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

### Details

Serval ID

serval:BIB_AC2AC686CCC3

Type

**Article**: article from journal or magazin.

Collection

Publications

Fund

Title

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

Journal

Geophysical Journal International

ISSN-L

0956-540X

Publication state

Published

Issued date

2010

Peer-reviewed

Oui

Volume

183

Pages

1408 - 1428

Language

english

Notes

Scholer2010b

Abstract

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.

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.

Keywords

Inverse theory, Spatial analysis, Fractals and multifractals, Controlled, source seismology, Statistical seismology, Wave scattering and diffraction

Create date

25/11/2013 17:31

Last modification date

03/03/2018 19:27