OVERBURDEN CHARACTERIZATION FOR GEOMECHANICS AND GEOPHYSICAL APPLICATIONS IN THE ELDFISK FIELD: A NORTH SEA CASE STUDY

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1 SPWLA 52 nd Annual Logging Symposium, May 14-18, 2011 OVERBURDEN CHARACTERIZATION FOR GEOMECHANICS AND GEOPHYSICAL APPLICATIONS IN THE ELDFISK FIELD: A NORTH SEA CASE STUDY K. Kozlowski 1, M. Fidan 2, A. Donald 1, P. Shotton 1, H. Nielsen 2, N. Anderson 2, J. Jocker 1 1 Schlumberger, 2 ConocoPhillips Copyright 2011, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors This paper was prepared for presentation at the SPWLA 52nd Annual Logging Symposium held in Colorado Springs, Co, USA, May 14-18, ABSTRACT The presence of elastic anisotropy has implications for a wide range of practical applications in both the geophysical as well as geomechanical domain. For instance, stress magnitudes and orientations can be very different in anisotropic media as compared to isotropic media. Hooke s law can be used to calculate stresses along the wellbore, but in order to do so the elastic properties of the formation are required. In the case of Transverse Isotropic (TI) formations such as shales, the number of independent elastic coefficients is five. A commonly used source for information on these five parameters is comprised of borehole sonic data. Nevertheless, even in a deviated well the number of borehole sonic measurements is at most four, thus necessitating the integration of single-well borehole sonic data with relevant data coming from an alternative source. A case study is presented where sonic data from a single well were combined with offset well data in order to fully characterize the overburden shale in the North Sea Eldfisk field. The results were subsequently used to determine the minimum horizontal stress profile along the well. This stress profile was compared with fracture gradients derived using more conventional models such as Eaton s and M&K. It was concluded that stress profiles on the basis of a full anisotropic model provide a natural fit with wellbore stability observations without requiring boost factors or the introduction of unjustifiable tectonic strains. INTRODUCTION A medium that is anisotropic has properties that depend on the direction in which these properties are measured. As a practical example, elastic anisotropy leads to borehole sonic wave slownesses that have magnitudes 1 which depend on the orientation of the well with respect to the anisotropic medium. It is common knowledge that shales exhibit anisotropic behavior due to the constituent plate-shaped clay particles oriented parallel to each other (Sayers, 2005). Most shales can be described, to a good approximation, as being Transversely Isotropic with a Vertical axis of symmetry (TIV, Walsh et al., 2006). The axis of symmetry is usually assumed to be orthogonal to the shale beds. In terms of their mechanical properties, transverse isotropic media are fully described by a total of five independent elastic stiffness coefficients, a subset of which can be determined by analyzing borehole sonic data from a single well. Sonic logs provide a continuous profile of dynamic elastic parameters as input to geophysical and geomechanical models. Overburden sonic logging is the primary focus on many North Sea wells to gain an understanding of the elastic properties for seismic and geomechanical studies. The overburden formations are mainly comprised of shale. Most of the logged wells are drilled from a common location such as a platform, and as a result these wellbores penetrate the overburden at various angles, complicating the interpretation of sonic compressional and shear measurements in these intrinsically anisotropic media. The geophysics community often takes elastic anisotropy into consideration when combining offset VSP data with wellbore sonic data as the compressional measurements acquired in deviated boreholes are known to be faster than those from vertical boreholes. Similarly, the geomechanics community has also considered the effects of anisotropy for elastic stiffnesses and rock strength properties for wellbore stability and hydraulic fracturing applications (Higgins et al., 2008; Donald et al., 2009). Historical wellbore stability models in overburden rocks generally are defined by a fracture gradient bound by leak-off tests, or formation integrity tests at the casing shoes. The continuous fracture gradient is traditionally derived by a model that uses input from the overburden stress and the pore pressure (Eaton, 1969; Matthews & Kelly, 1967). However, these models do not always reflect the

2 SPWLA 52nd Annual Logging Symposium, May 14-18, 2011 variation in rock properties and thus may be inadequate for narrow mud weight windows. With the understanding of the impact of anisotropy on stress modeling for completions in layered media (Higgins et al., 2008), a similar workflow may be applied to wellbore stability models in overburden shales. This paper describes a workflow where sonic data recorded in a deviated well drilled through (more or less) horizontal shale beds, are used to characterize the elastic properties of the TI formations. It is explained how a total of four sonic slownesses can be established in a well that is drilled at a non-zero angle with respect to the TI symmetry axis. In the presented case study these four measurements are complemented with compressional data from nearby offset-wells drilled at varying orientations through the same formations, in order to obtain all of the five independent TI elastic coefficients. Once established, the TI constants will be used to calculate the minimum horizontal stress along the well trajectory, and it will be discussed how stress profiles that are based on an isotropy assumption can be very different from those calculated using the more appropriate anisotropic equations. Furthermore, it will be explained how using physically correct equations for the stress profiles may circumvent the need for boost factors such as those used in more conventional fracture gradient models such as Eaton s (Eaton, 1969) or M&K (Matthews and Kelly, 1967), or the use of tectonic strains that are hard to justify but that are required to make the incorrect isotropic results fit the observations (F.I.T, drilling-induced features visible on the borehole wall, etc.). The outline of the paper is as follows. In the Theory section we will briefly discuss the relation between stresses and strains in TI media, and how this relation can be used to calculate the minimum horizontal subsurface stress. This calculation requires, among others, knowledge of the elastic properties of the medium. Elastic wave propagation data acquired with an advanced borehole sonic tool are the most suitable sources of information on these elastic properties, and the relation between borehole sonic slownesses and the formation properties are discussed. In the Case Study section it will be described how single-well borehole sonic data are combined with compressional slowness data from nearby offset wells in order to arrive at a full elastic characterization of the overburden shales in the Eldfisk field. The estimated elastic parameters are used to calculate the minimum horizontal stress around the wellbore, and the results are compared with those 2 coming from more conventional models such as Eaton s. THEORY For a linearly elastic medium, Hooke s law provides the relationship between the stress (σ) and strain (ε) tensors (e.g., Mavko et al., 2003, chapter 2):, (1) where C is called the stiffness tensor and where we have used the abbreviated notation for the subscripts (e.g., Nye, 1985). For a transverse isotropic medium with a vertical symmetry axis (TIV), the elastic stiffness tensor C is defined as: , (2) where the TI symmetry axis is parallel to x 3. An example of a TIV medium is a horizontal shale bed. Five of the six elastic stiffnesses in equation (2) are independent, i.e. C 11, C 33, C 13, C 44, C 66 while C 12 = C 11 2C 66. Stress determination using Hooke s law Assuming the strains and the stiffness coefficients in C are known, a practical application for Hooke s law is to use it to determine the principal stresses acting inside the elastic medium. For instance, in the case of a horizontal shale subjected to gravitational loading the minimum horizontal stress equals (Thiercelin and Plumb, 1994) C C (3) where is Biot s coefficient, P p is the pore pressure, and where subscripts h, H, and v indicate the direction of the minimum horizontal, maximum horizontal, and vertical stress respectively. In the case study section of this paper we will discuss an example where equation (3) is used to determine the minimum horizontal stress. To illustrate the importance of understanding the impact of elastic anisotropy on stress profiles we will

3 SPWLA 52 nd Annual Logging Symposium, May 14-18, 2011 also compare anisotropic stress results with those coming from more conventional models like Eaton s (Eaton, 1969) and M&K (Matthews and Kelly, 1967). In order to determine the minimum horizontal stress using equation (3), further information is required on the pore pressure, Biot s coefficient, as well as the elastic properties of the shale. The pore pressure and Biot s coefficient can be obtained in various ways, ranging from trend line methods and calibration using the mud weight and connection gas for the pore pressure, to using literature values for Biot s coefficient. The primary source of information on the elastic stiffnesses is wireline sonic data. The bulk wave speeds and the borehole mode speeds that can be derived from sonic data are related to the elastic properties of the formation through well-understood relations. Due to the anisotropic nature of these formations, the slowness magnitudes depend on the orientation of the well with respect to the formation. Therefore, in order to be able to extract the elastic coefficients from the available sonic data, the well orientation needs to be taken into account. In transverse isotropic formations, the amount of information that can be extracted from sonic logs depends to a large extent on the relative dip. The relative dip is defined as the angle between the well and the TI symmetry axis. For example, a 15 deviated well drilled through horizontal shale beds will have a relative dip of 15. Wave propagation in deviated wells The simplest case to consider is that of a vertical well drilled through horizontal shale beds ( 0). In such a case, the three wave propagation modes that can be readily related to three of the five background TI parameters are the vertically propagating compressional wave (yielding C 33 ), the vertically-propagating horizontally-polarized shear wave (yielding C 44 ), plus the horizontally-propagating horizontally-polarized shear wave (yielding C 66 ) that can be obtained by processing the borehole Stoneley mode (White, 1983, pages ). In the case of a non-zero relative dip (i.e., a deviated well drilled through a horizontal shale), the number of elastic wave modes that can be related to formation properties increases from three to four. First there is the compressional bulk wave which travels in the direction of the well and which is polarized (polarization is the direction of particle motion) more or less in the direction of propagation. Because its polarization is not 3 necessarily exactly parallel to its propagation direction, this wave is usually referred to as the quasi - compressional, or qp-wave. Norris and Sinha (1993), assuming a weakly TI medium, derive the following expression for its phase velocity (1/slowness) as a function of relative dip, bulk density, and TI elastic constants: 12 sin 2sin cos (4) where, 2. 2 In addition to the compressional bulk wave there are two bulk shear waves whose slownesses can be extracted from a dipole sonic tool. The SH-wave propagates in the direction of the well with a polarization vector that is confined to the horizontal plane (this is strictly speaking only true for horizontal beds). Its phase velocity is given by 1 2 sin (5) where. The second bulk shear wave is called the quasi-sv, or qsv-wave. Here, the addition quasi refers to the fact that the propagation and polarization direction of this shear wave are not necessarily exactly orthogonal to each other. The polarization vector of the qsv-wave is contained in the plane spanned by its propagation direction and the TI symmetry axis, and its phase velocity in the weak anisotropy approximation can be calculated using 1 2 sin cos. (6) In addition to the compressional and two shear wave slownesses, a fourth input comes from analyzing the Stoneley borehole mode. This mode is, in addition to the properties of the fluid inside the borehole, also sensitive to the elastic properties of the formation surrounding the well. The Stoneley-derived formation slowness is usually called the Stoneley-shear, or the shear-from-stoneley slowness. In terms of its velocity, Norris and Sinha (1993) arrive at the following expression: 2 cos sin. (7)

4 SPWLA 52nd Annual Logging Symposium, May 14-18, 2011 Assuming that both the bulk density and the relative dip are known, expressions (4) through (7) directly relate the elastic properties of the shale to four measurable wave velocities. Since a transverse isotropic medium has not four but five independent parameters, additional information is required to fully constrain and describe the properties of the elastic medium. In the following case study the required input comes from offset compressional slowness data acquired at varying relative dips. Prior to including the offset data, elastic coefficients C 44 and C 66 are obtained following the inversion procedure proposed by Norris and Sinha (1993). slowness values than the homogeneous isotropic model curves is an additional indication that the formation at this depth is TI (Valero et al., 2009). CASE STUDY The Eldfisk oil field is located between the Ekofisk and Valhall fields in the southern section of the North Sea. The Eldfisk field produces from the Ekofisk, Tor and Hod formations, which are mainly comprised of finegrained, high porosity reservoir chalk. Eldfisk was originally developed by pressure depletion which has caused compaction in the reservoir, resulting in some settling of the seabed (Norwegian Petroleum Directorate, 2011). The overburden in the Eldfisk area is comprised of mainly shale. Validation of TI assumption Sonic data acquired in a 40 to 60 deviated well in the Eldfisk field (operated by ConocoPhillips and the PL018 Partnership) were analyzed in order to characterize the elastic properties of the overburden shale. Aare and Knoth (2002) studied the area by evaluating seismic and sonic logs and concluded that the overburden can be described, to a good approximation, as being transverse isotropic. To support this conclusion, Figure 1 shows an example of dispersion curves (cross plots of slowness versus frequency) from the Oligocene in the Eldfisk overburden. For a more extensive discussion on dispersion curve analysis the reader is referred to Plona et al. (2004). Homogeneous isotropic (HI) model curves are plotted as solid lines while the sonic data transformed to the slowness-frequency domain are plotted as colored markers. In this deviated well, the flexural dispersion curves (in red and blue) are parallel and are plotting slightly below the HI model curves. The Stoneley slowness data (cyan) are showing the same behavior and plot below the model curve. The observation that the dispersion data for the Stoneley and dipole flexural modes have systematically smaller 4 Figure 1. Dispersion plot from Eldfisk overburden showing the dipole flexural modes in blue and red, along with the Stoneley mode data in cyan. Single well sonic processing The Stoneley shear slowness (i.e. 1/v St ) was determined through radial profiling algorithms which account for near-wellbore damage and dispersion effects (Sinha et al, 2006). In order to obtain the SH and qsv shear wave slownesses, sonic data acquired from two orthogonal dipole firings were rotated in a manner resembling Alford rotation (Alford, 1986). The rotated waveforms were subsequently processed to obtain the fast and slow shear wave slownesses which correspond to the slownesses of the SH and qsv waves. Note though that it is not known in advance which mode corresponds to which slowness, e.g. does the obtained fast shear slowness correspond to the SH or the qsv wave? To resolve this ambiguity, the fast-shear azimuth (FSA) is included in the analysis. The FSA indicates the orientation of the polarization direction of the fastest of the two shear waves. The FSA is defined in the plane normal to the tool, and is reported as an angle measured from some reference point. If this reference point is the top-of-hole, then a fast shear polarization direction to the side-of-hole indicates that the fast shear slowness corresponds to the slowness of the SH wave whereas an FSA to the top-of-hole means that the fast shear slowness corresponds to the qsv wave mode.

5 SPWLA 52 nd Annual Logging Symposium, May 14-18, 2011 Single well inversion for C 44 and C 66 The SH and qsv slownesses along with the Stoneley shear slowness were used as input into the computation (Norris and Sinha, 1993) of the TI formation properties C 44 and C 66. The average bedding dip from seismic was determined to be approximately 2 to 10 and an average bedding dip azimuth of 95 was used in the Oligocene formation. Combining these bedding orientations with the well deviation and azimuth yielded a relative dip on the order of 55. To summarize, C 44 and C 66 were obtained using three out of the four available measurements (the compressional slowness is not used in the inversion for C 44 and C 66 ). Additional data would need to be included in order to fully characterize the TI medium, such as data from an offset well drilled at a different relative dip. This will be discussed next. The TIV constants C 44 and C 66 are displayed in red and green in track 4 of Figure 2. It is observed how C 66 is consistently 20% to 40% larger than C 44. Thomsen s gamma can be readily calculated from C 44 and C 66, and is displayed in track 4 as well (in purple). Gamma is seen to vary between 0.2 and 0.5. The four slownesses that were obtained in this deviated well drilled through a TI medium, are displayed in Figure 2, track 3. For the majority of the overburden evaluated, the fast and slow shear slownesses exhibited approximately 10% to 15% differences. The SH(@90deg) and qsv(@90deg) displayed in track 2 are representative of what the fast and slow shear might read when acquired in a horizontal (90º) well in the same formation. Interpretation of C 44 and C 66 The concepts of C 44 and C 66 may seem rather abstract, but these two parameters nevertheless have a clear physical interpretation that can be understood through the help of a deck of cards. Imagine putting one hand on the top, and the other hand on the bottom of the deck, followed by moving one hand to the left and the other to the right. C 44 is a measure of the shear friction between the cards in the deck that needs to be overcome in order to make the relative motion of the two hands possible. Now imagine putting one hand on the left-hand side and the other hand on the right-hand side of the deck, followed by moving one hand closer and the other hand farther away. The imaginary lines along which the hands move are parallel and remain at the same distance from each other throughout the experiment. When viewed from above, the deck that was originally rectangle-shaped is now rhomboid-shaped, a type of deformation that is called simple shear. C 66 is a measure of the shear friction that needs to be applied by the two hands on the side of the deck in order to deform the deck from a rectangle into a rhomboid. 5 Figure 2. Composite log in the Upper Oligocene formation of Stoneley, fast and slow shear input data and computed TIV shear stiffnesses C 44 and C 66. The qsv(@90deg) and SH(@90deg) are representative of what the fast and slow shear might read when acquired in a horizontal (90º) well in the same formation. Integration with offset-well data Figure 3 shows a candidate phase slowness plot from the Upper Oligocene, given the proper amount of offset information, with slownesses plotted as a function of relative dip. The red, blue, and teal curves respectively denote the SH-, qsv-, and Stoneley shear wave slowness, while the black curve represents the qp-wave slowness. These model curves were calculated using Equations 4 to 7. The measured qp-, qsv-, SH-, and Stoneley-shear slownesses from this depth in the Upper

6 SPWLA 52nd Annual Logging Symposium, May 14-18, 2011 Oligocene are plotted as points at the appropriate relative dip of about 55. hole, whereas at larger relative dips the polarization direction of the fastest shear wave will be to the side of hole. The maximum difference between the qsv and SH shear waves in this example is approximately 100 us/ft at 90º relative dip. Similar to Figure 3, Figure 4 displays slownesses as a function of relative dip in the Eocene formation. At relative dips smaller than 40, the qsv shear wave travels faster than the SH wave and hence the FSA will point to the top of the hole. Above approximately 40 relative dip, the situation is reversed and the FSA will point to the side of the hole as the SH wave is the fastest of the two shear bulk waves. Figure 3. Phase slowness plot in the Upper Oligocene showing formation slowness as a function of the relative dip angle. Measured slowness data are shown as points. The phase slownesses of qp, qsv, and SH are presented as the black, blue, and red lines. The Stoneley shear phase slowness is shown in teal. As stated previously, additional data are required in order to obtain a complete understanding of the anisotropic properties. To achieve this goal, offset compressional data from several nearby wells at different deviations were used to compliment the single-well data and to provide an improved constraint on the remaining three independent TI parameters (i.e., C 11, C 13, and C 33 ). Based on this combination of the offset well compressional data and the shear slownesses in the study well, a table of the average estimated Thomsen parameters per formation is shown: Formation δ ε γ Upper Oligocene Eocene Balder Table 1: Thomsen parameters per formation Thomsen s parameter is defined as (Thomsen, 1986). Figure 4. Phase slowness plot in the Eocene showing formation slowness as a function of the relative dip angle. Measured slowness data are shown as points. The phase slownesses of qp, qsv, SH are presented as the black, blue, and red lines. The Stoneley shear phase slowness is shown in teal. This 90-degree flip in the FSA from top-of-hole to sideof-hole with increasing relative dip was also observed in cased-hole dipole sonic data acquired in a nearby offset well which had a gradual increase in deviation toward increasing measured depths (Figure 5). In agreement with Figure 4, the FSA is seen to flip 90 degrees at a relative dip of approximately 40 to 45 degrees. The Thomsen parameters for the upper Oligocene in Table 1 were used in the calculation of the slowness curves in Figure 3. Although uncertainties remain, the Thomsen parameters in this section of the overburden give a reasonable fit with the measured shear data of the study well, offset-well compressional data, and previous seismic work. Based on Figure 3 it is expected that the fastest shear wave acquired at relative dips less than about 42 would be polarized towards the top of 6

7 SPWLA 52 nd Annual Logging Symposium, May 14-18, 2011 at 4500ft TVD) correction would be required to match the point and to be consistent with the mud weights used to drill the well. Historically, simple and robust fracture gradient models like Eaton s were used because stress models derived from sonic and core measurements always required boost factors or additional tectonic strains that were often difficult to justify. Furthermore, the accuracy of these stress models was always questioned because of the large uncertainty in the input parameters. Consideration of the anisotropic elastic properties eliminates the need for adding tectonic strains and provides a physical explanation for previously questioned isotropic models. Figure 5. Comparison of Eldfisk study well drilled at 45 to 50 deviation in the Eocene (right) and nearby offset well drilled at varying deviation in the Eocene (left). Shear anisotropy in both wells was computed relative to top of borehole. The fast shear azimuth referenced to top-of-hole (FSH_RB) is shown in red. A gradual change of fast shear azimuth direction from top of hole to side of hole with inclination was observed in the offset well. Minimum horizontal stress estimation Pore pressure, minimum horizontal stress and formation integrity test (F.I.T.) from the Eldfisk overburden are shown in Figure 6. The minimum horizontal stress was calculated using Equation 3. Fracture pressures using the Eaton Gulf Coast method (Eaton, 1969) and Matthews & Kelly (M&K) method (Matthews and Kelly, 1967) are also displayed. Pore pressure has been derived using the Eaton trend line method and calibrated using the mud weight and connection gas. The minimum horizontal stress model is computed from the five independent elastic moduli, pore pressure and overburden stress. The moduli were first converted from dynamic to static using correlations derived from core measurements. In the upper portion of the logged section the minimum horizontal stress based on Equation 3 shows a similar trend as the fracture gradients. The minimum horizontal stress did not require any tectonic strains to match the F.I.T. calibration point. If the isotropic version of this equation were used, a 200 to 300 psi (0.85 to 1.28 ppg Figure 6. Pore pressure, minimum horizontal stress from anisotropic properties, Eaton fracture pressure, Matthews & Kelly (M&K) fracture pressure, formation integrity test (F.I.T.), and overburden stress in Eldfisk overburden. The difference between C 44 and C 66 is shown as shaded yellow in the right track. In the lower portion of the logged section (below ft MD), the minimum horizontal stress is significantly lower (500 to 600 psi or 1.07 to 1.28 ppg at 9000ft TVD) than the fracture gradient. The fracture gradients are computed as a function of pore pressure and overburden stress, and they do not account for changes in rock properties (stiffness or deformation). In this lower section of the overburden directly over the reservoir, mud losses are commonly observed while drilling. Even though there is no direct leak-off test or mini-fracture data for calibration of the minimum 7

8 SPWLA 52nd Annual Logging Symposium, May 14-18, 2011 horizontal stress in this section, field observations support the interpretation of a lower minimum stress than previously predicted by traditional modeling techniques. Figure 7 shows an example of the wellbore stability window in the Eldfisk overburden. This figure shows the underestimation of the fracture gradient at shallower depths while the overestimation at deeper depths leads to a higher likelihood of losses throughout the section. Figure 7. Wellbore stability window for Eldfisk overburden showing collapse, pore pressure, and losses overlaying with the drilling mud weight and fracture gradient from the Eaton method. Predicted breakout and vertical ultrasonic caliper are also presented. SUMMARY AND CONCLUSIONS A workflow for the estimation of the elastic properties of transverse isotropic overburden shale was presented. The workflow uses four slowness measurements from a single well and integrates those four inputs with compressional slowness data acquired in offset wells drilled at varying relative dips through the same formations. The outputs of the workflow are the five independent TI constants which were subsequently used to calculate the Thomsen parameters. Failure to account for elastic anisotropy in seismic processing can lead to errors in NMO correction, dip-moveout correction, AVO analysis, and migration. For geomechanical workflows, characterization of an elastic formation in terms of its independent stiffness properties is an intermediate step towards applications such as wellbore stability studies and hydraulic fracture design. In the case study it was illustrated how, once established, the elastic properties of a formation can be applied towards deriving a continuous profile of the minimum horizontal stress along the wellbore trajectory. With regards to this case study it is worthwhile to emphasize the following: - First of all, stress profiles that are based on the assumption that formations behave isotropic can be very different from those calculated using the more appropriate anisotropic equations. Since transverse isotropic shales compose a major part of sedimentary rocks and cover many of the hydrocarbon reservoirs around the world, elastic anisotropy is the rule rather than the exception. The most direct and continuous way to determine the anisotropic elastic properties is through the use of an advanced sonic logging tool (Pistre et al., 2005). - Secondly, using physically correct equations to determine the stress profiles around the well circumvents the need for boost factors such as those used in more conventional fracture gradient models, or the use of tectonic strains that are hard to justify but that are required to make the incorrect isotropic results fit the observations (F.I.T, drilling-induced features visible on the borehole wall, etc.). In the case study it was observed that the anisotropic stress equation compared well to the F.I.T. and mud weights used to drill the well, while the isotropic equation showed up to a 300 psi difference from these measurements. Meanwhile, the minimum horizontal stress in the lower part of the overburden was observed to be up to 600 psi lower than the Eaton calculated fracture gradient. ACKNOWLEDGMENTS The authors thank ConocoPhillips and the PL018 Partnership for permission to publish the data, Mitch New, ConocoPhillips Reservoir Characterization Manager, for his support, and Schlumberger Oilfield Services for the time and effort required to publish this document. The authors also thank Erik Wielemaker for his review and many fruitful discussions. 8

9 SPWLA 52 nd Annual Logging Symposium, May 14-18, 2011 REFERENCES Aarre, V., and Knoth, O., 2002, Borehole-calibrated processing of a 2D/4C line over the Eldfisk field: SEG International Exposition and 72 nd Annual Meeting. Alford, R.M., 1986, Shear data in the presence of azimuthal anisotropy: Dilley, Texas, SEG 1986 International Exposition and Annual Meeting. Donald, A., Paxton, A., Keir, D., and Koster, K., 2009, Improving seismic calibration and geomechanical models through characterization of anisotropy using single and multi well data: Case study in Forties field, UK: SEG International Exposition and Annual Meeting, Eaton, B. A., 1969, Fracture gradient prediction and its application in oilfield operations: SPE Higgins, S., Goodwin, S., Donald, A., Bratton, T., and Tracy, G., 2008, Anisotropic stress models improve completion design in the Baxter Shale: SPE Matthews, W. R., and Kelly, J. 1967, How to predict formation pressure and fracture gradient: Oil and Gas Journal, Mavko, G., Mukerji, T., and Dvorkin, J. 2003, The Rock Physics Handbook: Cambridge University Press. Norris, A. N., and Sinha, B. K., 1993, Weak elastic anisotropy and the tube wave: Geophysics, 58, No. 8, Nye, J.F. 1985, Physical properties of crystals: Oxford University Press. Pistre, V., Plona, T., Sinha, B., Kinoshita, T., Tashiro, H., Ikegami, T., Pabon, J., Zeroug, S., Shenoy, R., Habashy, T., Sugiyama, H., Saito, A., Chang, C., Johnson, D., Valero, H.P., Hsu, C.J., Bose, S., Hori, H., Wang, C., Endo, T., Yamamoto, H., Schilling, K., 2005, A new modular sonic tool provides complete acoustic formation characterization: SEG 2005 International Exposition and Annual Meeting. response using sonic dispersion curves, SEG 2004 International Exposition and Annual Meeting. Sayers, C., 2005, Seismic anisotropy of shales: Geophysical Prospecting, 53: Sinha, B. K., Vissapragada, B., Kisra, S., Sunaga, S., Yamamoto, H., Endo, T., and Valero, H.P., 2005, Optimal well completions using radial profiling of formation shear slownesses: SPE Sinha, B. K., Vissapragada, B., Renlie, L., and Skomedal, E., 2006, Horizontal stress magnitude estimation using the three shear moduli A Norwegian Sea Case Study: SPE The Norwegian Petroleum Sector Facts, 2009, Stavanger, Norway: Norwegian Petroleum Directorate. Thiercelin, M. J., and Plumb, R., A., 1994, Core-based prediction of lithologic stress contrasts in East Texas formations: SPE Formation Evaluation, Dec 1994, Thomsen, L., 1986, Weak elastic anisotropy: Geophysics, 51, Valero, H. P., Ikegami, T., Sinha, B., Bose, S., and Plona, T., 2009, Sonic dispersion curves identify TIV anisotropy in vertical wells: SEG Houston 2009 International Exposition and Annual Meeting. Walsh, J., Sinha, B., and Donald, A., 2006, Formation anisotropy parameters using borehole sonic data: SPWLA 47 th Annual Logging Symp., June 4-7. White, J.E., 1983, Underground sound: Application of seismic waves: Elsevier, New York. Plona, T. J., Kane, M. R., Sinha, B. K., and Walsh, J., 2000, Using acoustic anisotropy: SPWLA 41 st Annual Logging Symp., June 4 7. Plona, T., Sinha, B., Kane, M., Bose, S., Wang, C, Pabon, J., and Zeroug, S., 2004, Identifying formation 9

10 SPWLA 52nd Annual Logging Symposium, May 14-18, 2011 ABOUT THE AUTHORS Kristen Kozlowski is a Senior Petrophysicist for Schlumberger Data & Consulting Services (DCS). Her current area of focus in the North Sea is acoustics interpretation and petrophysics. Kristen has 7 years of experience with Schlumberger; she joined the company in 2004 as a wireline field engineer working throughout the Rocky Mountains in the United States. In 2006, she joined DCS in Denver, Colorado, USA, where she worked in the geomechanics domain, focusing on acoustics and applications to stress modeling and completions. She received her bachelor s degree in Materials Science and Engineering from the University of Michigan, Ann Arbor. Mehmet Fidan is a Formation Evaluation Specialist for ConocoPhillips in Norway. Mehmet has 30+ years of experience in the oil field, including 7 years as logging engineer with Schlumberger Wireline Services. After joining Phillips Petroleum (now ConocoPhillips) in 1986, Mehmet had various technical and management positions related to operation support, formation evaluation and production optimization. Mehmet received his bachelor s degree in Mechanical Engineering from the Middle East Technical University, Ankara and master s degree from The City University, London. Adam Donald is a Principal Geomechanics & Acoustics Engineer and is also the geomechanics team leader for the North Sea. Adam has 12 years of experience with Schlumberger; he joined the company in 1998 as a field engineer working on both land and offshore Canada projects. In 2004 he moved to Denver, Colorado, USA where he focused on tight gas evaluation in acoustics and petrophysics and applications to stress modeling and completion optimization. His focus in the North Sea is wellbore stability, rock mechanics testing and completion optimization. He received his bachelor s degree in Geological Engineering from University of Waterloo in Ontario, Canada and a master s degree in Mining Engineering from Dalhousie University in Nova Scotia, Canada. Adam holds two patents in areas of borehole acoustics and geomechanics. He is a registered Professional Engineer in the Province of Alberta, Canada and an active publishing member of SPWLA, SPE, and SEG. in 2006 working as a field engineer on drilling and measurement projects offshore in the North Sea. Peter received his bachelor s degree in Geoscience from the University of St. Andrews, Scotland, before spending a year working for a mud logging company. Peter received his master s degree in Petroleum Geoscience in His focus in the North Sea is wellbore stability, real-time drilling geomechanics, and sonic applications to geomechanics. Hardy Nielsen is a Geoscience Fellow for ConocoPhillips Norway, working in the Ekofisk area overburden characterization teams. Hardy has 29 years industry experience, 6 years from GECO A/S, 6 years from Mobil Exploration Norway and 17 years from ConocoPhillips Norway. He has worked on seismic processing, interpretation, exploration, production geophysics and has possessed team lead and director positions as well as been Chief Geophysicist in ConocoPhillips Norway for 5 years. His current focus is on overburden mechanical characterization and 4D seismic monitoring of the cuttings re-injection in the Ekofisk area. Hardy received a Cand. Scient degree in Geophysics from Aarhus University in Denmark and is a member of SEG and EAEG. Neil Anderson is a Petrophysicist for ConocoPhillips in Norway. He has 20 years of experience in Norway, 15 of which he spent in Stavanger. Prior to his career with ConocoPhillips, Neil worked as a field engineer and petrophysicist for Schlumberger and as a petrophysicist for Norsk Hydro. He received his degree in Engineering from the University of Saskatchewan. Jeroen Jocker is a Senior Petrophysicist working for Schlumberger Data and Consulting Services in The Hague, The Netherlands, from where he supports projects involving borehole acoustics in anisotropic media. Jeroen joined Schlumberger in 2006 as a research scientist specializing in borehole sonic and geomechanics, first working in Ridgefield, CT and later in Cambridge, MA. Jeroen has a master degree in Petroleum Engineering and a PhD in poro-elastic wave propagation, both from Delft UT, The Netherlands. Peter Shotton is a Geomechanics Engineer with the Schlumberger Data & Consulting Services (DCS) geomechanics team in Stavanger. Peter has 5 years of experience with Schlumberger; he joined the company 10