1887
ASEG2004 - 17th Geophysical Conference
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

Compressional (P) and shear (S) waves respond differently to the Earth’s geology. Hence an integrated interpretation of multi-component seismic data should provide greater information about the sub-surface than is available from P-wave data alone. Conventional multi-component seismic analysis uses scalar component selection to provide P- and S-wave images. This approach has proven successful in many situations. However, where P energy contaminates the horizontal components, and S energy contaminates the vertical component, there is potential to achieve purer P- and S-wave records by more fully exploiting the true vector nature of multi-component seismic data.

One elegant vector-processing technique, here referred to as elastic wavefield decomposition (EWD), takes advantage of the P- and S-wave separation properties of the divergence and curl operators. Practical implementation of EWD requires information about the seismic wavefield at depth. This is achieved via downward continuation of the elastic data in the time domain via a finite-difference approach.

Synthetic and real onshore multi-component seismic data are used to evaluate the practical viability of EWD for real-data applications. The robustness of the wavefield separation is dependent on the accuracy and smoothness of the velocity model used during the downward continuation stage of the algorithm. Velocity errors of up to 10% can be tolerated, after which significant artefacts appear in the separated records. A smooth velocity model will avoid contamination by spurious reflection events. P/S separation is still effective where a constant velocity model is used for data suffering from statics associated with lateral inhomogeneities in the near surface. Moderate noise contamination does not seem to significantly impact on the wavefield separation results. In fact, the downward continuation process appears to suppress random noise. Application of EWD to a real two-component record appears to enhance the relative strength and coherency of the P- and S-wave reflection events in the extracted P and S records.

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2004-12-01
2026-01-16

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  • Article Type: Research Article
Keyword(s): Elastic wavefield decomposition; multi-component; P- and S-wave separation; vector processing

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