Gulf of Mexico shelf framework interpretation using a bed-form attribute from spectral imaging

Abstract

This article introduces a new attribute called SPICE (spectral imaging of correlative events) that calculates a bed-form boundary framework from the seismic data, and highlights detail from subtle changes in the seismic wavelet. The concept of spectral imaging is presented in the context of a well-log model and its relationship to impedance layering. Further validation of the method is provided by a detailed sequence stratigraphy analysis using well logs and seismic data from the northern Gulf of Mexico. The technique, based on wavelet transform decomposition and singularity analysis of migrated seismic data, uses the localization properties of the wavelet transform in time and frequency to produce a unique display that provides a boundary framework of the subsurface that is rich in structural and stratigraphic detail. This advances seismic interpretation closer to the goal of producing accurate geologic mapping of the subsurface. Additionally, this attribute offers a straightforward way to interpret a seismic section similar to a geologist in the field who maps beds and faults directly from the outcrop. Most seismic interpretation today is performed on variable area displays of the seismic amplitude of a wavelet that changes with depth. This has historically posed a number of significant problems for the interpreter. Reflections in seismic data are blurred representations of the actual stratigraphy. The interference of a changing pulse shape with a wide variety of impedance contrasts in the subsurface adds a significant element of uncertainty to the final mapping of reservoir, seal, and trap. The richness and nonstationary character of the seismic trace require a process that localizes rapidly changing features in the spectrum. The unique calculation reduces the uncertainty in picking subtle bed-form boundaries and brings out the full extent of the resolution of the seismic amplitude data. SPICE is computed in the continuous wavelet transform (CWT) domain …