计算机应用 ›› 2014, Vol. 34 ›› Issue (3): 911-914.DOI: 10.11772/j.issn.1001-9081.2014.03.0911

• 行业与领域应用 • 上一篇    下一篇

基于差分进化的感应测井反演算法

熊杰1,2,邹长春3   

  1. 1. 长江大学 电子信息学院,湖北 荆州434023;
    2. 长江大学 石油工业模型与计算技术研究所,湖北 荆州434023;
    3. 中国地质大学 地球物理与信息技术学院,北京100083
  • 收稿日期:2013-08-13 修回日期:2013-10-09 出版日期:2014-03-01 发布日期:2014-04-01
  • 通讯作者: 熊杰
  • 作者简介:熊杰(1975-),男,湖北荆州人,副教授,博士,主要研究方向:地球物理正反演理论、智能算法;邹长春(1969-),男,江西宜春人,教授,博士生导师,主要研究方向:地球物理测井、岩石物理。
  • 基金资助:

    国家自然科学基金资助项目;湖北省教育厅科技项目

Induction logging inversion algorithm based on differential evolution

XIONG Jie1,2,ZOU Changchun3   

  1. 1. Institute of Modeling and Computing Technology of Petroleum Industry, Yangtze University, Jingzhou Hubei 434023, China;
    2. School of Electronics and Information, Yangtze University, Jingzhou Hubei 434023, China;
    3. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China
  • Received:2013-08-13 Revised:2013-10-09 Online:2014-03-01 Published:2014-04-01
  • Contact: XIONG Jie
  • Supported by:

    National Natural Science Foundation

摘要:

针对传统感应测井线性迭代反演受初始模型影响的问题,提出一种全局寻优的差分进化感应测井非线性反演算法。利用该反演算法对不同厚度二维轴对称地层模型进行反演研究,在无噪声情况下,反演结果和模型基本一致;在叠加5%,10%和15%随机噪声后,对厚储层反演结果良好,对薄储层反演结果稍差。数值实验结果表明,该反演算法具有很好的全局寻优和抗噪声能力,能有效解决感应测井传统迭代反演对初始模型依赖的问题。

关键词: 差分进化算法, 感应测井, 非线性反演, 抗噪性

Abstract:

An induction logging inversion algorithm based on the Differential Evolution (DE) was proposed to avoid the dependency of initial model. This inversion algorithm was applied to induction logging inversion on the 2-D axisymmetric models of different thickness layers, and yielded consistent results with the models in the noise-free case. When noises of 5%, 10% and 15% were added, the inversion results of thick reservoir remain fairly good but the results of thin reservoir became slightly inferior. The numerical experimental results demonstrate that the proposed inversion algorithm has the capabilities of global optimization and anti-noise. It is more independent of initial model than the traditional ones.

Key words: Differential evolution algorithm, induction logging, nonlinear inversion, anti-noise performance

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