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Abstract

Summary

We present a theory of Least-Squares Gaussian Beam Migration (LSGBM), which uses Gaussian beam propagator as the kernel of linearized forward modeling (demigration) and migration. Gaussian beam demigration relies on the calculation of the Green functions by a Gaussian-beam summation for the downward and upward wavefields. Actually, the adjoint operator of Gaussian beam demigration accounts for prestack depth migration by the cross-correlation imaging condition, and in the migration process, seismic traces are calculated one by one for each shot. Application of Gaussian beam demigration/migration algorithms to the least-squares migration scheme can optimally estimate a subsurface reflectivity. The proposed LSGBM is illustrated with a recorded data generated by Gaussian beam demigration for the Marmousi2 model. Numerical results show that LSGBM, compared to migration (adjoint) with Gaussian beams, produces images with more balanced amplitude, higher resolution and even fewer artifacts.

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/content/papers/10.3997/2214-4609.201412880
2015-06-01
2024-04-19

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Least-squares Gaussian Beam Migration
Conference Proceedings 2015, 1 (2015); https://doi.org/10.3997/2214-4609.201412880
/content/papers/10.3997/2214-4609.201412880
/content/papers/10.3997/2214-4609.201412880
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