Least-squares migration of incomplete reflection data

Tamas Nemeth*, Chengjun Wu, Gerard T. Schuster

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

884 Scopus citations


A least-squares migration algorithm is presented that reduces the migration artifacts arising from incomplete data. Instead of migrating data with the adjoint of the forward modeling operator, the normal equations are inverted by using a preconditioned linear conjugate gradient scheme that employs regularization. The modeling operator is constructed from an asymptotic acoustic integral equation, and its adjoint is the Kirchhoff migration operator. Numerical results show that the least-squares migrated sections are typically more focused than the corresponding Kirchhoff migrated sections and their reflectivity frequency distributions are closer to those of the true model frequency distribution.

Original languageEnglish (US)
Pages (from-to)208-221
Number of pages14
Issue number1
StatePublished - 1999
Externally publishedYes

ASJC Scopus subject areas

  • Geochemistry and Petrology


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