We present an integrated algorithm for high-resolution crustal-scale imaging utilizing long-offset wide-angle ocean-bottom seismometer (OBS) data and short-offset multichannel streamer (MCS) data. The algorithm adopts a two-step imaging strategy, initially using the OBS data to enhance deep structure imaging and capture long-wavelength features of the migration velocity. Subsequently, the MCS data are migrated to recover detailed short-wavelength components and shallow structures using the migration velocity model modified by the OBS result. Both steps employ the least-squares reverse time migration (LSRTM) method with appropriate regularization techniques. The algorithm is implemented using the Bregmanized operator splitting (BOS) approach, known for its efficiency and adaptability in handling non-smooth regularization, such as total-variation (TV) constraints. To improve computational efficiency, compressed sensing is employed to store incident wavefields at half their actual size and reconstruct them accurately when required. Convergence is expedited through the use of preconditioners and the Anderson acceleration method. The proposed algorithm is validated through large-scale numerical examples, demonstrating its robustness even with an initially imprecise velocity model. Results showcase improved resolution and accuracy achieved through the integration of OBS and MCS data. This study offers a comprehensive framework for crustal-scale imaging, addresses computational complexities, and provides enhanced imaging capabilities.

中文翻译：

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使用互补 OBS 和流光数据进行高分辨率地壳尺度成像的集成算法

我们提出了一种利用长偏移距广角海底地震仪（OBS）数据和短偏移距多通道拖缆（MCS）数据进行高分辨率地壳尺度成像的集成算法。该算法采用两步成像策略，首先利用OBS数据增强深层结构成像并捕获偏移速度的长波长特征。随后，使用OBS结果修改的偏移速度模型对MCS数据进行偏移以恢复详细的短波长分量和浅层结构。这两个步骤均采用最小二乘逆时偏移 (LSRTM) 方法和适当的正则化技术。该算法使用 Bregmanized 算子分裂 (BOS) 方法实现，该方法以其在处理非平滑正则化（例如总变分 (TV) 约束）方面的效率和适应性而闻名。为了提高计算效率，采用压缩感知来存储实际大小一半的入射波场，并在需要时准确地重建它们。通过使用预处理器和安德森加速方法可以加速收敛。所提出的算法通过大规模数值例子进行了验证，即使在最初不精确的速度模型下也证明了其鲁棒性。结果展示了通过 OBS 和 MCS 数据集成实现的分辨率和准确性的提高。这项研究为地壳尺度成像提供了一个全面的框架，解决了计算复杂性，并提供了增强的成像能力。