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Reconstruction of surface waves using super virtual interferometry: an example from the Forsmark site, Sweden
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics. Jilin University.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.ORCID iD: 0000-0003-2776-0846
Jilin University, China.
Uppsala University, Disciplinary Domain of Science and Technology, Earth Sciences, Department of Earth Sciences, Geophysics.
2017 (English)In: Geophysical Journal International, ISSN 0956-540X, E-ISSN 1365-246X, Vol. 211, no 1, p. 120-140Article in journal (Refereed) Published
Abstract [en]

Seismic interferometry is a technique that enables the extraction of the seismic impulse response (Green's function) between two receivers. The retrieved response is generally dominated by surface waves when sources are located at or near the surface of the Earth. In onshore seismic exploration, dealing with complex near-surface conditions is one of the main challenges for seismic data processing. In some cases, seismic interferometry can be used for suppressing surface waves without the use of a priori near-surface velocity model. Aside from being an effective tool for surface wave attenuation, the reconstructed surface waves generated by seismic interferometry contain useful information about near-surface heterogeneities and can be used to characterize the near-surface velocity field. In this study, we apply super virtual interferometry (SVI) to a real onshore data set from the Forsmark site, central Sweden, with the primary aim of characterizing shallow-subsurface structure. This is accomplished by improving the dispersion characteristics of the surface waves. We also show that SVI performs better than conventional correlation-type and convolution-type interferometry when reconstructing surface waves, both in synthetic and real data. We use the dispersive behaviour of the reconstructed surface waves to infer the geological structure of the shallow subsurface.

Place, publisher, year, edition, pages
2017. Vol. 211, no 1, p. 120-140
National Category
Geophysics
Identifiers
URN: urn:nbn:se:uu:diva-337144DOI: 10.1093/gji/ggx290ISI: 000412270400009OAI: oai:DiVA.org:uu-337144DiVA, id: diva2:1168435
Available from: 2017-12-20 Created: 2017-12-20 Last updated: 2018-02-01Bibliographically approved

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Xu, ZhuoJuhlin, ChristopherZhang, Fengjiao

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