反射波时频域地震波形反演方法

    Reflection waveform inversion in the time-frequency domain

    • 摘要: 反射波形反演通过交替更新模型中的中低波数组分和高波数组分为全波形反演提供良好的初始模型。但时域反射波形反演需要存储整个时间序列的震源背景波场与接收点散射波场互相关求取梯度,占用巨量的计算机存储空间。频域反射波形反演虽然有多尺度特性,但对计算机运算内存要求高。本文通过离散傅里叶变换,从时域波场提取对应的频域波场进行多尺度的时频域反演,仅需存储数片单频波场,在存储需求方面明显优于传统的时域反演,运算成本方面明显优于频率域,结合了时域反演的高效性和频域反演多尺度的特性。针对实际地震资料低频地震数据易缺失的问题,进一步结合包络反射波反演,在重构中深层地下介质低频信息的基础上进行逐级优化反演,降低对低频长偏移地震数据的要求。最后本文通过数值算例验证了基于包络数据的时频域反射波形反演方法对低频信息恢复的有效性。

       

      Abstract: Reflection waveform inversion(RWI) provides an effective initial model for full waveform inversion(FWI) by alternately updating the low-to-intermediate and high wavenumber components in the model.However,time-domain RWI requires storing the cross-correlation between the source background wavefield and the receiver scattered wavefield over the entire time series to compute gradients,demanding substantial computational storage.Although frequency-domain RWI exhibits multi-scale properties,it also imposes high demands on computational memory.Based on the discrete Fourier transform,this study proposed a RWI method that extracts frequency-domain wavefields from corresponding time-domain wavefields for multi-scale inversion in the time-frequency domain.The proposed method requires storing only a few single-frequency wavefield snapshots,showing significantly lower storage demands compared to conventional time-domain RWI and reduced computational costs relative to frequency-domain RWI.Therefore,the proposed method effectively combines the computational efficiency of time-domain RWI with the multi-scale properties of frequency-domain RWI.Considering the frequently missing low-frequency data in actual seismic data,this study further integrated envelope-based RWI to reconstruct low-frequency information for medium-deep subsurface structures.This enables stage-wise optimization of the inversion process,reducing the dependency on low-frequency long-offset data.Finally,numerical examples validate the effectiveness of the time-frequency domain RWI method based on envelope data in recovering low-frequency information.

       

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