6/23/2025, 8:26:56 PM 星期一
Discriminant Analysis on Sticking Based on Pattern Recognition Theory
Author:
Affiliation:

The Exploration and Production of Shale Gas Chongqing Fuling, SINOPEC,SINOPEC Institute of Petroleum Engineering,The Exploration and Production of Shale Gas Chongqing Fuling, SINOPEC

Clc Number:

P634.8

  • Article
  • | |
  • Metrics
  • |
  • Reference [11]
  • |
  • Related [19]
  • |
  • Cited by [0]
  • | |
  • Comments
    Abstract:

    The Support Vector Machine (SVM), Bayes discriminant analysis and multiple regression analysis were used for diagnosis and prediction of sticking. The discriminant model of stick type was built based on pattern recognition theory. The calculation analysis on the sticking data of northeastern Sichuan was made, it was indicated that the misjudgment rate for discriminant result of SVM, Bayes discriminant analysis and multiple regression analysis was 1.92%, 11.52% and 61.54%. The accuracy of SVM recognition result was the highest, but its discriminant equation is complex and the contribution of each component to the result could not be intuitively seen; while the equation of multiple regression analysis is simple, which could intuitively show the close degree between each component and sticking, but the accuracy of recognition result was lower. The accuracy of Bayes discriminant analysis was between the above two, but the discriminant accuracy is closely related to the number of discriminant.

    Reference
    [1]边肇祺,张学工.模式识别(第二版)[M],北京:清华大学出版社,2007:32-51.
    [2]阎铁,毕雪亮,王长江.基于支持向量机和聚类分析理论的钻具失效分析方法[J].石油学报,2007,28(3):135-140
    [3]石广仁.支持向量机在多地质因素分析中的应用[J].石油学报,2008,29(2):195-199
    [4]李建军,丁正生,张海燕.常用判别分类方法分析[J].西安科技大学学报,2007,27(1):138-142
    [5]罗刚,艾志久,王其华,等.基于模糊数学卡钻事故安全评价体系研究[J].西南石油大学学报,2007,29(6):118-122
    [6]陈晖,沈小翠.卡钻事故诊断仿真系统研究[J].石油机械,2009,37(7):55-57.
    [7]张林强.井下卡钻分析及处理,海洋石油,2007,(9):112-116
    [8]Vapnik V N.The nature of statistical learning theory[M]. Translated by zhang xuegong.bejing: Tsinghua university press,2000:85-205.
    [9]严丽,王燕,范树平.多元回归分析方法预测川东北礁滩相储层产能[J].新疆石油天然气,2011,7(4):37-40
    [10]顾和元,侯国庆,吴占伟.基于动态贝叶斯网络的深水防喷器可靠性研究[J].石油机械,2013,41(3):36-39.
    [11]韦明辉,黄海龙,韦忠良,等.基于支持向量机的钻井风险实时预测方法[J].钻采工艺,2012,35(5):15-17
    Comments
    Comments
    分享到微博
    Submit
Get Citation
Share
Article Metrics
  • Abstract:962
  • PDF: 1063
  • HTML: 199
  • Cited by: 0
History
  • Received:February 11,2015
  • Revised:August 01,2015
  • Adopted:September 18,2015
  • Online: November 09,2015
Article QR Code