Hybrid computational models for the characterization of oil and gas reservoirs

Expert Systems with Applications

Volumn 37, Issue 7, 2010, Pages 5353-5363

  Helmy, Tarek ^a   Fatai, Anifowose ^a   Faisal, Kanaan ^a  

^a KING FAHD UNIVERSITY OF PETROLEUM AND MINERALS   (Saudi Arabia)

Author keywords

Functional Networks; Fuzzy Logic; Hybrid computational intelligence; Petroleum reservoir characteristics; Support Vector Machines

Indexed keywords

COMPUTATIONAL INTELLIGENCE; COMPUTATIONAL INTELLIGENCE TECHNIQUES; CORRELATION COEFFICIENT; DATA SETS; EXECUTION TIME; FUNCTIONAL APPROXIMATION; FUNCTIONAL NETWORK; FUNCTIONAL NETWORKS; HIGH-ACCURACY; HIGHER-DIMENSIONAL; HYBRID COMPUTATIONAL INTELLIGENCE; HYBRID COMPUTATIONAL MODEL; HYBRID MODEL; INDIVIDUAL COMPONENTS; INFERENCE RULES; INPUT DATAS; LEAST-SQUARE FITTING; OIL AND GAS; OIL AND GAS RESERVOIR; PERFORMANCE INDICES; PREDICTOR VARIABLES; RESERVOIR CHARACTERIZATION; ROBUST MODELS; SIMULATION RESULT; TRAINING AND TESTING; TYPE-2 FUZZY LOGIC; TYPE-2 FUZZY LOGIC SYSTEM;

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL EFFICIENCY; ENERGY RESOURCES; FORECASTING; FUZZY INFERENCE; FUZZY SYSTEMS; HYBRID SENSORS; MECHANICAL PERMEABILITY; MINING ENGINEERING; MODELS; PETROLEUM DEPOSITS; PETROLEUM PROSPECTING; RESERVOIR MANAGEMENT; SUPPORT VECTOR MACHINES; ULTRAHIGH MOLECULAR WEIGHT POLYETHYLENES; VECTOR SPACES; VECTORS; WELL LOGGING;

PETROLEUM RESERVOIR ENGINEERING;

EID: 77950300963     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.01.021     Document Type: Article

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