Abstract
Channels are hydrocarbon prospective areas
which are often below the resolution of seismic data. This study was therefore
conducted with the aim of using spectral decomposition methods for imaging of
buried channels and associated structures in a 3D Post-Stack Depth Migrated
(PSDM) volume acquired from a field in the Niger Delta Basin. Two commonly used
spectral decomposition methods were used to enhance the resolution of seismic
data for interpretation. The methods utilized included Fast Fourier Transform (FFT)
and Continuous Wavelet Transform (CWT). Petrel and Opendtect were the
interpretational software tools utilized for the study. The seismic data was
conditioned using structural smoothing, and a zone of interest was selected
around -1000 to -3000ms. Three dominant frequencies were selected from the
sub-volume generated around the zone of interest. The frequencies were 10Hz,
25Hz and 32Hz respectively. These frequencies were extracted from the seismic
data using FFT and CWT decomposition methods. The results were colored using
Red, Green and Blue (Red for 10Hz, Green for 25Hz and Blue for 32Hz). These
frequencies were then blended together in a process called RGB blending. The
resultant output was a mix of only these three dominant frequencies. Analysis
of these results revealed the presence of several channels, crevasse splay
deposits, flood-plains and faults on two time-slices obtained at -2020ms and
-1800ms. The channels were meandering channels of low sinuosity, some of which
were fault controlled. The crevasse splay deposits were significantly large and
increased in number at the shallow time-slice. Some of the crevasse splay
deposits were found bifurcating fault lines and being deposited on floodplains,
indicating that they were younger than the faults. Channel flow direction was
from East to West, while channel migration was from South to North of the study
area. The increase in the number of channels from the base to the top of the
seismic data suggested a multistory stacked channel system. It was established
that channels and crevasse splays were best enhanced using the FFT
decomposition method while major and minor faults were best enhanced using CWT
method. Hence, this study has proven that the spectral decomposition method is
very effective in imaging subsurface buried channels, thus delineating
prospects and can be used for reservoir characterization.
Keywords: Spectral decomposition, Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT), Channels, Crevasse splays, Faults, Reservoir Characterization.