Statistical selection of the 'best' seismic source mechanisms from inversions of synthetic volcanic long-period events

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Title: Statistical selection of the 'best' seismic source mechanisms from inversions of synthetic volcanic long-period events
Authors: O'Brien, G. S.
Lokmer, Ivan
Bean, Christopher J.
Permanent link: http://hdl.handle.net/10197/5441
Date: Sep-2010
Abstract: Inversions for the source mechanism of long‐period (LP) seismicity recorded on volcanoes have become increasingly common and are used to interpret fluid‐driven processes. The source mechanism considered for LP inversions usually consists of a symmetric moment tensor with and without single forces. Also, constrained inversions have been performed where one presumes a specific source geometry that reduces the degrees of freedom in the inversion. To select the correct solution from the different possible mechanisms, the Akaike information criterion (AIC) has been used. However, since AIC performs well only if the inverted model is close to the true model, we tested its ability to select the correct model in LP inversions. Using synthetic data sets generated on Mt. Etna, Italy, with a tomography velocity model and the Green’s functions calculated for a simplified, homogeneous velocity model, we have investigated (1) if any of the inversion source models can recover the true mechanism and (2) the ability of the Akaike and Bayesian information criteria (BIC) to select the correct model. Results show that in some cases it is possible to recover the mechanism but never the source magnitude and that the BIC is a better measure than the AIC in selecting the true source model, although in numerous cases both criteria fail to select the correct solution. Therefore, the BIC should be used as opposed to the AIC if it is necessary to select an appropriate source. Caution should be used when using the statistical measure in any seismic inversion application.
Type of material: Journal Article
Publisher: American Geophysical Union
Copyright (published version): 2011, American Geophysical Union
Keywords: Inverse theory;Modeling;Volcano seismology
DOI: 10.1029/2009JB006958
Language: en
Status of Item: Peer reviewed
Appears in Collections:Earth Sciences Research Collection

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