随着油气勘探开发目标的日趋复杂和精细，对复杂介质地震成像的质量提出更高的要求。由偏移方法所得到的成像结果常常是地下真实结构畸变了的像，数学上可表示为点弥散函数与速度模型的卷积，点弥散函数包含了影响成像质量的所有信息。借鉴发育生物学fate mapping的思想，我们提出了染色算法，该算法可实现对任意目标结构的标记进而获得与该结构相关的波场和数据。此外，将染色算法用于计算点弥散函数并进一步利用点弥散函数开展角度域照明信息提取、近地表非均匀性对地震数据和成像质量的影响等一系列研究。本项目在前期的基础上，围绕提高复杂介质地震成像质量，从发展和完善染色算法相关理论、点弥散函数计算精度与效率的平衡、利用点弥散函数校正原始成像结果等方面开展研究。该研究不仅在理论方面对在地震波传播中标记与特定目标相关的能量具有重要意义，同时在应用方面对提高复杂地质结构下油气探测精度进而提高油气采收率也具有积极贡献。

Reflection migration is an important processing technique for detecting the subsurface structure in oil and gas exploration. The imaging result obtained by migration is a distorted image of the subsurface structure, and can be represented as a convolution between the point spreading function and the velocity model. The point spreading function consists all the information of the factors affecting the imaging quality. We employ the idea of developmental biology, develop the staining algorithm which can be used for marking any structure and the related seismic wavefield and data. In addition, we apply staining algorithm to calculation of the point spreading function, extraction of the angle domain illumination information and investigation on the effect of the small scale near surface heterogeneity to the seismic data and image. Based on these results, we focus on the improvement of the imaging quality by investigating the questions as follows: further develop the staining algorithm, investigate the accuracy and efficiency of PSF calculation, and the deconvolution between the PSF and original image. This study is not only significant in marking and tracing the seismic energy of a target structure, but also in improving the quality and quantity of the oil production.