Spectral decomposition is useful for analyzing seismic data, however commonly used techniques such as the Continuous Wavelet Transform (CWT) and the S transform (ST) may not have sufficient resolution for certain stratigraphic or seismic interpretation purposes. In this study we present a new coherency based method, Coherency Weighted Spectral Decomposition (CWSD), for improving the resolution of spectrally decomposed seismic data. The algorithm involves extracting high-resolution coherency information from all traces of the original seismic data using the parabolic radon transform (in the frequency domain) and applying it in a spectral decomposition scheme. The spectral decomposition scheme is defined as the convolution of the time series with a weighted Ricker wavelet in the time domain. The coherency weights ensure that coherent signals have better resolution in the temporal domain. The method shows better temporal resolution than the S transform. We demonstrate the efficacy of the method on both synthetic and real seismic data and show that at high frequencies the CWSD method can be used for sequence stratigraphic interpretation of seismic data.
Presentation Date: Tuesday, October 16, 2018
Start Time: 8:30:00 AM
Location: 210A (Anaheim Convention Center)
Presentation Type: Oral
