Importance of covariance components in inversion analyses of densely sampled observed data: an application to waveform data inversion for seismic source processes

Details Importance of covariance components in inversion analyses of densely sampled observed data: an application to waveform data inversion for seismic source processes Importance of covariance components in inversion analyses of densely sampled observed data: an application to waveform data inversion for seismic source processes

Oct 2008

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2008geoji.175..215y&link_type=abstract

Geophysical Journal International, Volume 175, Issue 6, pp. 215-221.

Astronomy and Astrophysics

Astronomy

4

Time Series Analysis, Inverse Theory, Earthquake Dynamics

Scientific paper

Nominally continuous data in space and/or time is obtained in various observations in geophysics. Due to an enhanced technology of computers, we can now invert such observed data with a very high sampling rate. Densely sampled observed data are usually not completely independent of each other, and so we must take this effect into account. As for seismic waveform data, they have at least temporal correlation due to the effect of inelastic attenuation of the Earth. Taking the data covariance into account, we have developed a method of seismic source inversion and applied it to teleseismic P-wave data of the 2003 Boumerdes-Zemmouri, Algeria earthquake. From the comparison of the final slip distributions inverted with and without the covariance components, we found that the effect of covariance components is crucial for a data set of higher sampling rates (>=5 Hz). If we neglect the covariance components, the inverted results become unstable due to overestimation of the information from observed data. So far, it has been widely believed that we can obtain a finer image of seismic source processes, by inverting waveform data with a higher sampling rate. However, the covariance components of observed data originated from inelastic effect of the Earth give a limitation on the resolution of inverted seismic source models.

Affiliated with

Also associated with

No associations

Rating

Importance of covariance components in inversion analyses of densely sampled observed data: an application to waveform data inversion for seismic source processes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Importance of covariance components in inversion analyses of densely sampled observed data: an application to waveform data inversion for seismic source processes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Importance of covariance components in inversion analyses of densely sampled observed data: an application to waveform data inversion for seismic source processes will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1701205