| Autor: |
Sylvain Masclet, H. Prigent, V. Massart, T. Bardainne |
| Rok vydání: |
2019 |
| Předmět: |
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| Zdroj: |
81st EAGE Conference and Exhibition 2019. |
| DOI: |
10.3997/2214-4609.201900968 |
| Popis: |
Summary Shallow stratigraphy in Southern Oman is characterized by the presence of an anhydrite layer causing a strong velocity inversion which makes seismic imaging particularly difficult. This known shallow sharp velocity inversion cannot be easily captured with reflected wave-based techniques or even acoustic full waveform inversion. We propose to recover it by applying multi-wave inversion, an approach combining information from P wave first breaks and ground-roll dispersion curves. In addition, an unsupervised machine learning technique is used to improve the quality of surface wave dispersion curve picks, crucial for the reliability of the multi-wave inversion results. With this innovative approach, the joint inversion of first breaks and surface waves leads to a better high resolution P-wave velocity model of the near surface which enables improved deep imaging. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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