The prediction of the compressibility factor of sour and natural gas by an artificial neural network system

Petroleum Science and Technology

Volumn 29, Issue 4, 2011, Pages 325-336

  Al Anazi, B Duraya ^a   Pazuki, G R ^b   Nikookar, M ^c   Al Anazi, A Fannoush ^d  

^a KING ABDULAZIZ CITY FOR SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^b MALEK ASHTAR UNIVERSITY OF TECHNOLOGY   (Iran)

^c IOR Research Institute   (Iran)

^d SAUDI ARAMCO   (Saudi Arabia)

Author keywords

artificial neural network; compressibility factor; natural gas; sour gas

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AVERAGE ABSOLUTE DEVIATION; COMPRESSIBILITY FACTOR; EXPERIMENTAL CORRELATION; EXPERIMENTAL DATA; FEED-FORWARD ARTIFICIAL NEURAL NETWORKS; MODEL VALIDITY; PENG-ROBINSON; REDLICH-KWONG; ROBINSON; ROOT MEAN SQUARE ERRORS; SHELL OIL; STATISTICAL CRITERION; THREE-LAYER; VAN DER WAALS;

BINARY MIXTURES; EQUATIONS OF STATE; GASES; NETWORK LAYERS; NEURAL NETWORKS; SOUR GAS; VAN DER WAALS FORCES;

COMPRESSIBILITY OF GASES;

EID: 78751543551     PISSN: 10916466     EISSN: 15322459     Source Type: Journal    
DOI: 10.1080/10916460903330080     Document Type: Article

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