PSDWII：物理结构驱动的波形反演成像
PSDWII: Physical-Structure-Driven Waveform Inversion Imaging
- School of Earth Sciences, Zhejiang University（浙江大学地球科学学院）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文提出PSDWII框架，将波形反演从数学优化驱动转为物理结构驱动，开发了三种具体方法，实现全波形反演等三项反演任务的多参数解耦。
AI中文摘要：
本文提出了一种物理结构驱动的波形反演成像框架（PSDWII），其基础是认识到地表记录的地震数据直接与地下虚拟源相关，而非与模型参数本身相关。基于这一认识，我们将地震波传播分解为三步物理过程：震源激发与入射波传播；入射波与非均质性相互作用，产生具有不同辐射模式的虚拟源并激发次生波；以及次生波的传播与接收。随后，利用传播算子的伴随（逆时外推）构建虚拟源的线性反演投影。通过区分不同虚拟源的表达式及其潜在物理机制，我们为三项反演任务建立了统一的数学表示：全波形反演（FWI）、地层物理属性成像和地层结构成像。在全波形反演中采用反卷积实现多参数解耦，在地层物理属性成像的角度域共成像道集反演中采用线性反演实现多参数解耦。PSDWII框架将传统的“数学优化驱动”的波形反演范式转变为“物理结构驱动”的范式，它既不构建目标函数，也不计算其梯度或海森逆矩阵。在该框架内，我们开发了三种具体方法：物理结构驱动的全波形反演（PSDFWI）、采用角度域共成像道集反演的物理结构驱动地层物理属性成像（PSDSI）以及物理结构驱动的地层结构成像（PSDMig）。
英文摘要：
This paper proposes a Physical-Structure-Driven Waveform Inversion Imaging framework (PSDWII), grounded in the recognition that surface-recorded seismic data are directly related to subsurface virtual sources rather than to the model parameters themselves. Based on this recognition, we decompose seismic wave propagation into a three-step physical process: source excitation and incident wave propagation; interaction of the incident wave with heterogeneities, which generates virtual sources with distinct radiation patterns and excites secondary waves; and propagation and reception of the secondary waves. The adjoint of the propagation operator (reverse-time extrapolation) is then used to formulate a linear inversion projection for the virtual sources. By distinguishing different virtual-source expressions and their underlying physical mechanisms, we establish a unified mathematical representation for three inversion tasks: Full Waveform Inversion(FWI), stratigraphic physical properties imaging, and stratigraphic structures imaging. Deconvolution and linear inversion are respectively adopted to achieve multi-parameter decoupling in FWI and in angle-domain common-image gather inversion for stratigraphic physical properties imaging. The PSDWII framework shifts the conventional ``mathematical optimization driven'' paradigm of waveform inversion to a ``physical-structure-driven'' one. It neither constructs objective functions nor computes their gradients or Hessian inverses. Within this framework, we develop three specific methods: physical-structure-driven FWI (PSDFWI), physical-structure-driven stratigraphic physical properties imaging with angle-domain common-image gather inversion (PSDSI), and physical-structure-driven stratigraphic structures imaging (PSDMig).
