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Petroleum Science >2021,??lssue 3:??- DOI: https://doi.org/10.1007/s12182-021-00557-y

Local events-based fast RTM surface-offset gathers via dip-guided interpolation Open?Access

文章信息

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作者：Yang Zhao, Feng-Lin Niu, Lei Fu, Cheng Cheng, Jin-Hong Chen & Shou-Dong Huo
作者單位：

Affiliations

  1. State Key Laboratory of Petroleum Resources and Prospecting, Unconventional Petroleum Research Institute, China University of Petroleum, Beijing 100083, China

    Yang Zhao

  2. Department of Earth, Environmental and Planetary Sciences, Rice University, Houston, TX, USA

    Feng-Lin Niu & Lei Fu

  3. Department of Earth and Planetary Science, University of California, Berkeley, CA, USA

    Cheng Cheng

  4. Aramco Research Center, Aramco Services Company, Houston, TX, USA

    Jin-Hong Chen

  5. Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China

    Shou-Dong Huo

Corresponding author

Correspondence to Yang Zhao.


投稿時間：2021-3-30
引用方式：Zhao, Y., Niu, FL., Fu, L. et al. Local events-based fast RTM surface-offset gathers via dip-guided interpolation. Pet. Sci. (2021). https://doi.org/10.1007/s12182-021-00557-y

文章摘要

Reverse Time Migration (RTM) Surface Offset Gathers (SOGs) are demonstrated to deliver more superior residual dip information than ray-based approaches. It appears more powerful in complex geological settings, such as salt areas. Still, the computational cost of constructing RTM SOGs is a big challenge in applying it to 3D field data. To tackle this challenge, we propose a novel method using dips of local events as a guide for RTM gather interpolation. The residual-dip information of the SOGs is created by connecting local events from depth-domain to time-domain via ray tracing. The proposed method is validated by a synthetic experiment and a field example. It mitigates the computational cost by an order of magnitude while producing comparable results as fully computed RTM SOGs.

關(guān)鍵詞

    Surface-offset gathers ；Reverse-time migration ；Dip-guided interpolation ；Reduced costs ；Local-event raytracing