Automatic recognition of oil reservoir models from well testing data by using multi-layer perceptron networks

Journal of Petroleum Science and Engineering

Volumn 77, Issue 3-4, 2011, Pages 254-262

  Vaferi, Behzad ^a   Eslamloueyan, Reza ^a   Ayatollahi, Shahab ^a  

^a SHIRAZ UNIVERSITY   (Iran)

Author keywords

Artificial neural networks; Reservoir model recognition; Well testing data

Indexed keywords

ANALYTICAL SOLUTIONS; ARTIFICIAL NEURAL NETWORK; AUTOMATIC RECOGNITION; BOTTOMHOLE; CONSTANT PRESSURES; CPU TIME; DATA SETS; DUAL-POROSITY RESERVOIRS; FAULT BOUNDARY; FIELD DATA; FLOW DISTURBANCES; HETEROGENEOUS MEDIA; HIDDEN LAYERS; HYDROCARBON RESERVOIR; MEAN RELATIVE ERROR; MULTI LAYER PERCEPTRON; MULTI-LAYER PERCEPTRON NETWORKS; OIL RESERVOIRS; RESERVOIR CHARACTERIZATION; RESERVOIR MODEL RECOGNITION; RESERVOIR MODELS; RESERVOIR PARAMETERS; SCALED CONJUGATE GRADIENTS; TEST DATA; TESTING METHOD; TESTING TECHNIQUE; TRAINING ALGORITHMS; TWO LAYERS; TWO STAGE;

CONJUGATE GRADIENT METHOD; ERRORS; HYDROCARBONS; LEARNING ALGORITHMS; NETWORK LAYERS; OIL WELL TESTING; PARAMETER ESTIMATION; PETROLEUM RESERVOIR ENGINEERING; PETROLEUM RESERVOIRS;

NEURAL NETWORKS;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; DATA SET; HYDROCARBON RESERVOIR; POROSITY; RESERVOIR CHARACTERIZATION; WELL TESTING;

EID: 79957443608     PISSN: 09204105     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.petrol.2011.03.002     Document Type: Article

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