4.7 Article

Enhancing Subsurface Scatters Using Reflection-Damped Plane-Wave Least-Squares Reverse Time Migration

期刊

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
卷 17, 期 4, 页码 706-710

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2019.2928061

关键词

Diffraction; Damping; Imaging; Inverse problems; Numerical models; Data models; Oils; Inverse problems; iteratively reweighted least-squares (IRLS); reverse time migration (RTM); seismic imaging; subsurface scatters

资金

  1. China Postdoctoral Science Foundation [2019M653650]
  2. Ministry of Science and Technology of China through the National Key Research and Development Program [2018YFC0603500, 2018YFC0603501, 2018YFC1504200]
  3. Major Research Plan of the National Natural Science Foundation of China [91730306]
  4. National Science and Technology Major Project of China [2016ZX05024-001-007, 2017ZX05069]

向作者/读者索取更多资源

Subsurface scatters are sometimes masked by reflectors in seismic migration images, because the diffractions are much weaker in energy than the reflections. We propose a novel imaging method, named reflection-damped plane-wave least-squares reverse time migration (RD_PLSRTM), to enhance the scatters in the migration image. We formulate seismic imaging as an inverse problem that minimizes a weighted residual between the modeled and observed seismic data. In the proposed approach, we use the plane-wave destruction filter to separate the diffractions from the reflections in the data residual. A reflection-damped weighting matrix is then used to govern the fitting of the diffractions and the reflections, and therefore emphasize the updates of the scatters. The inverse problem is finally solved by using an iteratively reweighted least-squares (IRLS) algorithm. The proposed method provides a generalized formulation that could be reduced to conventional PLSRTM and PLSRTM of diffractions (PLSRTM_D) by using specific damping factors. We conduct imaging tests on synthetic and field data that prove the superiority of the proposed method over PLSRTM in imaging deep scatters and subsalt scatters. Compared with PLSRTM_D, it could produce high-quality images of not only the scatters but also the reflectors.

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