Application of spectral inversion on sand-shale interbedded seismic data

Abstract

Spectral inversion is a seismic method that uses a priori information and spectral decomposition to improve images of thin layers whose thicknesses are below the tuning thickness. Any arbitrary pair of reflection coefficients can be represented as the sum of even and odd components. The even pair has the same magnitude and sign, and the odd pair has the same magnitude and opposite sign. The odd components are not conductive to detect thin beds, while a few even components can improve the thin bed identification. The essential of spectral inversion improves the seismic data resolution using the effective interference of the even components when the thin-bed thickness tends to zero. Spectral inversion yields accurate thickness determinations below tuning, using the inverse relationship between thickness and the constant periodicity of spectral interference patterns. The process differs from other inversions in that it needs no preset geological model and well data, and it is driven by geological rather than mathematical assumptions. The application of this spectral inversion method in a 3D seismic data volume from Daqing oilfield B1D block obtains a reflection coefficient set. Then the resolution of the 3D seismic data volume is improved by the given broad-band wavelet convolution with the reflection coefficient set and seismic attribute interpretation is performed. Results show that the output reflectivity series data has very high resolution and contains much more geological information than the original input seismic data, so that more reflection detail can be picked up and interpreted geologically. Compare with the conventional seismic attribute analysis, this spectral inversion method can improve imaging of subtle stratigraphic features and sedimentary facies.