دورية أكاديمية
Hybrid-Driven High-Resolution Prestack Seismic Inversion
| العنوان: | Hybrid-Driven High-Resolution Prestack Seismic Inversion |
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| المؤلفون: | Jian Zhang, Xiaoyan Zhao, Hui Sun, Jingye Li, Xiaohong Chen |
| المصدر: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 9448-9458 (2023) |
| بيانات النشر: | IEEE, 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Ocean engineering LCC:Geophysics. Cosmic physics |
| مصطلحات موضوعية: | Data-driven, model-driven, prestack inversion, reservoir characterization, Ocean engineering, TC1501-1800, Geophysics. Cosmic physics, QC801-809 |
| الوصف: | Prestack seismic inversion is considered among the most frequently utilized techniques for reservoir characterization. However, the resolution of the inverted parameters, such as P-, S-wave velocity, and density, is low due to the limited bandwidth and side-lobe interference of the seismic wavelet. To address this issue, a hybrid two-step strategy that combines data-driven and model-driven methods is proposed to enable higher resolution and accuracy of the inverted results. We first construct a three-layer fully connected network to implement the mapping of seismic data to reflection coefficients. The method does not require exact seismic wavelet to be known and intensive human-computer interaction. It estimates reflectivity based on the extracted features from training data, which gives more accurate results compared with traditional sparse inversion methods. Then, the model-driven method (i.e., amplitude variation with offset/angle inversion method) is adopted to reconstruct P-wave velocity, S-wave velocity, and density from the estimated reflection coefficients. The performance of the hybrid-driven strategy is checked using synthetic model and real data. The results indicate that the proposed method provides more accurate and higher resolution inversion results for seismic reservoir characterization. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 2151-1535 |
| العلاقة: | https://ieeexplore.ieee.org/document/10278412Test/; https://doaj.org/toc/2151-1535Test |
| DOI: | 10.1109/JSTARS.2023.3323696 |
| الوصول الحر: | https://doaj.org/article/e7b710108b1447aebc5ea563499dfe71Test |
| رقم الانضمام: | edsdoj.7b710108b1447aebc5ea563499dfe71 |
| قاعدة البيانات: | Directory of Open Access Journals |
| تدمد: | 21511535 |
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| DOI: | 10.1109/JSTARS.2023.3323696 |