Quantifying the similarity of seismic polarizations

S U M M A R Y Assessing the similarities of seismic attributes can help identify tremor, low signal-to-noise (S/N) signals and converted or reflected phases, in addition to diagnosing site noise and sensor misalignment in arrays. Polarization analysis is a widely accepted method for studying the orientation and directional characteristics of seismic phases via computed attributes, but similarity is ordinarily discussed using qualitative comparisons with reference values or known seismic sources. Here we introduce a technique for quantitative polarization similarity that uses weighted histograms computed in short, overlapping time windows, drawing on methods adapted from the image processing and computer vision literature. Our method accounts for ambiguity in azimuth and incidence angle and variations in S/N ratio. Measuring polarization similarity allows easy identification of site noise and sensor misalignment and can help identify coherent noise and emergent or low S/N phase arrivals. Dissimilar azimuths during phase arrivals indicate misaligned horizontal components, dissimilar incidence angles during phase arrivals indicatemisaligned vertical components and dissimilar linear polarizationmay indicate a secondary noise source. Using records of the Mw = 8.3 Sea of Okhotsk earthquake, from Canadian National Seismic Network broad-band sensors in British Columbia and Yukon Territory, Canada, and a vertical borehole array at Hoadley gas field, central Alberta, Canada, we demonstrate that our method is robust to station spacing. Discrete wavelet analysis extends polarization similarity to the time–frequency domain in a straightforwardway. Time–frequency polarization similarities of borehole data suggest that a coherent noise source may have persisted above 8 Hz several months after peak resource extraction from a ‘flowback’ type hydraulic fracture.