Publications

Seismic signals contain a wide variety of singularities. Singularities in a medium are the primary source of coherent reflections because they exhibit a large or even diverging amplitude behavior for their derivatives. The presence of these singularities results in stochastic non-stationarity of the data, limiting the applicability of conventional techniques, which often rely on stationarity assumptions.We develop an attribute that can create singularity order (singularities sharpness) of seismic signals. Singularity order is created by extending the ordinary continuous wavelet transform (CWT) to a transform with the scale fixed and wavelet order varied fractionally (fractional differentiation/integra tion). This method is a generalization of Mallats modulus maxima approach which can predict singularity order as dis (appearance) of local maxima in wavelet transform coefficients.The output of this attribute produces a map of singularity structure. It can capture and categorize the main reflector features, without being sensitive to amplitudes. It can be a powerful interpretation tools that can help us to extract stratigraphic information directly from seismic signals.Keywords: singularity order attribute, continuous wavelet transform, stratigraphic interpretation.