新疆石油地质 ›› 2002, Vol. 23 ›› Issue (5): 429-431.

• 应用技术 • 上一篇    下一篇

极值方差聚类法在测井分层取值中的应用——以莫北油田莫005井区为例

张明玉   

  1. 中国石油 新疆油田分公司 勘探处,新疆 克拉玛依 834000
  • 收稿日期:2002-04-08 修回日期:2002-06-25 出版日期:2002-10-01 发布日期:2020-08-11
  • 作者简介:张明玉(1962-),男,山东青岛人,高级工程师,油气勘探。联系电话:0990-6890157

Application of Minimax Variance Cluster Analysis Method in Well Log Layering Data Record—an example of Well Block Mo-005 in Mobei oilfield

ZHANG Ming-yu   

  • Received:2002-04-08 Revised:2002-06-25 Online:2002-10-01 Published:2020-08-11
  • About author:ZHANG Ming-yu (1962-), Male, Senior Engineer, Hydrocarbon Prospecting, Exploration Department, PetroChina Xinjiang Oil, Karamay, Xinjiang 834000, China

摘要: 在准噶尔盆地莫北油田莫005井区地质导向钻井中,采用极值方差聚类分析法,实现了对数字化测井曲线的自动分层取值。该方法首先是在数字化测井曲线上找出层间方差最大、层内方差最小的点作为分层点,同时考虑到上下围岩对薄层的屏蔽影响和测井曲线的波动性,对所有分层点按照深度值排成一组有序数组,然后用聚类分析法对其进行并界处理。更加突出了层间非均质差异性和层内均yi性,其结果与实际的岩性剖面分层十分吻合。而且,整个分层取值过程是基于上述理论方法采用VB(V6.0)语言编制的自动分层取值程序,由计算机自动完成。为砂泥岩剖面的自动测井相分析建立了一套有效的分层取值方法。

关键词: 极值方差聚类, 数字测井曲线, 自动分层取值

Abstract: In geologic orienting drilling in Well Block Mo-005 of Mobei oilfield in Junggar basin, minimax variance cluster method was applied, and automatic layering data record on digitalizing well logs had been realized. This method can be used to find out maximal and minimal points of interlayer variances on digitalizing well logs as layering points, and take account of screen effect of overlying and underlying surrounding rocks on thin sands or layers along with fluctuation of well log curves. All layering points are put in order as a set of ordinal numbers in terms of depth, followed by performing parallel processing with the method of cluster analysis. The results are very closed to real lithologic section zonation owing to its most distinct interlayer heterogeneity and inner-layer homogenization. The whole procedure of layering data record is automatically fulfilled on the basis of these method with VB (V6.0) program by computer. Such a method is suitable for auto-well logging phase analysis of sand-shale series.

Key words: minimax variance cluster analysis, digital well log curve, auto-layering data

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