融合点扩散函数的预条件黏声最小二乘逆时偏移
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  • 英文篇名:Preconditioned visco-acoustic least-squares reverse time migration integrated with point spread function
  • 作者:姚振岸 ; 孙成禹 ; 喻志超 ; 马振
  • 英文作者:YAO Zhen'an;SUN Chengyu;YU Zhichao;MA Zhen;Fundamental Science on Radioactive Geology andExploration Technology Laboratory,East China U-niversity of Technology;School of Geosciences,China University of Pe-troleum (East China);Institute of Oil & Gas,School of Earth andSpace Sciences,Peking University;
  • 关键词:最小二乘逆时偏移 ; 黏声 ; 点扩散函数 ; 去模糊滤波器 ; 预条件
  • 英文关键词:least-squares reverse time migration;;visco-acoustic;;point spread function;;deblurring fil-ter;;preconditioned
  • 中文刊名:SYDQ
  • 英文刊名:Oil Geophysical Prospecting
  • 机构:东华理工大学放射性地质与勘探技术国防重点学科实验室;中国石油大学(华东)地球科学与技术学院;北京大学地球与空间科学学院石油与天然气研究中心;
  • 出版日期:2019-02-15
  • 出版单位:石油地球物理勘探
  • 年:2019
  • 期:v.54
  • 基金:国家自然基金项目“深度偏移地震数据特征剖析与深度域直接反演方法研究”(41874153);; 国家科技重大专项“复杂目标多尺度资料高精度处理关键技术研究”(2016ZX05006-002);; 江西省教育厅科技项目“三维双复杂介质微地震波场全波形模拟与特征研究”联合资助
  • 语种:中文;
  • 页:SYDQ201901009
  • 页数:13
  • CN:01
  • ISSN:13-1095/TE
  • 分类号:7-8+87-97
摘要
在传统黏声最小二乘逆时偏移(Q-LSRTM)中,用于反传残差数据的伴随Q传播算子也是衰减的,因此导致其成像分辨率较低。为了改善Q-LSRTM的低分辨率问题,基于点扩散函数(PSF)构建黏声去模糊滤波器,然后将其作为Q-LSRTM迭代过程中的预条件化因子,最终实现高分辨的衰减补偿偏移,因此称为预条件Q-LSRTM。模型测试表明,预条件Q-LSRTM能获得更高的分辨率、更均衡的振幅以及更快的收敛速度。Q值偏移模型的敏感性测试表明,与Q-LSRTM相似,为了显著改善成像效果,预条件Q-LSRTM也需要相对精确的Q值模型和速度模型。
        In conventional visco-acoustic least-squares reverse time migration(Q-LSRTM),the adjoint Q propagators used for backward propagating residual data are also attenuative.Thus,the inverted images from Q-LSRTM are often observed to have lower resolution.To increase the resolution of QLSRTM,a preconditioned visco-acoustic leastsquare reverse time migration is put forward in this paper.The preconditioner is built with viscoa-coustic deblurring filters based on visco-acoustic point spread function.Model tests show that the preconditioned Q-LSRTM can produce images with higher resolution and more balanced amplitudes with faster convergence rate.With sensitivity tests of migration Q model,as the same case of Q-LSRTM,preconditioned Q-LSRTM also need a fairly accurate estimation of migration Q model in order to obtain noticeable improvements in the image quality,meanwhile a fairly accurate velocity model is also needed.
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