Data reconstruction with shot-profile least-squares migration
Data reconstruction with shot-profile least-squares migration
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DOI：
10.1190/1.3478375
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发表时间：
2010-12
期刊：
影响因子：
3.3
通讯作者：
S. Kaplan;M. Naghizadeh;M. Sacchi
中科院分区：
文献类型：
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作者：
S. Kaplan;M. Naghizadeh;M. Sacchi
我们介绍了短剖面迁移数据重建（SPDR）。SPDR利用弹廓迁移和反迁移算子构造最小二乘迁移弹集。为了提高效率，两种作业者都采用了恒定的运移速度模型，因此SPDR对底层地质信息的要求最低。将偏移算子应用于最小二乘偏移的弹片集，得到重构的数据集。SPDR可以从空间混叠的观测数据中重建镜头集合。在地球反射面近似模型中，考虑到地质倾角的约束条件，干扰普通射孔数据集的信号和混叠能量在偏移射孔数据集中是不相交的。在最小二乘迁移算法中，我们构建权重来利用这种分离，在保留信号的同时抑制混叠能量，并允许SPDR从混叠数据中重建拍摄集。用综合数据实例和一个实例说明了SPDR。
We introduce shot-profile migration data reconstruction (SPDR). SPDR constructs a least-squares migrated shot gather using shot-profile migration and demigration operators. Both operators are constructed with a constant migration velocity model for efficiency and so that SPDR requires minimal information about the underlying geology. Applying the demigration operator to the least-squares migrated shot gather gives the reconstructed data gather. SPDR can reconstruct a shot gather from observed data that are spatially aliased. Given a constraint on the geological dips in an approximate model of the earth’s reflector, signal and aliased energy that interfere in the common shot data gather are disjoint in the migrated shot gather. In the least-squares migration algorithm, we construct weights to take advantage of this separation, suppressing the aliased energy while retaining the signal, and allowing SPDR to reconstruct a shot gather from aliased data. SPDR is illustrated with synthetic data examples and one ...