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一阶Rytov近似有限频走时层析
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  • 英文篇名:Wave equation traveltime tomography using Rytov approximation
  • 作者:冯波 ; 罗飞 ; 王华忠
  • 英文作者:FENG Bo;LUO Fei;WANG HuaZhong;Wave Phenomena and Intelligent Inversion Imaging Group (WPI),School of Ocean and Earth Science,Tongji University;
  • 关键词:Rytov近似 ; 有限频走时敏感度核函数 ; 波动方程走时层析 ; 初至波 ; 隐式矩阵向量乘 ; Gauss-Newton方法
  • 英文关键词:Rytov approximation;;Finite-frequency traveltime sensitivity kernel;;Wave-equation traveltime tomography;;First-arrival;;Implicit matrix-vector product;;Gauss-Newton method
  • 中文刊名:DQWX
  • 英文刊名:Chinese Journal of Geophysics
  • 机构:同济大学海洋与地球科学学院波现象与智能反演成像研究组;
  • 出版日期:2019-06-12
  • 出版单位:地球物理学报
  • 年:2019
  • 期:v.62
  • 基金:国家自然科学基金(41774126,41574098,41604091,41704111);; 国家科技重大专项(2016ZX05024-001,2016ZX05006-002)资助
  • 语种:中文;
  • 页:DQWX201906019
  • 页数:10
  • CN:06
  • ISSN:11-2074/P
  • 分类号:233-242
摘要
传统的波动方程走时核函数(或走时Fréchet导数)多基于互相关时差测量方式及地震波场的一阶Born近似导出,其成立条件非常苛刻.然而,地震波走时与大尺度的速度结构具有良好的线性关系,对于小角度的前向散射波场,Rytov近似优于Born近似.因此,本文基于Rytov近似和互相关时差测量方式,导出了基于Rytov近似的有限频走时敏感度核函数的两种等价形式:频率积分和时间积分表达式.在此基础之上,本文提出了一种隐式矩阵向量乘方法,可以直接计算Hessian矩阵或者核函数与向量的乘积,而无需显式计算和存储核函数及Hessian矩阵.基于隐式矩阵向量乘方法,本文利用共轭梯度法求解法方程实现了一种高效的Gauss-Newton反演算法求解走时层析反问题.与传统的敏感度核函数反演方法相比,本文方法在每次迭代过程中,无需显式计算和存储核函数,极大降低了存储需求.与基于Born近似的伴随状态方法走时层析相比,本文方法具有准二阶的收敛速度,且适用范围更广.数值试验证明了本文方法的有效性.
        The conventional wave-equation traveltime sensitivity kernel(TSK)or traveltime Fréchet derivative is derived from the Born approximation and cross-correlation measurement,which has a very narrow valid condition.In fact,the seismic traveltime has a more linear relationship with the large-scale velocity structure.For small-angle forward scattered wavefield,Rytov approximation is proved to be superior to Born approximation.Based on the Rytov approximation and cross-correlation measurement,a new wave-equation traveltime sensitivity kernel is derived.Meanwhile,an implicit matrix-vector product method is proposed,which can directly calculate the product of a matrix(TSK)and a model-space vector as well as the product of a matrix transpose and a data-space vector,eliminating the need of calculating TSK explicitly.Based on the proposed implicit matrix-vector product method,traveltime tomography using the Gauss-Newton inversion algorithm is implemented efficiently by solving the normal equation iteratively using a conjugate gradient method.Compared with the conventional TSK method,the proposed inversion strategy is free of TSK calculation and storage,making it more practical for large-scale problem.Compared with the adjoint traveltime tomography,the proposed method hasaquasi-second-order convergent rate and a broader valid condition.Numerical examples demonstrate the effectiveness of the proposed method.
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