SCEC Award Number 17227 View PDF
Proposal Category Individual Proposal (Integration and Theory)
Proposal Title ESTIMATING UNCERTAINTY VALUES FOR QUANTITIES DERIVED FROM 9-COMPONENT STACKED CROSS-CORRELATION OF AMBIENT SEISMIC NOISE
Investigator(s)
Name Organization
Gregory Beroza Stanford University Xin Liu Stanford University
Other Participants
SCEC Priorities 4c, 4b SCEC Groups GM, Seismology
Report Due Date 06/15/2018 Date Report Submitted 11/14/2018
Project Abstract
The Virtual Earthquake Approach (VEA) has been successfully applied to Ground-motion prediction. The VEA method relies on seismic noise interferometry, which adds a component of random variability in ground-motion prediction in this approach. We develop a theoretical framework to predict this uncertainty for time domain noise-correlation assuming a diffuse noise wavefield and validate the theory predictions from a bootstrap approach. Based on observations from all station pairs of 154 stations in Southern California, we find significant discrepancy between the bootstrap and theory-predicted uncertainties. Our statistical analysis of the misfit involves separate analysis for ballistic and coda windows applied to all station pairs. The results show strong correlation between the localized source and the azimuth range of high misfit values between different metrics of uncertainty for the ballistic wave, and decreasing misfit value with increasing distance. Our study provides insight for future applications of the VEA method and for assessing the ground motion prediction variability for this approach.
Intellectual Merit Ground-motion prediction based on ambient seismic field measurements is an alternative approach to the traditional method using Ground Motion Prediction Equations (GMPEs). The reliability of the amplitude information extracted from ambient seismic noise interferometry is important for such applications. The focus of this work is on quantifying the uncertainty and bias in ambient-field cross-correlations.
Broader Impacts This work supported postdoctoral associate Xin Liu, who is working on various theoretical aspects of ambient field cross correlation.
Exemplary Figure Figure 2. a) Discrepancy between the bootstrap and theory-predicted uncertainties of stacked cross-correlation envelope for CHF-IPT (top) with ballistic signal (blue) and coda noise (yellow) windows. The stacked cross-correlation and its envelope for CHF-IPT (bottom). b) Beamforming result of the noise data between days 100-110 of year 2014. c & d) For virtual source OLI, the maps of misfit between bootstrap and theory-predicted uncertainties for signal and noise windows, respectively, with the same color scale. e & f) For virtual source CHF, the maps of misfit between bootstrap and theory-predicted uncertainties for signal and noise windows, respectively, with the same color scale.