Creaney, S., Kulla, J.B., Moretti, F.J., and Stroud, J.D., 1990, A Practical Model For Organic Richness From Porosity And Resistivity Logs: The American Association Of Petroleum Geologists Bulletin, V. 74 No. 12, p. 1777-1794. Rickman, R., Mullen, M., Petre, E., Grieser, B., and Kundert, D., 2008, A Practical use of Shale Petrophysics for Stimulation Design Optimization, SPE Annual Technical Conference and Exhibition, Denver, Colorado, USA, 21-24 September 2008

TABLE 1

STIMULATION DESIGN RECOMMENDATIONS BASED ON

BRITTLENESS CALCULATION

Figure 1 - A schematic of a petrophysical method used to evaluate shale-gas potential.

Figure 2 - Resistivity vs. porosity logs overlay showing deltalogR separation in the organic-rich

interval (Passey et al., 1990).

Figure 3 - DeltalogR transformation to Total Organic Carbon using Level of Maturity (after Passey

et al., 1990).

Figure 4 - A simple schematic of rock volumetrics.

Figure 5 - Crossplot of Young’s modulus and Poisson’s ratio showing the brittleness index

increasing to the southwest corner of the plot (After Rickman et al., 2008).

Figure 6 - TOC determination using the deltalogR method. On tracks 4, 6, and 8 are the overlay

between the resistivity curve and the porosity curve (sonic, density, and neutron) to get the deltalogR separation. Calculated TOC from the deltalogR method is also compared to TOC from core pyrolysis (red dots) on track 5, 7, and 9. Error minimization by averaging using the Hodges-Lehman method is presented on track 10.

X900

Figure 7 - Fluid and mineral volumetric calculation using a probabilistic approach. Red curves on

tracks 3-8 are the reconstruction logs which mostly match the log inputs (black curves). The XRD weight percentages (black dots) are plotted along with the output curves as seen on track 10.

Figure 8 - Rock mechanical properties log from the elastic moduli calculation. Track 6 shows the

dynamic moduli from the sonic log overlaid with static moduli from core data (black dots). Calculated brittleness curves are compared to core brittleness measurements (blue dots) on track 8.

X900

X900 X900

Figure 9 - Dynamic vs. static moduli crossplot from core measurement, to convert elastic moduli

from sonic log.

Figure 10 - Crossplot of Young’s modulus and Poisson’s ratio from X-1 well data, showing the

brittleness index increasing to the southwest corner of the plot. Figure 11 - G-function analysis from X-2 mini-frac diagnostic, to correct calculated closure pressure

from mechanical properties.

Roseneath

Figure 12 - The final result of petrophysics to rock mechanics evaluation for the hydraulic fracturing program for the X-2 well. Mini-frac data (blue dots) are plotted along with calculated. closure pressure (red curve) on track 7.

Figure 13 - Proppant type recommendations based on closure pressure (Economides et al, 1998).

X500