Inversion of Young’s modulus,Poisson’s ratio and density from pre-stack seismic data has been proved to be feasible and effective.However,the existing methods do not take full advantage of the prior information.Without considering the lateral continuity of the inversion results,these methods need to invert the reflectivity first.In this paper,we propose multi-gather simultaneous inversion for pre-stack seismic data.Meanwhile,the total variation(TV)regularization,L_1 norm regularization and initial model constraint are used.In order to solve the objective function contains L_1norm,TV norm and L_2 norm,we develop an algorithm based on split Bregman iteration.The main advantages of our method are as follows:(1)The elastic parameters are calculated directly from objective function rather than from their reflectivity,therefore the stability and accuracy of the inversion process can be ensured.(2)The inversion results are more in accordance with the prior geological information.(3)The lateral continuity of the inversion results are improved.The proposed method is illustrated by theoretical model data and experimented with a 2-D field data.
Most image saliency detection models are dependent on prior knowledge and demand high computational cost. However, spectral residual(SR) and phase spectrum of the Fourier transform(PFT) models are simple and fast saliency detection approaches based on two-dimensional Fourier transform without the prior knowledge. For seismic data, the geological structure of the underground rock formation changes more obviously in the time direction. Therefore, one-dimensional Fourier transform is more suitable for seismic saliency detection. Fractional Fourier transform(FrFT) is an improved algorithm for Fourier transform, therefore we propose the seismic SR and PFT models in one-dimensional FrF T domain to obtain more detailed saliency maps. These two models use the amplitude and phase information in FrFT domain to construct the corresponding saliency maps in spatial domain. By means of these two models, several saliency maps at different fractional orders can be obtained for seismic attribute analysis. These saliency maps can characterize the detailed features and highlight the object areas, which is more conducive to determine the location of reservoirs. The performance of the proposed method is assessed on both simulated and real seismic data. The results indicate that our method is effective and convenient for seismic attribute extraction with good noise immunity.
