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Improving the resolution of shallow seismic sections using eigenimage analysis
Author(s) -
Shtivelman Vladimir
Publication year - 2003
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2003005
Subject(s) - geology , seismology , coherence (philosophical gambling strategy) , image resolution , economic geology , resolution (logic) , scale (ratio) , geophysical imaging , regional geology , environmental geology , seismic to simulation , geophysics , remote sensing , seismic inversion , telmatology , tectonics , optics , computer science , physics , quantum mechanics , artificial intelligence , azimuth
The basic limitation of geophysical techniques used for imaging various shallow localized subsurface inhomogeneities is their spatial resolution, that is, the ability of the methods to detect small‐scale objects. This is especially true for low‐resolution techniques, such as recently developed methods using seismic surface waves. The objective of this work is to improve the spatial resolution and to enhance the detectability of small‐scale objects on seismic sections. For this purpose, a method of eigenimage analysis, based on singular value decomposition of seismic sections, was used. The method effectively separates events with different horizontal coherence. Since shallow subsurface inhomogeneities are characterized by poor horizontal coherence on seismic sections, such a separation can serve as a tool for detecting the inhomogeneous areas in the subsurface. Application of the method to synthetic and real seismic data shows that it can significantly improve the spatial resolution of the subsurface imaging.