基于Contourlet变换的地震多属性融合方法

本文提出一种基于Contourlet变换的地震多属性融合方法。首先，通过对多种地震属性进行Contourlet变换，使各属性的多分辨率、多方向性、局部化特性及各向异性得到有效表示。其次，对分解后的属性低频子带采用拉普拉斯能量和（SML）融合规则，高频子带利用各尺度系数间的相关性获取加权系数进行加权融合，不仅强化了各属性的边缘特征和细节信息，并且消除了噪声对融合结果的影响。实际资料应用效果表明，文中方法优于传统小波变换及其他常规融合方法,能消除多属性间的冗余，充分利用不同属性间的有效互补信息，可以提高油气储层预测及流体识别的精度。

Seismic multi-attribute fusion based on Contourlet transform

A novel method for seismic multi-attribute fusion based on Contourlet transform is presented in the paper. First the multi-resolution, multi-directionality, localized features and anisotropy of each seismic attribute can be effectively represented by Contourlet transformation. Then decomposed low-frequency sub-bands are fused with the sum modified Laplacian (SML), and high-frequency sub-bands are fused with weighted coefficients obtained by the correlation of each scale coefficients. This method can not only enhance edge features and details in seismic attributes, but also remove noise in the fusion. Experimental results show that the proposed method is superior to the classic wavelet transform and other conventional fusion methods. Real data applications indicate that this method can eliminate the redundancy of attributes and improve oil-gas reservoir prediction and fluid identification with full use of different attributes.