新疆石油地质

新疆石油地质 ›› 2002, Vol. 23 ›› Issue (4): 311-313.

• 油气勘探 • 上一篇    下一篇

商河油田沙二下油藏岩石物理相及测井评价

赵彦超1, 李丽1, 王希明2, 熊敏2   

  1. 1.中国地质大学资源学院,湖北 武汉 430074;
    2.中国石油 胜利油田公司临盘采油厂,山东 东营 257000
  • 收稿日期:2001-12-18 出版日期:2002-08-01 发布日期:2020-08-10
  • 作者简介:赵彦超(1961-), 男,湖北武汉人,副教授,主要从事油藏描述及剩余油分布、测井地质学的教学及科研工作。联系电话：027-87482427

The Petrophysical Facies and Its Well Logging Evaluation of Lower Sha-2 Reservoir in ShangHe Oilfield

ZHAO Yan-chao, LI Li, WANG Xi-ming, XIONG Min   

  • Received:2001-12-18 Online:2002-08-01 Published:2020-08-10
  • About author:ZHAO Y an-chao (1974-), Male, Associate Profesor, Petroleum Geology, Resource Institute, China University of Geoscience, Wuhan, Hubei 430074, China

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摘要： 应用流动带指标与主成分判别分析相结合的方法,在对商河油田商一区沙二下油藏的岩心资料进行详细的沉积学及成岩作用研究基础上,划分了四类岩石物理相类型。利用人工神经网络(BP)模型对该层位的物性进行预测,计算了流动带指标IFZ,并讨论了岩石物理相的展布及控制因素。研究表明,利用测井资料评价岩石物理相是储集层评

关键词: 商河油田, 岩石物理相, 测井, 评价, 神经网络

Abstract: By applying integrative approach of indicator flow zone (12) with principal component discriminating analysis, the core data from Lower Sha-2 reservoir in District Shang-1, ShangHe oilfield are elaborated in sedimentology and diagenesis, and based on which four types of the petrophysical facies are classified. Al- so, its petrophysical properties of this horizon are predicted using artificial neural network model (BP)， its IFZ is calculated and distribution and controlling factors of the petrophysical facies are discussed. Study shows that using well log data for appraisal of petrophysical facies is one of an important tool to evaluate reservoir quality.

Key words: ShangHe oilfield, petrophysical facies, well logging, evaluation, artificial neural network

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