In the last decade, a significant shift in the marine seismic acquisition business has been made where ocean bottom nodes gained a substantial market share from streamer cable configurations. Ocean bottom node acquisition (OBN) can acquire wide azimuth seismic data over geographical areas with challenging deep and shallow bathymetries and complex subsurface regimes. When the water bottom is rugose and has significant elevation differences, OBN data processing faces a number of challenges, such as denoising of the vertical geophone, accurate wavefield separation, redatuming the sparse receiver nodes from ocean bottom to sea level and multiple attenuation. In this work, we review a number of challenges using real OBN data illustrations. We demonstrate corresponding solutions using processing workflows comprising denoising the vertical geophones by using all four recorded nodal components, cross-ghosting the data or using direct wave to design calibration filters for up- and down-going wavefield separation, performing one-dimensional reversible redatuming for stacking QC and multiple prediction, and designing cascaded model and data-driven multiple elimination applications. The optimum combination of the mentioned technologies produced cleaner and high-resolution migration images mitigating the risk of false interpretations.

中文翻译：

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OBN 处理回顾：挑战与解决方案

在过去十年中，海洋地震采集业务发生了重大转变，海底节点从拖缆配置中获得了可观的市场份额。海底节点采集 (OBN) 可以在具有挑战性的深浅水深和复杂地下状态的地理区域上获取宽方位角地震数据。当水底有皱褶且高程差异较大时，OBN数据处理面临着垂直检波器去噪、波场精确分离、将稀疏接收节点从海底重定为海平面、多重衰减等挑战。在这项工作中，我们使用真实的 OBN 数据插图回顾了一些挑战。我们使用处理工作流程演示了相应的解决方案，包括通过使用所有四个记录的节点分量对垂直地震检波器进行去噪，交叉重影数据或使用直接波设计校准滤波器以用于上行和下行波场分离，执行一维可逆重调堆叠QC和多重预测，设计级联模型和数据驱动的多重消除应用程序。上述技术的最佳组合产生了更清晰和高分辨率的迁移图像，降低了错误解释的风险。并设计级联模型和数据驱动的多重消除应用程序。上述技术的最佳组合产生了更清晰和高分辨率的迁移图像，降低了错误解释的风险。并设计级联模型和数据驱动的多重消除应用程序。上述技术的最佳组合产生了更清晰和高分辨率的迁移图像，降低了错误解释的风险。