Possibilistic c-Means for considering of Neutron and Density Porosity

被引:0
|
作者
Koohani, P. Nouri [1 ]
Zarandi, M. H. Fazel [1 ]
Seifipour, N. [2 ]
机构
[1] Amirkabir Univ Technol, Dept Ind Engn, POB 15875-4413, Tehran, Iran
[2] Amirkabir Univ Technol, Dept Inhibitor, Tehran, Iran
关键词
Gamma Ray; Log; porosity; Possibilistic C-Means clustering; Resistivity;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Petro physical parameters are important for predicting capacity of reservoir so, many modern oil and gas wells are drilled directly. Based on measuring these parameters, logging operations is done to achieve a complete log of every well. In some cases a complete set of data with minimum error of logs is achieved, but for various reasons such as failure to complete the logging of old wells logs are incomplete or inadequate, so getting complete set of data is too hard or impossible. Density and Neutron porosity are two of the important results of logging. As a result in this study these two parameters have been considered by Possibilistic C-Means clustering to evaluate its range. Gamma ray, Deep resistivity and sonic log are used for inputs.
引用
收藏
页数:5
相关论文
共 50 条
  • [21] A Possibilistic Multivariate Fuzzy c-Means Clustering Algorithm
    Himmelspach, Ludmila
    Conrad, Stefan
    SCALABLE UNCERTAINTY MANAGEMENT, SUM 2016, 2016, 9858 : 338 - 344
  • [22] Generalized Adaptive Possibilistic C-Means Clustering Algorithm
    Xenaki, Spyridoula
    Koutroumbas, Konstantinos
    Rontogiannis, Athanasios
    10TH HELLENIC CONFERENCE ON ARTIFICIAL INTELLIGENCE (SETN 2018), 2018,
  • [23] Relational and Median Variants of Possibilistic Fuzzy C-Means
    Geweniger, Tina
    Villmann, Thomas
    2017 12TH INTERNATIONAL WORKSHOP ON SELF-ORGANIZING MAPS AND LEARNING VECTOR QUANTIZATION, CLUSTERING AND DATA VISUALIZATION (WSOM), 2017, : 234 - 240
  • [24] Possibilistic C-means Algorithm Based on Collaborative Optimization
    Zang, Jing
    Li, Chenghua
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGY (CSAIT 2013), 2014, 255 : 587 - 593
  • [25] An enhanced possibilistic C-Means clustering algorithm EPCM
    Zhenping Xie
    Shitong Wang
    F. L. Chung
    Soft Computing, 2008, 12 : 593 - 611
  • [26] A Weight Possibilistic Fuzzy C-Means Clustering Algorithm
    Chen, Jiashun
    Zhang, Hao
    Pi, Dechang
    Kantardzic, Mehmed
    Yin, Qi
    Liu, Xin
    SCIENTIFIC PROGRAMMING, 2021, 2021
  • [27] Robust Fuzzy-Possibilistic C-Means Algorithm
    Zhou Yong
    Li Yue'e
    Xia Shixiong
    2008 INTERNATIONAL SYMPOSIUM ON INTELLIGENT INFORMATION TECHNOLOGY APPLICATION, VOL I, PROCEEDINGS, 2008, : 669 - 673
  • [28] Continuous biometric authentication using Possibilistic C-Means
    Batista dos Santos, Matheus Magalhaes
    Segundo, Mauricio Pamplona
    2018 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2018,
  • [29] A Relational Dual of the Fuzzy Possibilistic c-Means Algorithm
    Sledge, Isaac
    Bezdek, James
    Havens, Timothy
    Keller, James
    2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010), 2010,
  • [30] Alternative fuzzy-possibilistic c-means clustering algorithm
    Wu, Xiao-Hong
    Wu, Bin
    Zhou, Jian-Jiang
    DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2007, 14 : 11 - 14