Hembram, S. and Gupta, S.D., 2021. Significance of suitable wavelet estimation to the analysis of Spectral Decomposition method to detect channel feature: a case study in the Jaisalmer Sub-basin, India. Journal of Seismic Exploration, 30: 381-404. Capturing the reservoir body in complex geology through regular attribute analysis is a challenging task. Subsurface imaging based on spectral decomposition analysis shows an improvement procedure for hydrocarbon exploration, especially in the complex geological setup. The spectral decomposition study was carried out in the Jaisalmer sub-basin. The sedimentary basin has the potential for hydrocarbon exploration. However, frequent alternation of lithology in the clastic and carbonate reservoir formation has made the exploration task challenging. Wavelet pattern recognition is a fundamental aspect of this process. The Continuous Wavelet Transformation (CWT) method was adopted to carry out the spectral decomposition study. A suitable wavelet was identified to characterize the reservoir lithology. The Gaussian wavelet produced a better and optimized outcome in this study than the other wavelets, such as Morlet and Mexican Hat. Few advanced attribute analyses such as geo-body capture and variance study were carried out based on volume rendering through the RGB blending process. The process was adopted using spectrally decomposed volume. The attribute analysis has produced an image that shows the extension of the reservoir lithology in the study area. One paleochannel was identified based on this study in the Pariwar formation as a potential reservoir architecture of hydrocarbon exploration.