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Passive seismic full waveform inversion using reconstructed body-waves for subsurface velocity construction

机译:用于地下速度施工的重建体波的被动地震全波形反演

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摘要

Full waveform inversion (FWI) using passive seismic data can use amplitude, phase and travel time information from the data simultaneously. However, at least three challenges are involved in passive seismic full waveform inversion (PSFWI): a low signal-to-noise ratio (SNR), source location uncertainty and an unknown source wavelet. In this study, we propose a method that combines seismic interferometry and a source-independent inversion algorithm to solve these problems. Using seismic interferometry, the original passive seismic data recorded on the surface can be reconstructed into new virtual source records that have a relatively high SNR and certain source location. The source-independent algorithm eliminates the influence of source wavelet error on the final inversion results. Through numerical tests, we discuss the effects of passive source number and recording time on the inversion results and find that increasing the source number or recording time can improve inversion quality. We extract the background velocity model from the results of PSFWI and use it as the initial model of active source FWI. Least square reverse time migration (LSRTM) is then conducted to verify the accuracy of the inverted velocity models. The final results demonstrate that our PSFWI method can construct accurate long-wavelength velocity structures for subsequent active source FWI. The velocity model constructed using our successive inversion strategy can improve the LSRTM results.
机译:使用被动地震数据的全波形反转(FWI)可以同时使用来自数据的幅度,相位和行进时间信息。然而,至少有三个挑战涉及被动地震全波形反演(PSFWI):低信噪比(SNR),源位置不确定度和未知源小波。在这项研究中,我们提出了一种结合地震干涉测量和源无关的反演算法来解决这些问题的方法。使用地震干涉测量法,可以重建在表面上记录的原始被动地震数据重建为具有相对高的SNR和某些源位置的新虚拟源记录。源无关的算法消除了源小波误差对最终反演结果的影响。通过数值测试,我们讨论了被动源码和记录时间对反转结果的影响,并发现增加源号或录制时间可以提高反转质量。我们从PSFWI的结果中提取了背景速度模型,并将其用作有源FWI的初始模型。然后进行最小方反时间迁移(LSRTM)以验证反相速度模型的准确性。最终结果表明,我们的PSFWI方法可以为后续有源源FWI构建精确的长波长速度结构。使用连续反转策略构建的速度模型可以提高LSRTM结果。

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