Abstarct: Spectral decomposition baxsed on Fourier transform is one of the useful tolls in geophysics. This method has widely used in seismic data processing and interpretation. Underground changes affect frequency content of seismic data. Study of frequency content of these information can map subtle changes of channel thickness, temporal bed tuning thickness, location of hydrocarbon reservoirs and so on. The earth behaves such as low pass filter. So when seismic signals travel in the earth, frequency content of seismic signals changes with time and they became non-stationary. Fourier transform is not suitable to representation of non-stationary signals so time-frequency transforms introduced. Time-frequency distribution is utilized as a powerfull toll for simultaneously representation of signals in both time and frequency domain, can reveal the characteristics that are not easily observed in the time representation or the frequency representation alone. There are many time-frequency distribution such as Short Time Fourier transform, Continous Wavelet transform, S transform and Wigner-Ville distribution. Conventional time-frequency distributions have many advantages but moreover have some restrictions that arise from various reasons such as Heisenberg uncertainty principle and superposition principle. Therefore looking for methods which preserve the existing advantages of the conventional methods and eliminate disadvantages of them is necessary. Reduced Interference distribution is one of best of these methods. In this thesis, we used Reduced Interference distribution to identify thin beds, buried channels and hydrocarbon reservoirs by extracting seismic attributes. We compare our results with conventional time-frequency distributions and earn more accurate results.