Tj. Vanderwalt et al., THE ESTIMATION OF KINEMATIC VISCOSITY OF PETROLEUM CRUDE OILS AND FRACTIONS WITH A NEURAL-NET, Chemical engineering journal and the biochemical engineering journal, 51(3), 1993, pp. 151-158
This paper illustrates how a neural net, a three-layered Perceptron, c
an be trained to estimate viscosities for undefined crude oils and fra
ctions. Three Saudi-Arabian crude oils were employed to illustrate the
use of the neural net to approximate the relation in a very simple ma
nner with no need for a priori knowledge of the system. This empirical
correlation was accurate to 98.74% if tested on experimental data not
used during training, which is a fivefold improvement on average resu
lts obtained by two recently-proposed equations to estimate the viscos
ity of hydrocarbons. Although the neural net equation seems to be less
transparent than former correlations, a method called backward analys
is is proposed to analyze the weight matrix of the neural net in order
to gain valuable insight into the viscosity system.