Estimation of vertical stochastic scale parameters in the Earth's crystalline crust from seismic reflection data

Statistics – Computation

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

9

Exploration Geophysics: Computational Methods, Seismic, Exploration Geophysics: Data Processing, Exploration Geophysics: Seismic Methods (3025)

Scientific paper

Its been shown that the statistical properties of a reflected seismic wavefield can be related to the statistical properties of the crust. In this paper, we report on a method to invert a reflected seismic wavefield for vertical stochastic parameters. The method is founded on a deconvolution, thresholding, and numerical integration procedure to estimate the Earth's bi-modal velocity perturbation. We then fit a von Kármán autocorrelation function to the autocorrelation of the estimated velocity perturbation and record the von Kármán parameters which result in the minimum misfit. Tests show that our scheme is successful at recovering the vertical characteristic length in synthetic seismic reflection data.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Estimation of vertical stochastic scale parameters in the Earth's crystalline crust from seismic reflection data 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 Estimation of vertical stochastic scale parameters in the Earth's crystalline crust from seismic reflection data, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Estimation of vertical stochastic scale parameters in the Earth's crystalline crust from seismic reflection data will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-1010220

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.