Seismic Spectral Decomposition Technique And Its Application Research

Seismic spectral decomposition tranformes seismic data from time domaininto the frequency domain, and it provides a new approach of seismic data analysis and interpretation in frequency domain. After seismic data’s spectral decomposition, it generates the amplitude spectrum and phase spectrum. The amplitude spectrum can identify temporal bed thickness variability, and the phase spectrum can detect lateral geological discontinuities. Compared with conventional seismic techniques, spectral decomposition technique can obtain a more accurate geological body imaging, which is now needed to resolve the stratigraphy, lithology, and other complex reservoir problems. It will generate different results when the same seismic data choose differern spectral decomposition algorithms. The choice of spectral decomposition algorithms for spectral decomposition results are important, but many alternative algorithms, each algorithm has certain advantages and disadvantages, and therefore, according to the actual need to select the appropriate spectral decomposition algorithm is very important.This paper discusses the basic principle of the the spectral decomposition and introduce the general used spectral decomposition algorithms in detail. For analysising the advantages and disadvantages of each algorithm, I build a simple wedge model.Using different spectral decomposition algorithms on the wedge model forward results, I analysis the time window size affect on the time-frequency resolution of the short time Fourier transform, and the comparative analysis the time and frequency resolution between the short time Fourier transform, continuous wavelet transform, time-frequency continuous wavelet transform and the S-transform. The wedge model and fault models are analyzed and discussed the factors affect on spectral decomposition results and the advantages of spectral decomposition on detecting the lateral geological discontinuities.. Finally, I apply the spectral decomposition technology in the Xin Nong areas.I get the following conclusions and recommendations through studying the method and application of spectral decomposition:(1) Choosing different spectral decomposition algorithms on the same seismic data, it will get different spectral decomposition results. To select the appropriate spectral decomposition algorithm,we must get well-known about the work area information and depend on the geological tasks.Only through this, spectral decomposition will get good results. (2) Spectral decomposition has more stringent requirements on the seismic data, so not all of the seismic data are suitable for spectral decomposition. So before spectral decomposition,we must evaluate the data in strictly in accordance with the requirements.(3) The spectral decomposition have some effect in improving the seismic resolution. Spectral decomposition technique combined with seismic wave attenuation theory and low-frequency shadows can predict hydrocarbon, but this effect is generally the a posteriori, which is known oil and gas shows in the work area, and then analysis of the spectral decomposition results to see if there are effects, and finally thrust reversers into practical application. Although some places show the energy attenuation and low-frequency shadow phenomenon by spectral decomposition, it not necessarily contain the oil and gas, as multiple solutions for hydrocarbon detection by spectral decomposition. To solve this problem, we can be combined with other reservoir prediction technique to multi-party verification for reducing exploration risk.(4) The spectral decomposition technology is mainly applied to the post-stack seismic data at this stage, but pre-stack data may have a richer frequency information,which is the spectral decomposition technology needs.Therefore, spectral decomposition technology can also be applied to the pre-stack seismic data, combined with the AVO technique for better detection of hydrocarbons.