The Spectral Decomposition Technique Based On MP And Its Application In Seismic Signal Processing

The spectral decomposition technique is an effective method for processing and interpreting seismic data. Firstly, this paper studies the basic principle and compares with several traditional time-frequency analysis methods such as short-term Fourier transform, Gabor transform, wavelet transform and Wigner-Ville distribution, and tak ing the correct time- frequency analysis method to ensure the quality of seismic spectral decomposition is critical.According to the characteristics of seismic signals in time domain and frequency domain localization, the MP(matching pursuit) algorithm is applied to carry on the treatment, which are discussed in details based on the basic idea of spectrum decomposition technique, operation principle and the realization method. Because the MP algorithm has good time- frequency aggregation and flexible adaptability, the MP algorithm is applied to seismic spectrum decomposition technique, in explaining stratigraphic response and reservoir characterization show its advantage, and is an effective method for the recognition of the oil and gas reservoir.Aiming at the problem of large amount of computation and low efficiency in the process of signal sparse decomposition, the paper improves the MP algorithm. Using artificial bee colony algorithm to optimize the MP algorithm to find the best atomic process, in order to reduce the amount of computation and improve the operation rate. At the same time, to improve the local search ability of artificial bee colony algorithm, the improved artificial bee colony algorithm is put forward and the speed of spectral decomposition is improved. Finally, the spectral decomposition technique is applied to obtain the underground storage layer under different frequency spectrum profile and single channel set based on improved MP, and to recognition of oil and gas reservoir according to the seismic wave attenuation theory and low- frequency shadows.