S41A-4449:
Illumination of Geology and Recent Tectonic History in Idaho and Oregon from Persistent Scattering Extracted from Ambient Noise

Thursday, 18 December 2014
Mark P Panning1, Raymond M Russo1, Paul M Bremner1, Sutatcha Hongsresawat2, Victor I Mocanu3, Adrian C Stanciu2, Megan E Torpey2 and John C VanDecar4, (1)Univ of FL-Geological Sciences, Gainesville, FL, United States, (2)University of Florida, Gainesville, FL, United States, (3)University of Bucharest, Dept. of Geophysics, Bucharest, Romania, (4)Nature Publishing Group, London, United Kingdom
Abstract:
In the last decade, ambient noise techniques have revolutionized the ability to image crustal structure by allowing calculation of empirical Green’s functions between stations through cross-correlation of noise records. Even with very long records, however, the resulting Green’s functions still have noise in the sense of energy that cannot be simply modeled as the impulse response of a virtual source at the location of one station recorded at the other. Thanks to the extremely high quality and densely-spaced deployment of broadband sensors by the IDaho-ORegion (IDOR) flexible array deployment from 2011-2013 in western Idaho and eastern Oregon, we have identified signals in ambient noise cross-correlograms consistent with cross-correlated energy from persistent seismic scatterers near or within the seismic array. By using cross-correlograms from all available pairs of the 86 broadband sensors of the IDOR array and the permanent stations within the footprint of the array, BMO and HLID, we employ a Kirchoff-like stacking technique to image likely locations for such persistent scattering, which we call scattering intensity. The resulting scattering intensity maps show the highest scattering intensity correlated with the distribution of feeder dikes for the Columbia River Basalts, while the lowest scattering intensity is correlated with relatively undeformed regions of the Idaho Batholith. Overall, patterns of scattering intensity are clearly related with the surface geology and tectonic history of the region. This technique represents a new tool for extracting yet more information from the apparent noise in the signals extracted from ambient noise.