The Application of an Artificial Neural Network (ANN) and a Genetic Programming Neural Network (GPNN) for the Modeling of Experimental Data of Slim Tube Permeability Reduction by Asphaltene Precipitation in Iranian Crude Oil Reservoirs-Reference-Cited by-同舟云学术

The Application of an Artificial Neural Network (ANN) and a Genetic Programming Neural Network (GPNN) for the Modeling of Experimental Data of Slim Tube Permeability Reduction by Asphaltene Precipitation in Iranian Crude Oil Reservoirs

Published:2012-12 Issue:23 Volume:30 Page:2450-2459
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Manshad A. Khaksar,Manshad M. Khaksar,Ashoori S.

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

http://www.tandfonline.com/doi/pdf/10.1080/10916466.2010.519749

Reference9 articles.

1. Akbari, M. and Jalali, F. Dew point pressure estimation of gas condensate reservoirs, using artificial neural network (ANN). EUROPEC/EAGE Conference and Exhibition. June11–14, London, England. SPE 107032

2. The Effect of Asphaltene Precipitation on Carbonate-Rock Permeability: An Experimental and Numerical Approach

3. Ph.D. Thesis;Ashoori S.,2003

4. Civan, F. Modeling and simulation of formation damage by organic deposition. First International Symposium on Colloid Chemistry in Oil Production: Asphaltenes and Wax Deposition, ISCOP 1995. November26–29, Rio de Janeiro, Brazil. pp.102–107.

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