Prediction of Crude Oil Viscosity using Feed-Forward back-Propagation neural network (FFBPNN)

Prediction of Crude Oil Viscosity using Feed-Forward back-Propagation neural network (FFBPNN)

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Crude oil viscosity is an important governing parameter of fluid flow both in the porous media and in pipelines. So, estimating the oil viscosity at various operating conditions with accuracy is of utmost importance to petroleum engineers. Usually, oil viscosity is determined by laboratory measurements at reservoir temperature. However, laboratory experiments are rather expensive and in most...
 
Published at Petroleum & Coal, 54(2): 124-135
Published in 2012
 
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Makinde, F. A., Ako, C. T., Orodu, O. D. and Asuquo, I. U.
Orodu Oyinkepreye David » Oyinkepreye D. Orodu is a Professor of Petroleum Engineering and has varied Oil & Gas industry experience spanning field operations in pipeline integrity and academia. Preye holds a bachelor's degree in Chemical Engineering from the University of Port Harcourt; master's in Oil & Gas Engineering, the Robert Gordon University and a doctorate in Oil & Natural Gas Engineering, China University of... view full profile
Orodu Oyinkepreye David
 
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