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There is a diversity of seismic attributes that are accessible for the fluvial reservoir characterization. Withal, the accurate optimization of attributes within the tectonically inverted reservoirs like the Syncline and Horst structures is the chief confront for the prospect delineation. During the stratigraphic pinch-out demarcation, the resolution is to image the sandstone and discriminate the porous and non-porous reservoirs. The continuous wavelet transforms of spectral decomposition tool is a proven stratigraphic reservoir characterization tool. Therefore, this study validates the triumphant execution of the continuous wavelet transforms of spectral decomposition tool for illuminating the high-quality sands distribution along the reservoir architectures on Miano gas field in the Middle Indus Basin, Pakistan. The predictable gears like the root-mean-square (RMS) amplitude provide inadequate reservoir characterization. However, the continuous wavelet transforms of spectral decomposition technique resolves the thin sand beds and quantitatively characterizes the reservoir fluids. The statistical analysis of B-reservoir reveals strong correlation coefficients of ~ (R) 2 > 0.8 for 28 Hz and ~ (R) 2 > 0.75 for absolute average amplitude characteristics along the Syncline. Conversely, the RMS demonstrates weak correlation coefficient of ~ (R) 2< 0.2. The instantaneous frequency model detects the oil sand lens encased within the mudrock that is corroborated by the spectral decomposition. The acoustic impedance-based instantaneous spectral modeling brightens the high-porosity (bright negative acoustic impedance anomalies) zones within the ultra-thin stratigraphic pinch-out reservoir configurations at 37 Hz and 48 Hz. Frequency bandwidth of 10 Hz to 50 Hz is suitable for delineation of complex oil and gas-bearing litho-fluids, architecture, and hence, CWT can be used as finest tool as compared to broadband seismic for characterization of pools (conventional and unconventional resource shale plays) stratigraphic examinations (Tayyab et al., 2017a; Naseer and Asim, 2017b; Tayyab and Asim, 2017c; Naseer and Asim, 2017d). The wedge modeling using the seismically extracted can yield a better resolution as compared to wavelet extraction made inside the designed spectrum (Naseer and Asim, 2017d).
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