Structure Independent Seismic Velocity Estimation

Author : Chunyu Liu
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (134 download)

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Download or read book Understanding Seismic Velocity Structure and Its Time-varying Process Beneath the Mississippi Embayment Through Ambient Noise Analysis written by Chunyu Liu and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We apply ambient noise analysis to image shear wave velocity from near surface to uppermost mantle beneath the Mississippi embayment, and investigate the crustal response to climatological loadings. To further understand the generation mechanism of microseisms, we explore the azimuthal distribution of the signal-to-noise ratio and amplitude difference of crustal surface waves and estimate possible source locations in the ocean through back- projections.A shear wave velocity model with 0.5 0.5 resolution for the crust and uppermost mantle has been determined. We take advantage of the dense coverage and long-term deployments of 277 3-component broadband stations installed from 1990 to 2018 to image the shear wave velocity. Rayleigh group velocity dispersion curves extracted from ambient noise are inverted to obtain shear wave velocity at 5, 12, 24, and 43 km. We find that low velocity features characterize the Reelfoot Graben, Rough Creek Graben, Black Warrior basin, and southern Mississippi embayment in the upper 5 km of crust. High velocity features characterize the Ozark plateau, Ouachita mountains and Nashville dome. From 5 to 12 km, a low velocity anomaly is associated with the Missouri batholith. From 12 to 24 km, high velocity features characterize the Reelfoot-Rough Creek graben, and along the Appalachian-Ouachita thrust front. From 24 to 43 km, high velocity anomalies are commonly observed in the Mississippi embayment, and spatially correlated with the crustal thickness.Cross-correlation of the ambient seismic field is also used to estimate seasonal seismic velocity variations and to determine the underlying physical mechanisms. We process continuously recorded broadband data from 53 stations in 2014 to obtain daily and yearly cross- correlations and measure the Rayleigh wave phase velocity change over 4 frequency bands, 0.3-1, 0.5-1.2, 0.7-1.5, and 1-2 Hz. We then calculate the correlation coefficients between the velocity variations and the precipitation, water table fluctuation, temperature, atmospheric pressure and wind speed to find which external variable correlates most strongly with the observed changes. We observe high t/t (a proxy for velocity variation), the slowest velocity relative to annual average, from May to July and low t/t in September/October, and find the t/t variations correlate primarily with water table fluctuation. The correlation coefficients between water table fluctuation and t/t are independent of the interstation distance and frequency, but high coefficients are observed more often in the 0.3-1 Hz than 1-2 Hz band probably because high-frequency coherent signals attenuate faster than low-frequency ones. The t/t variations lag behind the water table fluctuation by about 20 days, which suggests the velocity changes can be attributed to the pore pressure diffusion effect. The maximum t/t variations decrease with frequency from 0.03% at 0.3-1 Hz to 0.02% at 1-2 Hz, and the differences between them might be related to different local sources or incident angles. The seasonal variations of t/t are azimuthally independent, and a large increase of noise amplitude only introduces a small increase to the t/t variation. The maximum t/t variations non-linearly decrease with the distance, which could be associated with the attenuation of coherent noise. At close distances, the maximum t/t holds a wide range of values, which is likely related to local structure. At larger distances, velocity variations sample a larger region so that it stabilizes to a more uniform value. We find that the observed changes in wave speed are in agreement with the prediction of a poroelastic model.The source distribution of ambient noise is of fundamental importance to understanding the generation mechanism of microseisms. Cross-correlations of ambient seismic noise from 277 broadband stations with at least 1-month recording between 1990 and 2018 are used to estimate source locations of primary and secondary microseisms inside the Mississippi embayment. We investigate source locations by analyzing the azimuthal distribution of the signal-to-noise ratio (SNR) and amplitude difference of crustal surface wave arrivals and by 2D F-K analysis. We also use 84 stations with continuous 1-year recording to explore seasonal variations of SNRs of the surface wave, which could be used to locate active sources in different seasons. We observe that (1) four azimuths could be identified in the azimuthal distribution of SNRs and reflect four different energy sources. Two energy sources are active in the Pacific and Atlantic ocean of northern hemisphere during winter and two relatively weak sources are active near Australia and South America in the southern hemisphere during summer. (2) Primary microseisms originate along the coastlines of southern Australia, Canada and Alaska, Newfoundland, and northeast South America. (3) Secondary microseisms could be generated in the deep water of northern and southern Pacific ocean, along coastlines of Canada and Alaska associated with reflections, and in the deep water of south of Greenland. (4) Azimuthal distribution of SNRs of sediment surface waves observed at 1-5s is negatively correlated with the geometry of the edge of the Mississippi embayment. The sediment surface waves could be induced by the basin-edge..