1887
Volume 70, Issue 6
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Seismic reflectivity inversion using ‐norm regularization produces sparse solutions by applying an ‐norm constraint. The fast iterative shrinkage‐thresholding algorithm is one of the most effective methods to solve ‐norm regularized inversion problems. A large number of iterations are commonly required in the fast iterative shrinkage‐thresholding algorithm because its solution converges slowly towards the sparse solution. To improve its convergence rate, we introduce a modifying strategy for the traditional fast iterative shrinkage‐thresholding algorithm. When implementing the soft‐thresholding operator, the thresholding value is adaptively adjusted by assigning the reciprocal of the solution in the previous iteration as a weight to the thresholding value of the current iteration. In this way, small variables in the solution produce large coefficients applied to the thresholding value, which causes small variables to quickly converge to zero. The adaptive fast iterative shrinkage‐thresholding algorithm shows significantly improved computational efficiency and accuracy compared to the traditional fast iterative shrinkage‐thresholding algorithm. It produces good results for both numerical and field examples of ‐norm regularized seismic reflectivity inversion.

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2022-06-16
2022-06-27
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  • Article Type: Research Article
Keyword(s): Inversion; Resistivity
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