Analyzing seismic attributes in the frequency domain is quite important for detailing many reservoir intervals. Such details are essential for reservoir characterization and de-risking new appraisal and production drilling locations. Spectral decomposition with color blending is a key attribute for extracting significant components from the seismic spectrum. This paper examines an illuminated workflow which involves data conditioning and frequency decomposition for detecting subtle changes within seismic signals for the late Messinian prolific Abu Madi Formation, Nile Delta, Egypt. Firstly, Post-stack noise cancellation filter is used for enhancing the data by filtering out random noise using a structurally oriented and edge-preserving algorithms. To increase the reflector continuity, in the area of poor-quality data, a stronger noise attenuation workflow followed by an amplitude normalization was applied. This poor-quality area is directed from the presence of Messinian anhydrite which masks any pertinent true amplitude. Both noise cancellations were then combined and this noise cancelled dataset was used as an input for the spectral enhancement. Several spectral enhancements attempts were tested using different methods; one involved the enhancement of the low frequencies using a low-pass high-cut filter, and the other one involved an enhancement of both the low and the high frequencies, aiming for a white spectrum. Frequency decomposition and RGB blending were applied on both enhanced datasets, using two different methods: one involving a window-based Fast Fourier Transform (FFT) and the other one involving an adaptive matching pursuit algorithm. The bright colours observed in the blends were interpreted as an indicator of the presence of hydrocarbon which associated with clear depositional architectures and elements. The results of this work derisked the presence hydrocarbon potentiality at a proposed location of the North El-Amirya Exploration well (NEA-2X). An obvious meandering channel towards the crest of the fault block and along the proposed location is clearly identified.