• Title/Summary/Keyword: Electrofacies

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AUTOMATED ELECTROFACIES DETERMINATION USING MULTIVARIATE STATISTICAL ANALYSIS

  • Kim Jungwhan;Lim Jong-Se
    • 한국석유지질학회:학술대회논문집
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    • spring
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    • pp.10-14
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    • 1998
  • A systematic methodology is developed for the electrofacies determination from wireline log data using multivariate statistical analysis. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the efficiency and quality of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification matches well to the core and the cutting data with high reliability This methodology for electrofacies classification can be used to define the reservoir characteristics which are helpful to the reservoir management.

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Automatic Electrofacies Classification from Well Logs Using Multivariate Statistical Techniques (다변량 통계 기법을 이용한 물리검층 자료로부터의 암석물리학상 결정)

  • Lim Jong-Se;Kim Jungwhan;Kang Joo-Myung
    • Geophysics and Geophysical Exploration
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    • v.1 no.3
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    • pp.170-175
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    • 1998
  • A systematic methodology is developed for the prediction of the lithology using electrofacies classification from wireline log data. Multivariate statistical techniques are adopted to segment well log measurements and group the segments into electrofacies types. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the quality and efficiency of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification works well with reliability to the core and cutting data. This methodology for electrofacies determination can be used to define reservoir characterization which is helpful to the reservoir management.

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