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Spatio-autocorrelation 
Training

Please join the University of Utah, in collaboration with the University of New Mexico, the University of Puerto Rico Mayaguez, and the University of Texas at El Paso for a virtual multi-day interactive collaborative spatio-autocorrelation (SPAC) training run by Dr. Surya Pachhai, Research Assistant Professor, of the University of Utah department of Geology & Geophysics. Dr. Pachhai will lead this hands-on training of the spatio-autocorrelation (SPAC) technique.  

Students

General introduction of Spatial Autocorrelation (SPAC) data and its usage to image the subsurface structure

Acquisition and processing of ambient noise data for SPAC

Geophysical inversion and imaging subsurface structure using hierarchical trans-dimensional Bayesian inversion

Real application of hierarchical trans-dimensional Bayesian inversion of SPAC data

ABOUT THE TRAINING

What will I learn?

Students will learn how to use noise recorded by geophones to image the subsurface structure. The inversion approach they learn can be applied to solve other geophysical problems as well. Additionally, the subsurface structure can be used to estimate an average shear (S)-wave velocity to a depth of 30 m (i.e., Vs30) to characterize the site response in designing earthquake resistant buildings.

What will I need to participate?

A computer, internet connection, and preferably data you can work on.

How can I prepare for this training?

Please download the codes and sample data from Dr. Surya Pachhai’s github repository. There are also many references in the handbook included in this git repository. In order to download, these files, you will need to open a terminal then type git clone https://gitfront.io/r/user-3200264/x1pecp9T5TKV/Bayesian-Inversion-of-SPAC-gitfront.git

To better understand SPAC, we recommend the following papers:

Aki K. , 1957. Space and time spectra of stationary stochastic waves with special reference to microtremors, Bull. Earthq. Res. Inst., 35, 415–456.

Hao Zhang, Kristine Pankow, William Stephenson, A Bayesian Monte Carlo inversion of spatial auto-correlation (SPAC) for near-surface Vs structure applied to both broad-band and geophone data, Geophysical Journal International, Volume 217, Issue 3, June 2019, Pages 2056–2070, https://doi.org/10.1093/gji/ggz136

Stephenson, W. J.,  Hartzell, S.,  Frankel, A. D.,  Asten, M.,  Carver, D. L., and  Kim, W. Y. (2009), Site characterization for urban seismic hazards in lower Manhattan, New York City, from microtremor array analysis, Geophys. Res. Lett.,  36, L03301, doi:10.1029/2008GL036444.

Is there any special knowledge or skills I should have for the training?

Any knowledge of coding in python/matlab would be helpful, (but not required?).

​Will different topics be covered each day?

 

YES!

Day 1: General introduction of Spatial Autocorrelation (SPAC) data and its usage to image the subsurface structure.

 

Day 2: Acquisition and processing of ambient noise data for SPAC.

Day 3: Geophysical inversion and imaging subsurface structure using hierarchical trans-dimensional Bayesian inversion.

 

Day 4: Real application of hierarchical trans-dimensional Bayesian inversion of SPAC data.

Can I still participate if I am unable to attend the live sessions?

Yes! All trainings will be recorded and posted to the C-CIES website!

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