ISSN 1004-4140
CN 11-3017/P
孔雪, 王德营, 张瑞香, 朱学娟, 胡秋媛. 曲波域不规则地震数据提高分辨率技术研究[J]. CT理论与应用研究, 2017, 26(6): 707-713. DOI: 10.15953/j.1004-4140.2017.26.06.06
引用本文: 孔雪, 王德营, 张瑞香, 朱学娟, 胡秋媛. 曲波域不规则地震数据提高分辨率技术研究[J]. CT理论与应用研究, 2017, 26(6): 707-713. DOI: 10.15953/j.1004-4140.2017.26.06.06
KONG Xue, WANG De-ying, ZHANG Rui-xiang, ZHU Xue-juan, HU Qiu-yuan. A Method for Enhancing Resolution of Irregular Seismic Data in Curvelet Domain[J]. CT Theory and Applications, 2017, 26(6): 707-713. DOI: 10.15953/j.1004-4140.2017.26.06.06
Citation: KONG Xue, WANG De-ying, ZHANG Rui-xiang, ZHU Xue-juan, HU Qiu-yuan. A Method for Enhancing Resolution of Irregular Seismic Data in Curvelet Domain[J]. CT Theory and Applications, 2017, 26(6): 707-713. DOI: 10.15953/j.1004-4140.2017.26.06.06

曲波域不规则地震数据提高分辨率技术研究

A Method for Enhancing Resolution of Irregular Seismic Data in Curvelet Domain

  • 摘要: 受野外观测条件的限制,采集的地震数据体通常不规则,并缺失一部分数据道。传统的单道提高分辨率方法无法兼顾横向地震信息,处理结果存在空间一致性问题。为此,本文提出在曲波域内进行不规则地震数据,通过曲波变换实现对地震数据的稀疏表征,将提高分辨率问题转化为曲波域1-范数约束的稀疏促进求解,得到规则化的高分辨率地震数据体。该方法避免传统单道提高分辨率方法存在的局限性,在提高分辨率的同时,能够恢复缺失的地震数据、压制随机噪声,进而提高地震数据的完备性,模型和实际资料试算,验证了该方法的正确性、有效性和适用性。

     

    Abstract: Considering the irregularity of seismic data and the limitation of traditional enhancing resolution method in single-channel seismic data, the problem of enhancing resolution is introduced into Curvelet domain and the method for enhancing resolution of irregular seismic data in curvelet domain is proposed. It utilizes the two-dimensional or high-dimensional support of curvelet basis function and the sparse representation of seismic data in curvelet domain, the problem of enhancing resolution of two-dimensional or high-dimensional seismic data is converted into the sparse promote solving with the constraint of L1-norm. Avoiding the problem of spatial consistency of the traditional enhancing resolution method, this method can enhancing the seismic resolution, suppressing random noise and restore the missing seismic traces, the completeness and resolution of seismic data are improved. Model and real data verify the correctness, validity and applicability of the method.

     

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