Radial variations in cross‐dipole shear slownesses in a limestone reservoir

SPE Reservoir Evaluation &Amp; Engineering

Bratton

Cryer

et al. 2008

Highly depleted reservoirs exhibit sharply lower pore pressures and horizontal stress magnitudes than does the overlying shaly formation. Drilling through such depleted reservoirs can cause severe fluid loss and drilling-induced wellbore instability. Accurate and reliable estimates of horizontal stresses can provide an early warning of impending drilling problems that may be mitigated by appropriate drilling fluid design and drilling practices. We have developed a new multifrequency inversion algorithm for the estimation of maximum and minimum horizontal stress magnitudes using cross-dipole dispersions. Borehole sonic data for the case study presented in this paper was acquired by a cross-dipole sonic tool in a deepwater well, offshore Louisiana in the Gulf of Mexico (GOM). The logged interval spans 1,000 ft below the casing shoe. In addition, the Modular Dynamic Tester (MDT) (©Schlumberger) minifrac tests were performed at three depths in shale, thus yielding two minimum horizontal stress magnitudes. The borehole sonic data were suitable for the inversion of crossdipole dispersions at three depths in shale, as well as at a depth in a highly depleted sand reservoir. There was one depth in shale above the depleted sand where we could estimate the minimum horizontal stress magnitude with both the MDT minifrac tests and inversion of borehole sonic data. The results of the two techniques are consistent, providing encouragement for further validation of the multifrequency inversion of cross-dipole dispersions to estimate horizontal stresses. Even though the overburden stress is expected to increase with depth, both the maximum (S Hmax ) and minimum (S hmin ) horizontal stresses obtained from the inversion of borehole sonic data are significantly smaller in the depleted sand than in the overburden shale. However, both the horizontal stress magnitudes increase again in the shale below the depleted sand. Such rapid variations in horizontal stress magnitudes cause large fluctuations in the safe mud-weight window. This challenge in drilling through the depleted sand was successfully handled by using special drilling fluid to mitigate seepage losses and the differential sticking in the depleted sand and overlying shale. We have also performed dipole radial profiling (DRP) of formation shear slownesses using the measured cross-dipole dispersions at three depths in shale and one in highly depleted sand. Analysis of radial profiles in the two orthogonal directions indicates plastic yielding or stiffening of rock in the near-wellbore region. While plastic yielding increases the shear slowness, stiffening would reduce the shear slowness.

Section: Formation Stresses From Sonic Datamentioning

confidence: 99%

Section: Appendixmentioning

confidence: 99%

Estimation of Near-Wellbore Alteration and Formation Stress Parameters From Borehole Sonic Data

SPE Reservoir Evaluation &Amp; Engineering

Bratton

Cryer

et al. 2008

“…With the recent introduction of algorithms for the Stoneley radial profiling of horizontal shear slowness and dipole radial profiling of vertical shear slowness, we can unambiguously estimate the virgin formation shear moduli C 44 , C 55 , and C 66 . These algorithms account for the sonic tool bias and possible near-wellbore alteration effects on the measured sonic data 17,18 .…”

Section: Formation Stresses Using the Three Shear Modulimentioning

confidence: 99%

Horizontal Stress Magnitude Estimation Using the Three Shear Moduli - A Norwegian Sea Case Study

Proceedings of SPE Annual Technical Conference and Exhibition

Vissapragada

Renlie

et al. 2006

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractFormation stresses play an important role in geophysical prospecting and development of oil and gas reservoirs. A reliable in-situ stress determination is a premise for all geomechanical evaluations of a reservoir including initial drilling, infill drilling, sand prediction, stimulation and fracturing, well integrity evaluation, coupling with reservoir flow analyses, fault reactivation and environmental aspects particularly related to injection. The underlying theory behind the estimation of formation stresses using borehole sonic data is based on acoustoelastic effects in rocks. Acoustoelasticity in rocks refers to changes in elastic wave velocities caused by changes in pre-stress in the propagating medium. Elastic wave propagation in a pre-stressed material is described by equations of motion for small dynamic fields superposed on a statically deformed state of the material. These equations are derived from the rotationally invariant equations of nonlinear elasticity. However, shear wave propagation in a triaxially stressed rock can also be expressed in terms of the stressdependent shear moduli. A new Stress Magnitude Estimation (SME) algorithm yields the maximum horizontal stress magnitude using the three shear moduli outside the nearwellbore altered annulus together with the Mechanical Earth Model that provides the overburden stress, pore pressure, and minimum horizontal stress as a function of depth. The maximum and minimum horizontal stresses can also be obtained from a multi-frequency inversion of cross-dipole dispersions in the presence of stress-induced crossovers. Inversion results for the stress magnitudes are obtained together with the stress coefficients of velocities in terms of the formation nonlinear constants referred to a local reference state. Formation stress magnitudes together with stress coefficients of velocities help in distinguishing radial alteration of shear slownesses caused by near-wellbore stress concentrations from those resulting from plastic yielding of rock. The methodology used in the two Norwegian Sea wells, operated by Statoil, successfully estimated the horizontal stress magnitudes. Results for the minimum horizontal stress corroborate well with the stress magnitude estimated from extended leak-off test in one of the wells.

“…In practice a formation is called slow if the shear slowness of the formation is larger than the mud slowness whereas in the opposite case, the formation is said to be fast. In addition to its use in the wave propagation in a borehole, mud slowness is also a key parameter in the processing of sonic waveforms [2] or get proper results from profiling techniques [3], [4].…”

Section: Introductionmentioning

confidence: 99%

Probabilistic mud slowness estimation from sonic array data

Valero

Djikpesse

2008 IEEE Ultrasonics Symposium

2008

There are various ways to get an estimate of the mud slowness. The most common one consists in performing acoustic measurement at the surface using mud sample or using empirical laws linking mud slowness as a function of mud density and type. In this case, the estimation of mud slowness is said to be indirect as the estimated mud value is not the one measured in the well at the time the tool recorded the data. The second approach consists in analyzing dispersive modes contained in recorded data and from this study deriving an estimate of the mud slowness. The drawback of this non automatic method is that it relies heavily on the skill of the person that will analyze the dispersion plots. Therefore, there is a need for a general framework capable to provide reliable and accurate mud slowness estimation with minimum supervision. In order to overcome this need a probabilistic approach combining the high frequency monopole data and the output from the monopole radial profiling to get an estimate of the mud slowness has been developed. Robustness and efficiency of this algorithm will be illustrated on real field data.