中国石油大学学报（自然科学版）Issue(1)：43-49,7.DOI:10.3969/j.issn.1673-5005.2015.01.006
基于高阶稀疏Radon变换的预测多次波自适应相减方法
Multiples prediction and adaptive subtraction with high-order sparse Radon transform
摘要
Abstract
An adaptive subtraction in high-order sparse Radon domain for multiple-elimination is proposed. Subtraction in time domain can damage primary while it is overlapped with multiples. Radon transform is not an orthogonal transforma-tion; its inversion will loss data trivial. For primary-preservation, the high-resolution sparse Radon transform is incorporat-ed with orthogonal polynomial transformation and sparse representation by an overcomplete dictionary, thus a high-order sparse Radon transform is achieved. The high-order sparse Radon transform not only keeps primary amplitude but improves the resolution of multiple elimination. The adaptive subtraction in high-order sparse Radon domain will decrease the dam-age to the primaries. The experiments with synthetic data and field data show good performances in multiple elimination and AVO( amplitude versus offset)-preservation.关键词
Radon变换/正交多项式变换/过完备字典/自适应相减/AVO(振幅随偏移距的变化)Key words
Radon transform/orthogonal polynomial transform/overcomplete dictionary/adaptive subtraction/AVO( ampli-tude versus offset)分类
能源科技引用本文复制引用
薛亚茹,杨静,钱步仁..基于高阶稀疏Radon变换的预测多次波自适应相减方法[J].中国石油大学学报（自然科学版）,2015,(1):43-49,7.基金项目
国家自然科学基金项目(41204095) （41204095）
