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Abstract

Summary

Time migration is an attractive tool to produce subsurface images because it is very fast, less sensitive to the model errors than depth migration and, usually, massively parallelized technique. However, the time-migration operator is derived by considering many assumptions, among others a straight ray propagation, regularly sampled seismic data and infinite migration aperture which frequently results in deteriorated images. Least-squares techniques can also be applied within the time-migration framework to tackle the imaging problems. As migration/demigration strongly depends on the velocity model, we first apply an iterative time-migration model building based on kinematic wavefield attributes and a thresholding approach followed by interpolation and smoothing. In this paper, we investigate three least-squares time-migration methods: the conventional approach using conjugate gradient (L-BFGS) optimization, a single-iteration approach using Hessian filter and CRS data conditioning, an iterative approach using preconditioning by diffraction correlation matrix. All least-squares methods lead to an enhancement of the image resolution and mitigating migration artifacts.

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/content/papers/10.3997/2214-4609.201803062
2018-11-27
2024-04-23

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Applying Least-Squares Migration Methods in Time Imaging: Marine and Land Data Example
Conference Proceedings 2018, 1 (2018); https://doi.org/10.3997/2214-4609.201803062
/content/papers/10.3997/2214-4609.201803062
/content/papers/10.3997/2214-4609.201803062
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