The application of reverse time migration (RTM) to land seismic data is still a great challenge due to its low quality, low signal-to-noise ratio, irregular spatial sampling, acquisition gaps, and missing traces. Therefore, prior to the application of this kind of depth migration, the input prestack data must be judiciously preconditioned; that is, it must be interpolated, regularized, and enhanced. There are several Fourier-based methods for seismic data preconditioning, but for 2D real land data, as we will show, the regularization of prestack data based on the common reflection surface (CRS) method provides high-quality enhanced preconditioned data, which is suitable for prestack depth migration and velocity model building. We have determined the successful application of RTM to onshore seismic data, revealing the great potential of combining RTM and CRS-based prestack data regularization. We apply this processing combination to real land data with low quality and irregular spatial sampling, from geologically complex areas with the presence of diabase sills and steeply dipping reflectors. Normally, it is very difficult to extract the wavelet of the seismic source from this type of low-quality onshore data because the reflection events are hidden or mixed with noise, and, because of this, RTM migration is often applied using artificial sources (e.g., a Ricker wavelet), which can introduce ringy side lobes in the reflectors. Therefore, we develop a practical algorithm for wavelet determination from the power spectrum of the CRS regularized prestack data, and we apply it successfully in the RTM migration. We develop applications of our prestack data preconditioning based on CRS followed by RTM for two 2D onshore seismic lines from the Tacutu and Parnaiba basins, Brazil. Comparisons with standard Kirchhoff depth migration reveal that the combination of CRS followed by wavelet extraction and then RTM improves the quality and resolution of the final migrated images.

中文翻译：

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基于公共反射面的叠前数据正则化和逆时偏移的结合：在真实土地数据中的应用

由于反向时间偏移（RTM）的质量低，信噪比低，空间采样不规则，采集间隔不足以及缺少迹线，因此将其应用于陆地地震数据仍然是一个巨大的挑战。因此，在应用这种深度迁移之前，必须明智地对输入的叠前数据进行预处理。也就是说，必须对其进行插值，正则化和增强。如前所述，有几种基于傅立叶的地震数据预处理方法，但对于2D真实土地数据，基于公共反射面（CRS）方法对叠前数据进行正则化可以提供高质量的增强型预处理数据。用于叠前深度偏移和速度模型构建。我们确定了RTM在陆上地震数据中的成功应用，揭示了结合RTM和基于CRS的叠前数据正则化的巨大潜力。我们将此处理组合应用于低质量和不规则空间采样的真实土地数据，这些数据来自存在辉绿岩基岩和陡倾反射器的地质复杂区域。通常，很难从这类低质量的陆上数据中提取地震源的小波，因为反射事件被隐藏或与噪声混合在一起，因此，RTM迁移通常使用人工源进行（例如（Ricker小波），可以在反射器中引入环形的旁瓣。因此，我们开发了一种实用的算法，用于从CRS规范化的叠前数据的功率谱中确定小波，并将其成功应用于RTM迁移。我们开发了基于CRS和RTM的叠前数据预处理的应用程序，用于巴西Tacutu和Parnaiba盆地的两条2D陆上地震线。与标准Kirchhoff深度偏移的比较表明，结合CRS，小波提取和RTM，可以提高最终偏移图像的质量和分辨率。