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https://doi.org/10.5194/se-2019-37
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-2019-37
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Mar 2019

11 Mar 2019

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This preprint has been retracted.

An adaptive unstructured mesh based solution to topography least-squares reverse-time imaging

Qiancheng Liu1 and Jianfeng Zhang2 Qiancheng Liu and Jianfeng Zhang
  • 1Department of Physical Sciences and Engineering, King Abdullah University of Science and Technology
  • 2Institute of Geology and Geophysics, Chinese Academy of Sciences

Abstract. Least-squares reverse-time migration (LSRTM) attempts to invert for the broadband-wavenumber reflectivity image by minimizing the residual between observed and predicted seismograms via linearized inversion. However, rugged topography poses a challenge in front of LSRTM. To tackle this issue, we present an unstructured mesh-based solution to topography LSRTM. As to the forward/adjoint modeling operators in LSRTM, we take a so-called unstructured mesh-based “grid method”. Before solving the two-way wave equation with the grid method, we prepare for it a velocity-adaptive unstructured mesh using a Delaunay Triangulation plus Centroidal Voronoi Tessellation (DT-CVT) algorithm. The rugged topography acts as constraint boundaries during mesh generation. Then, by using the adjoint method, we put the observed seismograms to the receivers on the topography for backward propagation to produce the gradient through the cross-correlation imaging condition. We seek the inverted image using the conjugate gradient method during linearized inversion to linearly reduce the data misfit function. Through the 2D SEG Foothill synthetic dataset, we see that our method can handle the LSRTM from rugged topography.

This preprint has been retracted.

Qiancheng Liu and Jianfeng Zhang

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Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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  • RC1: 'review', Tristan van Leeuwen, 22 Mar 2019 Printer-friendly Version
  • RC2: 'review', Anonymous Referee #2, 14 Apr 2019 Printer-friendly Version

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
  • RC1: 'review', Tristan van Leeuwen, 22 Mar 2019 Printer-friendly Version
  • RC2: 'review', Anonymous Referee #2, 14 Apr 2019 Printer-friendly Version

Qiancheng Liu and Jianfeng Zhang

Qiancheng Liu and Jianfeng Zhang

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