Ultrasonic transmission is sensitive to the variation in mechanical
properties of materials. Wave propagation through fractured media
introduces changes in the frequency content, travel time and
transmission coefficient of the wave. A workflow based on physics-driven
unsupervised learning is developed to process the transmitted
ultrasonic-shear waveforms to non-invasively visualize the geomechanical
alterations due to hydraulic fracturing of a tight sandstone. Novelty of
the work involves the assignment of physically consistent clusters to
the measurements of shear waveforms across the axial and frontal planes
by incorporating the travel time of the peak of spectral energy and
transmission coefficient. The proposed workflow generates maps of
geomechanical alterations across the frontal and axial planes of the
sample. The outputs of the workflow are in good agreement with
independent techniques viz. acoustic emission and X-ray computed
tomography. The proposed workflow can be adapted for improved fracture
characterization in the subsurface when processing sonic-logging,
cross-wellbore seismic or surface seismic waveform data.