scholarly journals Cone penetrometer testing at the Hanford Site: Final performance evaluation report

1994 ◽  
Author(s):  
L.R. Richterich ◽  
B.R. Cassem
Keyword(s):  
Performance Evaluation ◽  
Cone Penetrometer ◽  
Hanford Site ◽  
Evaluation Report ◽  
Final Performance ◽  
Cone Penetrometer Testing

A Bayesian approach for determining velocity and uncertainty estimates from seismic cone penetrometer testing or vertical seismic profiling data

2011 ◽  
Vol 48 (7) ◽  
pp. 1061-1069
Author(s):  
Adam Pidlisecky ◽  
Seth S. Haines
Keyword(s):  
Travel Time ◽  
Model Uncertainty ◽  
Velocity Model ◽  
Cone Penetrometer ◽  
Uncertainty Estimates ◽  
Data Error ◽  
Cone Penetrometer Testing ◽  
Seismic Cone Penetrometer ◽  
Measurement Location ◽  
Ray Paths

Conventional processing methods for seismic cone penetrometer data present several shortcomings, most notably the absence of a robust velocity model uncertainty estimate. We propose a new seismic cone penetrometer testing (SCPT) data-processing approach that employs Bayesian methods to map measured data errors into quantitative estimates of model uncertainty. We first calculate travel-time differences for all permutations of seismic trace pairs. That is, we cross-correlate each trace at each measurement location with every trace at every other measurement location to determine travel-time differences that are not biased by the choice of any particular reference trace and to thoroughly characterize data error. We calculate a forward operator that accounts for the different ray paths for each measurement location, including refraction at layer boundaries. We then use a Bayesian inversion scheme to obtain the most likely slowness (the reciprocal of velocity) and a distribution of probable slowness values for each model layer. The result is a velocity model that is based on correct ray paths, with uncertainty bounds that are based on the data error.

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