ALGEBRAIC PROCESSING TECHNIQUES FOR ESTIMATING SHEAR-WAVE SPLITTING IN NEAR-OFFSET VSP DATA - THEORY

A vector convolutional model for multicomponent data acquired in an an isotropic earth is used as a basis for developing algebraic solutions to interpret near-offset VSP data. This interpretation of the cumulati ve or interval medium response (Green's tensor) for shear waves, deter mines a polarization azimuth for the leading shear wave and the time-d elay between the fast and slow split waves. The algebraic solutions ef fectively implement least-squares eigenanalysis or singular value deco mposition. Although the methodology for shear-wave analysis is strictl y relevant to a transmission response, it can be adapted to surface da ta for a uniform anisotropic overburden. The techniques perform well w hen calibrated and tested using synthetic seismograms from various ani sotropic models. Noise tests demonstrate the sensitivity of the interv al measurements to local interferences, particularly if the shear wave s are generated by one source. Although the algorithms are faster than numerical search routines, this is not seen as their major advantage. The solutions may have potential in near real-time interpretation of shear-wave data in well logging, where they may be coded on a microchi p to provide a direct stream of separated shear waves, or polarization and birefringenoe information. There may also be some benefit for lar ge prestack multicomponent surface data sets, where the solutions prov ide a direct transformation to the split-shear-wave components, reduci ng the storage space for further processing.