【摘要】 本文基于波动方程的自由表面多次波压制预测减去法,采用近期迅速发展的多尺度变换系统中的Curvelet变换替代减去法,收到了较好的效果。该变换具有最优稀疏约束条件,能使一次波在一组基函数上的投影能量尽可能小。其主要实现过程为:对地震记录数据进行Curvelet变换,以预测多次波的Curvelet域的系数为阈值,采用类似去噪的手段去除多次波。该方法能满足去除多次波过程的能量最小准则。文中在Curvelet算法数值实验中尝试了先把地震记录做Radon变换,并用Curvelet阈值法减去Radon域的多次波,再把去除了多次波的数据做反Radon变换即为多次波去除结果。数值实验结果表明,在Radon域进行Curvelet变换去除多次波的效果更好,并能更好地保留一次波的能量。更多还原

【Abstract】 The paper uses Curvelet transform in multiple-scale transform system rapidly developed in recent years to replace the elimination process of wave-equation-based predictive subtraction method for free-surface-related multiple suppression, and receives better multiple-eliminated effects. The transform is characterized by optimum sparseness constraint condition that makes the mapping energy of primary reflections on a set of basis function as small as possible. The major implement process as follows: the Curvelet transform is carried out for seismic data, then, to take the coefficients of predictive multiple in Curvelet domain as thresholds by finally using similar noise-eliminated tools to eliminate multiple. The method can meet the minimum energy norm in multiple-eliminated process. In the numeric tests of Curvelet algorithm, the paper tries Radon transform of seismic data first, subtracts the multiple in Radon domain by using Curvelet thresholds method, and multiple-eliminated results are from inverse Radon transform of multiple-eliminated data. The numeric tests showed the better multiple-eliminated effects come from the transform in Radon domain for the Curvelet transform and the energy of primary reflections can be better remained.更多还原