西南石油大学学报(自然科学版) ›› 2008, Vol. 30 ›› Issue (1): 51-53.DOI: 10.3863/j.issn.1000-2634.2008.01.014

• 地质勘探 • 上一篇    下一篇

小波分析在测井裂缝识别中的应用

高伟1 王允诚1 徐静2 伍国勇3 冯雪龙4   

  1. 1.“油气藏地质及开发工程”国家重点实验室·成都理工大学,四川 成都 610059;2.中国石油新疆石油管理局测井公司,新疆 克拉玛依 834000;3.中国石化江苏油田研究院,江苏 扬州 225000;4.中国石油玉门油田分公司勘探事业部,甘肃 酒泉 735000
  • 收稿日期:2006-11-27 修回日期:1900-01-01 出版日期:2008-02-20 发布日期:2008-02-20
  • 通讯作者: 高伟

Application of Wavelet Analysis in Recognizing Fractures by Logging

GAO Wei1 WANG Yun-cheng1 XU Jing2 WU Guo-yong3 FENG Xue-long4   

  1. 1.State Key Laboratory of Oil/Gas Reservoir Geology and Exploitation·Chengdu University of Technology,Chengdu Sichuan 610059,China;2.Xinjiang Petroleum Administration Bureau Logging Company,Karamay Xinjiang 834000,China;3.Jiangsu Oilfield Institute,Yangzhou Jiangsu 225000,China;4.Yumen Oilfield Branches Exploration Division,Jiuquan Gansu 735000,China
  • Received:2006-11-27 Revised:1900-01-01 Online:2008-02-20 Published:2008-02-20
  • Contact: GAO Wei

摘要: 针对井下裂缝发育层段识别的难点,提出了用小波分析的方法分解声波时差信号,使井下的岩性与微观结构特征信号、流体性质信号、裂缝响应信号和随机干扰信号互相分离,直接重构出反映裂缝发育的声波高频信号,从而避免许多声波低频信号的影响,正确识别裂缝发育情况。用同样的方法分解双侧向电阻率信号,重构出电阻率测井各个层段的低频信号,直观地反映深、浅侧向的差异情况,有效地识别裂缝发育层位。最后结合高频声波信号和低频电阻率信号,识别出裂缝发育层段。应用表明,该方法与岩芯观察有很好的一致性。

关键词: 小波分析, 裂缝识别, 测井信号, 信号分解, 信息重构

Abstract: Recognition of the fractures in the wells is a hard problem,the research submits the method of wavelet analysis to decompose the interval transit time information,which makes the microstructure characteristic signal,fluid characteristic signal,despondences of fractures and random disturbance signal separated from lithology,the high frequency signals reflecting fractures are directly reconstructed to avoid the influence of low frequency signal and recognize development of fractures correctly.Also,the same method is used to decompose the microelectrode log signals,reconstruct the low frequency signals that reflect the permeable layer.At last,combination of the high frequency signal of fractures and the low frequency signal of microelectrode log can help to recognize the layer of fracture development.Practice in oil gas field indicates the results from the method are consisting with the results coming from the core inspection.

Key words: wavelet analysis, fracture recognition, log signals, signal decomposition, signal reconstruction

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