The
aim
of
my
MASc
study
was
to
design
an
Artificial
Neural
Network
(ANN)
trained
on
data
set
to
cover
a
wide
operating
range
of
all
parameters
affecting
the
demulsifier
dosage
in
a
desalting
process
for
crude oil
operations.
This
network
will
be
used
to
work
as
a
black
box
model
inside
the
controller
in
which
all
affecting
parameters
are
inputs
and
the
demulsifier
dosage
is
the
controller’s
output.
Testing
this
control
scheme
showed
an
effective
reduction
in
demulsifier
consumption
rate
compared
to
existing
methods.
The
results
also
showed
that
the
existing
control
strategy
is
highly
conservative
to
prevent
the
salt
from
exceeding
the
limit.
The
generated
function
from
the
ANN
was
also
used
to
optimize
the
amount
of
fresh
water
added
to
wash
the
salty
crude
oil.
Further,
an
ANN
model
was
developed
in
this
research
to
generate
an
online
estimate
of
the
salt
content
in
the
produced
oil.
Thesis: Modeling
and
Optimization
of
Desalting
Process
in
Oil
Industry (PDF)
