Sonic data are now acquired in most wellbores for a variety of applications including seismic tie, porosity evaluation, lithology determination, fracture detection, gas detection, and geomechanics modeling. The industry is also more aware of the impacts of intrinsic (fractures, layering), extrinsic (stress), and borehole effects that may affect the basic measurements of compressional and shear slownesses. Any advanced interpretation of sonic data has historically been done days to weeks after the acquisition, and the value of the measurement can be diminished due to the time of delivery of the final product.
An updated data-driven inversion algorithm applied while logging can provide robust shear and compressional slownesses with associated quality control indicators. The updated algorithm has fewer user parameters and is more reliable in layered, stressed, or damaged formations. Processing quality is determined using the coherency of the measured signal and an industry-standard rock physics model for theoretical validation. With the updated dipole shear inversion and more flexible dipole anisotropy frequency filters, the dipole shear anisotropy processing can deliver reliable results at the wellsite.
A byproduct of the new dipole shear inversion algorithm is the environmental slowness that is used to optimally fit the dipole dispersion signal. The interpretation of the environmental slowness parameter can indicate the anisotropy mechanism in addition to zones of near-wellbore alteration to provide further insight immediately.
The wellsite dipole shear inversion and anisotropy processing were run on a vertical well in eastern Australia, within a stacked tight gas sand reservoir that requires hydraulic fracturing. The main application of the sonic data was reliable slownesses as input to stress modeling for designing the stimulation, but the direction of the maximum horizontal stresses within the clastic gas-filled zones was also required. The dipole shear inversion results were able to handle various lithologies and hole conditions, as well as identify vertical transverse isotropy (VTI) anisotropic shale intervals between the horizontally stressed sand zones.