| Autor: |
Alan Schiemenz, Richard Coates, K. Jiao |
| Rok vydání: |
2014 |
| Předmět: |
|
| Zdroj: |
Proceedings. |
| ISSN: |
2214-4609 |
| DOI: |
10.3997/2214-4609.20140714 |
| Popis: |
Full Waveform Inversion (FWI) has recently emerged as a promising method for refining seismic velocity models to achieve enhanced imaging. The algorithm involves iteratively updating the velocity model to improve the match between the recorded seismic data and the simulated waveforms. Each iteration typically requires multiple wavefield extrapolations. As a result the technique places significant computational burdens on even the largest computers when applied to large three-dimensional surface seismic datasets. This paper discusses the application of two statistical sampling strategies to a time-domain FWI algorithm, with the aim of minimizing the computation costs while still ensuring that all the information in the data is utilized. Results are shown for a synthetic model and for a real data set acquired with a multi-vessel coil geometry, both of which show significant computational savings. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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