【摘要】 地震数据处理通常假定反射数据仅由一次波组成,地震勘探资料中的表面多次波通常被视为相干噪音予以压制.基于波动方程预测的反馈迭代法为数据驱动的方法,可有效压制复杂地下介质的表面多次波,通常可由级数展开法和迭代法两种方法实现.文中分别从理论阐述以及应用效果分析方面对基于波动方程预测的反馈迭代法的两种实现途径进行研究,并采用GPU/CPU协同并行加速计算预测表面多次波,改善以往CPU计算效率低的状况.文中对含表面多次波的炮数据和复杂的SMAART模型进行了计算,并将利用级数展开法与迭代法压制表面多次波的效果进行对比分析,结果表明,迭代形式反馈迭代法压制表面多次波的方法效果更佳.由于实现迭代法和级数展开法需要完成的自适应匹配相减的次数不同,迭代法的计算成本略高于级数展开法.更多还原

【Abstract】 We usually assume that reflection data only consist of primary during seismic data processing.And surface-related multiple in seismic prospecting data is usually suppressed as coherent noise.Data-driven feedback iteration approach based on wave equation prediction is an effective method which can suppress surface-related multiple from complex earth media.This algorithm can be performed by either series expansion or iteration.In this paper,the two implementation approaches for feedback iteration based on wave equation prediction is researched from theory description and applied effect analysis perspective,this paper also give specific explanation on basic principles of the two approaches.In this paper,surface-related multiple is predicted by collaborative parallel calculation of GPU/CPU,which can improve the situation of low calculation efficiency by CPU.With the development of GPU accelerating technology,computation efficiency for seismic data processing is improved.This will be helpful when applying iteration approach on suppressing surface-related multiple of large scale seismic data.The shot data with surface-related multiple and SMAART model with surface-related multiple from complex media have been tested in the paper.In this research,result of series expansion approach shows it needs to be obtained by summing many prediction items,and in fact the number of predictable items is usually limited,this will lead to errors in the multiple suppression process.In contrast to series expansion approach,we can obtain better multiple suppression effect by iteration approach.The effect is usually ideal when iteration approach is used after three times.Iteration can also be combined with many other approaches,it shows more flexibility.Different amount of adaptive matching subtraction are required for iteration and series expansion approach,so the computation cost of iteration is slightly higher than that of series expansion approach,but GPU accelerating method can solve the problem in some degree.Iteration approach is more effective on complex media,so that it has more widely applied range and development prospect.更多还原