Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Details Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Dec 2010

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2010geoji.183.1408s&link_type=abstract

Geophysical Journal International, Volume 183, Issue 3, pp. 1408-1428.

Astronomy and Astrophysics

Astronomy

1

Inverse Theory, Spatial Analysis, Fractals And Multifractals, Controlled Source Seismology, Statistical Seismology, Wave Scattering And Diffraction

Scientific paper

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

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