海底节点高效混采海量数据分离技术

与陆上混采数据混叠干扰类型单一相比，由于海底节点（OBN）高效混采施工的特殊性，OBN高效混采数据中存在多种混叠干扰类型，其中非生产炮数量过多造成逻辑坐标系统下的重炮以及复杂海域导致的严重变观现象，是OBN高效混采资料中产生多种类型混叠干扰的两种主要原因。为此，通过分析OBN高效混采数据中混叠干扰类型，研究了迭代动态映射技术以及炮点逻辑坐标预处理、稀疏反演法的技术方案。选择基于FKK变换的稀疏反演法预测噪声的分离方法，同时以迭代的方式对所有重炮的逻辑位置进行全局动态映射预处理，高效识别多种混叠干扰，从而精准、快速地分离高混叠度的OBN海量地震数据。对A区OBN高效混采数据的分离结果表明，分离的单炮数据保真度高，在优化分离效率的前提下，取得了较理想的分离效果。

Deblending massive OBN data acquired by efficient and blended shooting method

Compared with land blended data with simple noises, OBN blended data have many types of noises due to the special method of OBN acquisition. Two primary causes for the multiple types of noises are heavy overlapped shots on the logical coordinate system and severe geometry deformation. After analyzing the types of noises in OBN data, we studied iterative dynamic mapping, pre-processing of logical shot coordinates and sparse inversion deblending technology. The sparse inversion deblending method is based on FKK. It globally maps the logical positions of all overlapped shots in a dynamic and iterative way to recongnize noises, and then it accurately and quickly deblends the massive seismic data severely blended. The application in Block A shows that the deblended OBN data are of high fidelity, indicating that the method can provide optimal results while improving deblending efficientcy.