Comparison of intelligent and statistical clustering approaches to predicting total organic carbon using intelligent systems

Journal of Petroleum Science and Engineering

Volumn 86-87, Issue , 2012, Pages 190-205

  Sfidari, Ebrahim ^a   Kadkhodaie Ilkhchi, Ali ^b   Najjari, Saeid ^c  

^a UNIVERSITY OF TEHRAN   (Iran)

^b UNIVERSITY OF TABRIZ   (Iran)

^c SHAHID CHAMRAN UNIVERSITY OF AHVAZ   (Iran)

Author keywords

Cluster analysis; Intelligent systems; K means clustering; Petrophysical data; SOM clustering; Total organic carbon

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; CLUSTER VALIDITY; CONVENTIONAL TECHNIQUES; DATA CLUSTERING; DATA SETS; ELECTROFACIES; GAS FIELDS; GAS RESERVOIR; HIERARCHICAL CLUSTER ANALYSIS; INTELLIGENT DATA; K-MEANS CLUSTERING; LITHOFACIES; LOG MEASUREMENT; PERSIAN GULF; PETROPHYSICAL; PREDICTION METHODS; SOM CLUSTERING; STATISTICAL CLUSTERING; TOTAL ORGANIC CARBON; TWO-STEP APPROACH; WELL LOG DATA;

CLASSIFICATION (OF INFORMATION); CLUSTERING ALGORITHMS; CONFORMAL MAPPING; FORECASTING; GAS INDUSTRY; HIERARCHICAL SYSTEMS; INTELLIGENT SYSTEMS; NEURAL NETWORKS; PETROLEUM RESERVOIRS; WELL LOGGING;

CLUSTER ANALYSIS;

ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; DATA SET; HIERARCHICAL SYSTEM; HYDROCARBON RESERVOIR; LITHOFACIES; TOTAL ORGANIC CARBON;

ARABIAN SEA; INDIAN OCEAN; PERSIAN GULF;

EID: 84860296302     PISSN: 09204105     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.petrol.2012.03.024     Document Type: Article

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