Improving water saturation estimation in a tight shaly sandstone reservoir using artificial neural network optimized by imperialist competitive algorithm - A case study

Journal of Petroleum Science and Engineering

Volumn 127, Issue , 2015, Pages 347-358

  Amiri, Morteza ^a   Ghiasi Freez, Javad ^b   Golkar, Behnam ^c   Hatampourd, Amir ^d  

^a UNIVERSITI TEKNOLOGI MALAYSIA   (Malaysia)

^b NATIONAL IRANIAN OIL COMPANY   (Iran)

^c PETROLEUM UNIVERSITY OF TECHNOLOGY   (Iran)

^d SHAHID BAHONAR UNIVERSITY OF KERMAN   (Iran)

Author keywords

Factor analysis; Imperialist competitive algorithm (ICA); Neural network; Principal component analysis; Tight gas sand (TGS); Water saturation determination

Indexed keywords

ALGORITHMS; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; COMPLEX NETWORKS; FACTOR ANALYSIS; HYDROCARBONS; LOW PERMEABILITY RESERVOIRS; NEURAL NETWORKS; OIL FIELD DEVELOPMENT; OIL FIELDS; OPTIMIZATION; PETROLEUM RESERVOIRS; PRINCIPAL COMPONENT ANALYSIS; TIGHT GAS; WELL LOGGING;

FEED-FORWARD BACK PROPAGATION; IMPERIALIST COMPETITIVE ALGORITHM (ICA); IMPERIALIST COMPETITIVE ALGORITHMS; LOW POROSITY AND PERMEABILITY; PETROPHYSICAL PARAMETERS; RESERVOIR CHARACTERIZATION; TIGHT GAS SANDS; WATER SATURATIONS;

PETROLEUM RESERVOIR ENGINEERING;

EID: 84925501009     PISSN: 09204105     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.petrol.2015.01.013     Document Type: Article

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