GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 82-2
Presentation Time: 8:20 AM


FROTHINGHAM, Michael G., Geological Sciences, University of Colorado, Boulder, Boulder, CO 80309, MAHAN, Kevin H., Department of Geological Sciences, University of Colorado Boulder, 2200 Colorado Avenue, UCB 399, Boulder, CO 80309-0399, SCHULTE-PELKUM, Vera, Geological Sciences and CIRES, University of Colorado-Boulder, 2200 Colorado Ave, Boulder, CO 80309 and CAINE, Jonathan S., U.S. Geological Survey, Box 25046, DFC, MS 980, Denver, CO 80225

Recent advances in passive seismic data acquisition (EarthScope) and seismic anisotropy processing techniques (receiver functions) provide powerful new resources for measuring rock properties and interpreting the structure of continental crust at depth. However, seismic data have commonly been interpreted to represent mantle fabrics or regional stress fields without testing links to surface geology. Our study quantitatively compares crustal seismic anisotropy inferred from receiver functions from USArray and CREST seismic station data to predicted seismic anisotropy based on Colorado Rocky Mountain basement structures and crystal-scale mineral properties therein. We predict crustal seismic anisotropy through the following methods: 1) compilation of published digital geologic maps and associated structural data, 2) homogenization of geologic data into a pixelated map displaying lithology, strike, and dip of foliation, 3) assignment of a representative elastic tensor from a database to each pixel, 4) structural rotation of each tensor, and 5) calculation of average seismic properties over the entire map. Finally, the orientation, symmetry, and amplitude of predicted seismic anisotropy derived from surface geology is quantitatively correlated to depth-dependent seismic anisotropy interpreted from receiver functions. Although the methodology is still being developed, preliminary results of predicted seismic anisotropy demonstrate 1) unequal weight of certain lithologies on seismic anisotropy signals, 2) positive correlation between predicted versus observed seismic anisotropy in foliated and folded domains, and 3) overprinting signatures from regional ductile deformation fabrics, ductile shear zones, and brittle deformation fabrics. These approaches should improve our ability to interpret crustal geologic structures from seismic data and provide valuable new tools for unraveling the geologic history of continental assembly and deformation.