Detecting buried channels using linear least square RGB color stacking method based on deconvolutive short time Fourier transform

Buried channels are one of the stratigraphic hydrocarbon traps. They are often filled with a variety of porous and permeable sediments so they are important in exploration of oil and gas reservoirs. In reflection seismic data, high-frequency components are sensitive to the channel thickness, whereas, low-frequency components are sensitive to the channel infill materials. Therefore, decomposition of seismic data to its spectral components provides useful information about both thickness and infill materials of buried channels. A 4D spectral data is produced by applying spectral decomposition to a 3D seismic data cube which is decomposed into several single frequency 3D cubes. Since different frequencies carry different types of information, each single frequency cube cannot show all subsurface information simultaneously. Therefore, we used color stacking method and constructed RGB plots, which represent more information than single frequency volumes. In this paper, we applied three methods of Deconvolutive Short Time Fourier Transform (DSTFT), S Transform (ST) and Short Time Fourier Transform (STFT) to a land seismic data from an oil field in south-west of Iran. We used the resulting spectral volumes to create RGB color stacking plots for tracing buried channels. According to the results, the RGB plots based on the DSTFT method revealed more details than the ST and STFT methods.