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    基于迭代光滑动态时间规整算法的共成像点道集优化叠加方法

    An optimized stacking method for common-image gathers based on iterative smooth dynamic time warping

    • 摘要: 当前,油气勘探对地震成像质量的要求日益提升,叠前偏移技术在地震数据处理中发挥着至关重要的作用。然而,利用偏移速度分析方法处理复杂地质构造时,往往难以精准重建速度模型,导致共成像点道集的同相轴发生弯曲,影响了叠加结果的成像精度。基于动态时间规整算法的地震数据叠加方法通过匹配参考地震道与其他地震道的相似性,校正同相轴的一致性,但当各地震道之间的幅值差异较大,或者地震数据信噪比较低时,该方法易出现错误匹配的情况,进而导致波形畸变,制约了其在道集校正中的应用效果。针对上述问题,提出了一种基于迭代光滑动态时间规整算法的道集叠加方法,引入平滑性约束和迭代策略对规整路径进行优化,提高了道集校正精度和同相轴一致性。特别是在复杂地质条件下,ISDTW算法取得了较好的成像效果。合成数据和实际数据的测试结果验证了ISDTW算法在减少局部匹配误差、提升地震成像质量方面的显著优势。

       

      Abstract: Prestack depth migration is crucial to seismic imaging. However, its application to complex structures is impeded by the limitations of migration velocity analysis. The inaccuracies in the reconstructed velocity model lead to curved events in common-image gathers, which consequently reduce the precision of stacking. Dynamic time warping (DTW) addresses curved event correction by matching the similarity between a reference trace and other traces. However, significant amplitude differences between traces or low signal-to-noise ratios can lead to mismatch, resulting in waveform distortion and poor trace alignment. To solve this problem, this paper proposes a new method based on the iterative smooth dynamic time warping (ISDTW) algorithm. This method introduces smoothness constraints and an iterative strategy to optimize the warping path and thereby enhances the accuracy and consistency of trace alignment. Especially under complex geological conditions, ISDTW demonstrates improved imaging performance. Synthetic and field data tests validate the notable advantages of ISDTW in reducing local matching errors and improving the quality of the stacked data.

       

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