Application of the artificial neural network to multivariate anomaly recognition in geochemical exploration for hydrocarbons

Geochemistry: Exploration, Environment, Analysis

Volumn 2, Issue 1, 2002, Pages 75-82

  Zhang, Liuping ^a   Bai, Guoping ^a  

^a CHINA UNIVERSITY OF PETROLEUM   (China)

Author keywords

Cluster analysis; Direct hydrocarbon indicators; Multivariate anomalies; Neural network

Indexed keywords

CLUSTER ANALYSIS; COMPUTER CIRCUITS; GASOLINE; GEOCHEMISTRY; HYDROCARBONS; MULTIVARIANT ANALYSIS; NEURAL NETWORKS; NORMAL DISTRIBUTION; PATTERN RECOGNITION; POPULATION STATISTICS; PROVEN RESERVES; SEEPAGE;

BACK-PROPAGATION ARTIFICIAL NEURAL NETWORK; DIRECT HYDROCARBON INDICATORS; GEOCHEMICAL CHARACTERISTIC; GEOCHEMICAL EXPLORATION; HYDROCARBON EXPLORATION; HYDROCARBON POTENTIAL; MULTIVARIATE ANOMALIES; MULTIVARIATE STATISTICAL ANALYSIS;

BACKPROPAGATION;

ARTIFICIAL NEURAL NETWORK; DATA PROCESSING; GEOCHEMICAL SURVEY; HYDROCARBON EXPLORATION;

EID: 0036488442     PISSN: 14677873     EISSN: None     Source Type: Journal    
DOI: 10.1144/1467-787302-008     Document Type: Article

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