Abstract
In complex near-surface exploration area with strong attenuation, extracting attenuation parameters and compensating attenuation is one of the important steps in seismic data processing. Traditional attenuation parameter estimation methods, such as spectral ratio method and centroid frequency shift method, need to use seismic wavelets, but it is difficult to extract reliable seismic wavelets from strong attenuation and noise seismic data. Without attenuation estimates and the subsequent Q compensation, the resolution of seismic image will be seriously affected. In order to avoid extracting seismic wavelets, the concept of adjacent channel attenuation difference (ACAD) is proposed for the first time, which is the difference between the integrations of the absorption coefficient along the ray paths of adjacent seismic traces. And then a method for Q tomography inversion using ACAD is given. The definition of ACAD is first, and then the centroid frequency shift method for ACAD estimation is givenInthe case of strong attenuation, the correction formula of centroid frequency shift method for the ACAD estimation is derived. The quantitative relationship between the error of ACAD estimates from the noisy record and the SNR calculated from the selected seismic frequency band is discussed, and the correction formula of the centroid frequency shift method for the ACAD estimation under noise condition is proposed. The theoretical noisy data excited by three different source models and produce in the attenuation medium are tested, from which the correctness of the ACAD estimation method and correction formula are verified. Then, the Q tomography inversion equation with the ACAD estimates is given, and the near-surface Q tomography inversion is carried out on the real seismic data in the loess source area, which confirms the feasibility and effectiveness of the approaches introduced in this paper. The ACAD estimation not only eliminates the seismic wavelet extraction step, but also adapts to seismic data with strong attenuation or poor SNR. The accurate Q compensation can improve the reliability and resolution of seismic image.
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