基于波动方程反射波反演的速度模型宽谱重构方法及其海上拖缆数据应用

常规地震勘探中, 地震数据大都缺少大炮检距信号和有效的低频成分, 使得传统的全波形反演(FWI)方法很难恢复中、深层参数模型的低波数分量。依据多尺度反演思想, 采用基于模型分解的波动方程反射波反演方法重构宽谱速度模型, 同时提出自适应构造约束的模型正则化方法优化反演结果, 提高反演稳定性。以Sigsbee模型数据为例展示了该方法是如何有效地同时重构宏观速度模型(长波长)和速度扰动(短波长)或反射率结构的。将所提方法用于东海拖缆采集数据, 利用走时到波形信息匹配的波动方程反射波反演策略, 构建了与地层更加吻合的宏观背景模型, 获得了高分辨的地层成像剖面, 成像道集平整度与成像剖面的连续性有明显提高, 深部基底的成像更加清晰。

Due to the lack of long-offset and usable low-frequency signals in most conventional seismic data, classical full waveform inversion is unable to retrieve long-wavelength components of models in middle and deep zones.Based on the idea of multiscale inversion, a wave-equation reflection inversion method based on model decomposition is used to reconstruct a wide-spectrum velocity model.Meanwhile, an adaptive structure-constrained model regularization method is proposed to optimize inversion results and improve robustness.An experiment using the Sigsbee model illustrated how this approach can effectively reconstruct the macro-velocity model (long wavelength) and velocity disturbance or reflectance structure (short wavelength).In a case study of streamer data acquired in the East China Sea, we employed a wave-equation reflection inversion strategy that combines traveltime and waveform to construct a macroscopic background model more consistent with structures and obtained high-resolution imaging sections simultaneously.Imaging gathers were less noisy and stacked sections were more continuous compared with legacy data, and an improved image of deep basement was yielded.