Use of Ambient Noise Greens Functions in Explosion Moment Tensor Estimation (ANMT)
Abstract
We examine the use of ambient Noise Correlation Tensors (NCT) in seismic moment tensor inversion. We develop and test a new method, the Inversion of the Virtual Earthquake Approach (iVEA) based on the work published by Prieto and Beroza (2008) and Denolle et al. (2013), which introduced the forward problem, called the Virtual Earthquake Approach (VEA), in which complex wave propagation is captured in the NCT between seismometers using an ambient noise interferometry methodology, and then leveraged for use in ground motion estimation. The geometry is constrained by the common receiver in all NCTs (a virtual source) being located at the epicenter of the earthquake of interest. Further, VEA relies on spatial derivatives of surface wave eigen functions to convert the resulting set of unit-force surface-surface NCTs to a set of nine approximate dislocation source Greens Functions appropriate for modeling earthquakes and explosions, which we call the Greens Tensor (GT).We numerically investigate the terms used in this conversion (i.e., VEA), evaluate how the error in the conversion propagates into moment tensor solution uncertainty, assuming that the NCT perfectly retrieves the GT. Solutions obtained using iVEA and their uncertainties are evaluated in the context of the sourcetype discrimination application and then tested on real data. We find that while it is possible to use NCT to estimate seismic moment tensors, there are significant potential biases, and large uncertainties due to the approximate nature of the empirical NCT based Greens tensors. However, this approach does show some promise for using the ambient noise methodology to find Greens functions for complex wave propagation paths, which may allow data from those paths to be incorporated into a seismic moment tensor inversion in part.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 02, 2018
- Accession Number
- AD1067382
Entities
People
- Douglas S. Dreger
- Nathaniel J. Lindsey
- Sean Ford
Organizations
- University of California, Berkeley