Practical Evaluation of P- and S-Wave Separation Via Elastic Wavefield Decomposition

Abstract

The practical ability of elastic wavefield decomposition (EWD) to yield purer compressional (P) and shear (S) seismic images than conventional scalar component analysis of multi-component seismic data is examined. This vector-processing technique 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 seismic data using a time-domain, finite-difference approach. Synthetic data experiments demonstrate that the robustness of EWD 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 can still be 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 dataset from the Bowen Basin, Australia, appears to enhance the relative strength and coherency of the P- and S-wave reflection events in the extracted P and S records, respectively. Following application of EWD, the corresponding converted-wave stack exhibits better coherency and fault definition than the converted-wave stack produced from the raw horizontal-component data.