Marchenko Imaging From Rugged Topography in Mountainous Areas

• Published in: IEEE geoscience and remote sensing letters Vol. 21; pp. 1 - 5
• Main Authors: Chen, Xiaochun, Hu, Yezheng, Huang, Xuri, Chen, Kang, Peng, Haotian, Liu, Xiaobing, Chen, Kai
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Data acquisition; Datum (elevation); Deconvolution; Elevation; Elevation-static correction; Flat surfaces; Floating; floating datum; Focusing; Green's function; Green's function methods; Green's functions; Imaging; Imaging techniques; Iterative methods; Land acquisition; Marchenko imaging; Mountain regions; Mountainous areas; Mountains; Radio frequency; Receivers; rugged topography; Seismic data; Seismological data; Surface topography; Surfaces; Topography
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2023.3334221

Marchenko imaging has the particular ability to generate the subsurface image free of spurious artifacts related to internal multiples. However, conventional Marchenko imaging (C-MI) is performed based on the assumption that the sources and receivers of the recorded seismic data are placed on a flat surface, which is restrictive and hard to satisfy in mountainous areas with rugged topography. The elevation-static correction (or time shift) is a usual solution to ensure this assumption holds. But it only works well if the surface consistency is satisfied. To alleviate the limitations of C-MI in processing seismic data acquired from mountainous areas with rugged topography, we present a technique for conducting Marchenko imaging from a floating datum. The proposed Topography-Marchenko imaging (T-MI) is achieved by estimating an initial down-going focusing function between a floating datum and a focal point in the subsurface. In this work, we use seismic data corrected to a floating datum rather than a final datum as input to the iterative Marchenko scheme to retrieve Green's functions. The retrieved Marchenko Green's functions are further used to generate the subsurface image. The T-MI method can effectively avoid imaging distortions caused by the elevation-static correction. The proposed T-MI method is validated through applications to a synthetic model with rugged topography and a land dataset acquired from a mountainous area in Northwest Sichuan, China.