ESTIMATION OF FORMATION STRESSES USING BOREHOLE SONIC DATA (original) (raw)
Formation stresses play an important role in geophysical prospecting and development of oil and gas reservoirs. Both the direction and magnitude of these stresses are required in (a) planning for borehole stability, (b) hydraulic fracturing for enhanced production, and (c) selective perforation for sand control. The formation stress state is characterized by the magnitude and direction of the three principal stresses. Generally, the overburden stress is obtained by integrating the formation density from surface to the depth of interest. The minimum horizontal stress (Sh) can be estimated from a minifrac, closure pressure in an extended leak-off test, or from analysis of mud losses. However, estimating the maximum horizontal stress (SH) magnitude remains a challenge in the industry. The underlying theory behind the estimation of formation stresses using borehole sonic data is based on acoustoelastic effects in rocks. Acoustoelasticity refers to changes in elastic wave velocities caused by changes in the prestress in the propagating medium. A new Stress Magnitude Estimation algorithm yields SH magnitude using the three shear moduli outside the near-wellbore altered annulus together with the Mechanical Earth Model (MEM) that provides the overburden stress, pore pressure, and Sh as a function of depth. Cross-dipole shear moduli are measured in the two orthogonal sagittal planes containing the borehole axis. The third shear modulus in the borehole cross-sectional plane is estimated from Stoneley data. Since Stoneley data is significantly affected by tool effects and near-wellbore alterations, we estimate the far-field shear modulus in the borehole cross-sectional plane using the Stoneley shear velocity radial profiling algorithm. When the horizontal stresses are nearly the same (SH = Sh), there is no shear wave splitting and cross-dipole shear slownesses are nearly equal. Under these circumstances, a Velocity Dispersion Gradient (VDG) algorithm can be used in a depth interval with a reasonably uniform lithology and where the volumetric distribution of clay and other minerals are nearly constant. The VDG algorithm inverts differences between dipole dispersions at two depths in the same lithology interval for estimating horizontal stress gradient within the chosen depth interval. It is assumed that observed differences in dipole dispersions are essentially caused by differences in the overburden and horizontal stresses at the two depths. We discuss results of using the two algorithms described above on waveforms acquired by a sonic tool recorded in a few wells. The MEM is built using drilling reports, mud reports, petrophysical logs as well as wellbore images.
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