Angle-domain common-image gathers (ADCIGs) that can be used for migration velocity analysis and amplitude-versus-angle analysis are important for seismic exploration. However, because of the limited acquisition geometry and seismic frequency band, ADCIGs extracted by reverse time migration (RTM) suffer from illumination gaps, migration artifacts, and low resolution. We have developed a reflection angle-domain pseudoextended plane-wave least-squares RTM method for obtaining high-quality ADCIGs. We build the mapping relations between the ADCIGs and the plane-wave sections using an angle-domain pseudoextended Born modeling operator and an adjoint operator, based on which we formulate the extraction of ADCIGs as an inverse problem. The inverse problem is iteratively solved by a preconditioned stochastic conjugate-gradient method, allowing for reduction in computational cost by migrating only a subset instead of the whole data set and improving the image quality thanks to preconditioners. Numerical tests on synthetic and field data verify that our method can compensate for illumination gaps, suppress migration artifacts, and improve resolution of the ADCIGs and the stacked images. Therefore, compared to RTM, our method provides a more reliable input for migration velocity analysis and amplitude-versus-angle analysis. Moreover, it also provides much better stacked images for seismic interpretation.

中文翻译：

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来自平面波最小二乘法逆时偏移的角域共像道集

可用于偏移速度分析和振幅对角分析的角域共像道集 (ADCIG) 对于地震勘探非常重要。然而，由于采集几何和地震频带有限，通过逆时偏移 (RTM) 提取的 ADCIG 受到光照间隙、偏移伪影和低分辨率的影响。我们开发了一种反射角域伪扩展平面波最小二乘 RTM 方法，用于获得高质量的 ADCIG。我们使用角域伪扩展玻恩建模算子和伴随算子建立 ADCIG 和平面波截面之间的映射关系，在此基础上我们将 ADCIG 的提取公式化为逆问题。逆问题通过预处理随机共轭梯度方法迭代求解，允许通过仅迁移子集而不是整个数据集来降低计算成本，并通过预处理器提高图像质量。对合成和现场数据的数值测试验证了我们的方法可以补偿照明间隙、抑制迁移伪影并提高 ADCIG 和堆叠图像的分辨率。因此，与 RTM 相比，我们的方法为偏移速度分析和幅度对角度分析提供了更可靠的输入。此外，它还为地震解释提供了更好的叠加图像。并提高 ADCIG 和堆叠图像的分辨率。因此，与 RTM 相比，我们的方法为偏移速度分析和幅度对角度分析提供了更可靠的输入。此外，它还为地震解释提供了更好的叠加图像。并提高 ADCIG 和堆叠图像的分辨率。因此，与 RTM 相比，我们的方法为偏移速度分析和幅度对角度分析提供了更可靠的输入。此外，它还为地震解释提供了更好的叠加图像。