石油与天然气地质 ›› 2011, Vol. 32 ›› Issue (5): 718-723.doi: 10.11743/ogg20110510

• 储层评价 • 上一篇    下一篇

基于谱分解技术的储层定量地震解释

边立恩, 于茜, 韩自军, 陈彬彬   

  1. 中海石油(中国)有限公司 天津分公司 勘探开发研究院,天津 300452
  • 收稿日期:2010-09-25 修回日期:2011-09-08 出版日期:2011-10-28 发布日期:2011-12-16
  • 作者简介:边立恩(1982-),男,助理工程师,地震资料解释与储层预测。

Quantitative seismic interpretation of reservoirs based on the spectral decomposition technique

Bian Li'en, Yu Qian, Han Zijun, Chen Binbin   

  1. Research Institute of Exploration and Development,CNOOC Tianjin Company,Tianjin 300452,China
  • Received:2010-09-25 Revised:2011-09-08 Online:2011-10-28 Published:2011-12-16

摘要:

谱分解技术是一项新的地震储层研究技术,它通过离散傅里叶变换或最大熵的方法将地震资料从时间域转换到频率域进行研究。根据地震波传播理论推导了薄层振幅谱的表达式,证实了薄层谱的频陷特性,即频陷周期的倒数等于薄层的时间厚度。并以此原理为基础,探讨了基于谱分解技术的储层厚度估算的研究思路和技术方法。在实际应用中,通过建立目的层精确的速度场分布和沿层调谐体中第一谱峰频率的求取来达到储层厚度的定量解释。应用实例表明,该方法预测的结果与实钻情况具有很高的吻合度,结果可信,为储层的定量地震解释提供了新的手段和方法,具有广阔的应用前景。

关键词: 调谐体, 速度场, 定量地震解释, 谱分解, 储层预测

Abstract:

Spectral decomposition is a new technique for seismic reservoir research that transforms seismic data from time domain to frequency domain by discrete Fourier transform or maximum entropy approach.According to the theory of seismic wave propagation,this paper deduces the amplitude spectrum expression of thin beds and confirms their notches characteristics of spectrum,i.e.the reciprocal of notches period equals to the temporal thickness of thin bed.With this principle,we discuss ideas and methods of estimating reservoir thickness based on spectral decomposition.In practice,quantitative interpretation of reservoir thickness is realized by establishing a precise velocity field of targets and computing the first spectral peak frequency in target tuning cube.The application shows that the prediction results are consistent with the drilling data,indicating they are credible.Spectral decomposition provides a new approach and method for quantitative seismic interpretation of reservoirs and has broad application prospects.

Key words: tuning cube, velocity field, quantitative seismic interpretation, spectral decomposition, reservoir prediction

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