Adaptive wavelet for the detection of surface waves to predict marine sediments properties

A. Kritski, A. P. Vincent, David A Yuen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Our goal is to predict dynamic (shear velocity, attenuation) and physical properties (stiffness, density) of marine sediments from seismoacoustic records of surface waves propagating along the water-seabed interface. To estimate and invert propagational parameters of surface waves (group and phase velocity) into shear velocity as a function of distance and depth we use the wavelet cross-correlation technique [7]. In order to achieve a better resolution of imaging we developed a new data driven adaptive wavelet. Our approach is based on the Karhunen-Loeve decomposition (KL) of the data records. Obtained set of wavelets is naturally adapted to the surface wave modes propagation in terms of scales values: time and periods (frequencies). We show that the developed adaptive wavelet discriminates better between different surface wave modes than it can be achieved by using standard wavelets kernels.

Original languageEnglish (US)
Title of host publication67th European Association of Geoscientists and Engineers, EAGE Conference and Exhibition, incorporating SPE EUROPEC 2005 - Extended Abstracts
PublisherSociety of Petroleum Engineers
Pages1599-1602
Number of pages4
Volume67th European Association of Geoscientists and Engineers Conference and Exhibition 2005: The Challenge of Discovery. Incorpor...
ISBN (Print)9073781981, 9789073781986
StatePublished - Jan 1 2005
Event67th European Association of Geoscientists and Engineers, EAGE Conference and Exhibition, incorporating SPE EUROPEC 2005 - Extended Abstracts - Feria de Madrid, Spain
Duration: Jun 13 2005Jun 16 2005

Other

Other67th European Association of Geoscientists and Engineers, EAGE Conference and Exhibition, incorporating SPE EUROPEC 2005 - Extended Abstracts
CountrySpain
CityFeria de Madrid
Period6/13/056/16/05

Fingerprint Dive into the research topics of 'Adaptive wavelet for the detection of surface waves to predict marine sediments properties'. Together they form a unique fingerprint.

Cite this