With the development of seismic exploration, passive-source seismic data has attracted increasing attention. Ambient noise passive seismic sources exists widely in nature and industrial production. Passive seismic data is important in logging while drilling (LWD), large-scale structural exploration, etc. In this paper, we proposed a passive multiple reverse time migration imaging (PMRTMI) method based on wavefield decomposition and normalized imaging conditions method. This method differs from seismic interferometry in that it can use raw passive seismic data directly in RTM imaging without reconstruction of virtual active gather, and we use the wavefield decomposition method to eliminate the low frequency noise in RTM. Further, the energy normalized imaging condition is used in full wavefield decomposition, which can not only enhance the image quality of both edge and deep information but also overcome the wrong energy problem caused by uneven distribution of passive sources; furthermore, this method exhibits high efficiency. Finally, numerical examples with the Marmousi model show the effectiveness of the method.

中文翻译：

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基于波分解和归一化成像条件的被动多次逆时偏移成像

随着地震勘探的发展，无源地震资料引起了越来越多的关注。环境噪声无源地震源在自然界和工业生产中广泛存在。被动地震数据在随钻测井（LWD），大规模结构勘探等方面具有重要意义。本文基于波场分解和归一化成像条件方法，提出了一种被动多次逆时偏移成像（PMRTMI）方法。该方法与地震干涉法的不同之处在于，它可以直接在RTM成像中使用原始的被动地震数据，而无需重建虚拟的主动采集，并且我们使用波场分解方法来消除RTM中的低频噪声。此外，能量归一化成像条件用于全波场分解，不仅可以提高边缘信息和深度信息的图像质量，而且还可以解决由于无源光源分布不均而导致的错误的能量问题。此外，该方法显示出高效率。最后，Marmousi模型的数值例子证明了该方法的有效性。