Quality control and optimization of partial-stack datasets in pre-stack seismic inversion
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摘要: 高质量的部分叠加道集数据是地震叠前反演的基础,然而不同偏移距叠加道集数据之间经常出现时间、振幅等不闭合现象,直接进行叠前反演则会影响反演弹性参数的可信度。因此,有必要对叠前反演道集进行质控及优化,以提高近、中、远偏移距道集的闭合效果。以残差准相关系数阈值为标准对部分叠加道集数据进行有限的调整,同时利用校正量统计图谱分析和递归插值的方法,对校正的时间偏移量和振幅缩放系数进行控制和优化,最终得到闭合效果较好的部分道集叠加数据体。实例表明使用校正及优化后的部分叠加道集数据进行反演能够显著提高叠前反演质量。Abstract: High quality partial-stack seismic data are the foundation of pre-stack inversion; however, the mis-tie and the phase displacement of partial-stack seismic datasets often lead to unconfident elastic parameters. It's very necessary for seismic datasets to control quality in order to improve the reliability of different offset gathers. In the paper, partial-stack seismic could be adjusted based on the standard of threshold value of residual quasi-correlation, and then seismic processing of phase correction and limited time shift would be executed based on the method of static graphs and recursive interpolate. The actual data inversion shows that under the responsible quality control, the partial-stack datasets correction processing could improve the inversion quality obviously.
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