How reliable is statistical wavelet estimation?
Jonathan A. Edgar, Mirko van der Baan · 2009
Well logs are often used for the estimation of seismic wavelets. The phase is obtained by forcing a well-derived synthetic to match the seismic, thus assuming the well log provides ground truth. However, well logs are not always available and can predict different phase corrections at nearby locations. Thus, a wavelet estimation method that can reliably predict phase from the seismic alone is required. We test three statistical wavelet estimation techniques against the deterministic method of seismic-to-well ties. We explore how the choice of method influences the estimated wavelet phase, with the aim of finding a statistical method which consistently predicts a phase in agreement with well logs. The statistical method of kurtosis maximization by constant phase rotation was consistently able to extract a phase in agreement with seismic-to-well ties. Furthermore, the second method based on a modified mutual-information-rate criterion provided frequency-dependent phase wavelets where the deterministic method could not. Time-varying wavelets were also estimated — a challenge for deterministic approaches due to the short logging sequence. We conclude that statistical techniques can be employed as quality control tools for the deterministic methods, a way of interpolating phase between wells, or act as standalone tools in the absence of wells.