基于负熵的地震盲反褶积方法及其应用

讨论了基于负熵的地震盲反褶积方法。盲反褶积方法不需要以最小相位子波和高斯白噪反射系数为基本假设，通过高斯混合模型模拟反射系数序列中的强反射信息（地质目标体）和弱反射信息（隐蔽性油气藏），基于负熵的非高斯性判据定义盲反褶积目标函数，应用期望最大化算法求解模型参数的最优估计，最终得到与原始反射系数相似程度很高的非高斯反射系数。选用不同相位子波和非高斯反射系数模型对方法进行了验证，并与维纳脉冲反褶积进行了比较，结果表明，算法适应非最小相位、非高斯系统。将方法应用于实际地震数据处理，地震记录的频带被有效拓宽，地震资料的分辨率得到提高。

Seismic blind deconvolution method based on negative entropy and its application

A seismic blind deconvolution method based on negative entropy was discussed.Blind deconvolution method does not take minimum-phase wavelet and Gauss white noise reflection coefficients as basic assumptions.Through utilizing Gaussian hybrid model,the strong (geologic targets) and weak (subtle reservoir) reflection information in reflection coefficient sequence were simulated;blind deconvolution objective function was defined in terms of non-Gauss criteria based on negative entropy;expectation maximization algorithm was applied to compute the optimal estimation of model parameters,finally non-Gauss reflection coefficient with high similarity to original reflection coefficient was obtained.Different phase wavelet and non-Gauss reflection coefficient model were selected to prove the method,and compared to Viener impulse deconvolution.The results show that the algorithm adapts non-minimum phase and non-Gauss system.The method was applied actual seismic data,the frequency bandwidth was effectively enlarged,and the resolution was improved.