新疆石油地质 ›› 2025, Vol. 46 ›› Issue (1): 97-104.doi: 10.7657/XJPG20250112

• 应用技术 • 上一篇    下一篇

一种优化深度域速度反演的方法

李继伟1(), 李光鹏1, 杜佳骏1, 冯荣昌1, 段晓旭2   

  1. 1.中国石油集团 东方地球物理勘探有限责任公司 西南物探研究院,成都 610000
    2.广东省海洋地质调查院,广州 510080
  • 收稿日期:2024-02-20 修回日期:2024-05-22 出版日期:2025-02-01 发布日期:2025-01-24
  • 作者简介:李继伟(1992-),男,重庆人,工程师,石油物探,(Tel)028-85762648(Email)1026639387@qq.com
  • 基金资助:
    中国石油集团东方地球物理勘探有限责任公司科研课题(01-01-2021)

A Method for Optimizing Depth Domain Velocity Inversion

LI Jiwei1(), LI Guangpeng1, DU Jiajun1, FENG Rongchang1, DUAN Xiaoxu2   

  1. 1. Southwest Geophysical Research Institute, BGP Inc., CNPC, Chengdu, Sichuan 610000, China
    2. Guangdong Marine Geological Survey Institute, Guangzhou, Guangdong 510080, China
  • Received:2024-02-20 Revised:2024-05-22 Online:2025-02-01 Published:2025-01-24

摘要:

山前带地震资料信噪比低,剩余速度场拾取困难,深度域速度场难以迭代收敛到最优,是山前带地震资料无法实现偏移准确归位的主要原因。利用五维数据规则化中的数据插值技术对偏移前的原始共中心点道集进行数据重构,通过改变观测系统,改善其面元属性,提高地震资料信噪比,以满足叠前深度偏移速度场迭代的需求。同时为了保证偏移数据的保真性,数据插值得到的高信噪比共中心点道集仅作为深度域速度场迭代反演的输入道集,原始共中心点道集作为最终叠前深度偏移成像的输入道集,在此基础上,实现了深度域速度场迭代的快速准确收敛。实际资料应用表明,该方法可行性强,迭代更新求取的最终偏移速度场准确,偏移剖面反射归位合理,可为山前带叠前深度偏移速度建模提供借鉴。

关键词: 山前带, 地震资料处理, 五维数据规则化, 数据插值, 共中心点道集, 深度域速度反演, 叠前深度偏移

Abstract:

Seismic data from piedmont areas typically suffers from low signal-to-noise ratio (SNR), making it challenging to pick residual velocity fields and causing difficulties in iterative convergence of the depth domain velocity field to its optimal value. All these factors impede accurate migration and imaging of the seismic data from piedmont areas. By using the interpolation techniques in five-dimensional data regularization, the data from the original common midpoint (CMP) gathers prior to migration were reconstructed. By altering observation system, the bin attributes were enhanced to improve the SNR of the seismic data for iterative inversion of the pre-stack depth migration (PSDM) velocity field. To ensure the fidelity of the migrated data, the high-SNR CMP gathers obtained from data interpolation were used solely as inputs for the iterative inversion of the depth domain velocity field, while the original CMP gathers were preserved for the final PSDM imaging. This method enables fast and accurate iterative convergence of the depth domain velocity field. The actual application demonstrates that the method is highly feasible, and yields accurate final migrated velocity field through iterative updates and well-aligned reflections of migrated seismic profiles. This method provides a valuable reference for PSDM velocity modeling in the piedmont areas.

Key words: piedmont, seismic data processing, five-dimensional data regularization, data interpolation, CMP gather, depth domain velocity inversion, PSDM

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