Hydrocarbon Processing - April 2021 - 32

Clean Fuels
the operating regimes that need
attention. The difference between
OWs and IOWs is the degree of
criticality and the required time
to respond to mitigate escalating
situations, including the triggering
of the emergency depressurization
system. FIG. 1 presents an
example of an IOW developed
and implemented by MOL, a
Hungarian energy company, in its
six HPI facilities. MOL developed
a portfolio of OWs and IOWs
based on industry standards and
the experience of its SMEs, and
by configuring associated OW
and IOW digital asset templates.
These templates are then put into
production across its facilities,
enabling changes to be propagated
quickly and efficiently.
2. Feed train fouling-Managing
polymerization and associated
gumming and fouling to
optimize asset performance

is another common, powerful
application of the operational
data infrastructurea, which allows
the configuration of asset health
indexes by SMEs to determine
the health of various assets,
such as pumps, exchangers,
heat tracing and valves. The
health indexes can then be used
to incorporate indicators of
possible issues, such as fouling
from polymerization in the
exchanger train or a drop in
pump efficiency. The health
index can be aggregated across
the PTU and/or the RDU to
roll up to a key performance
indicator (KPI) on the summary
dashboard, enabling drill-down
and diagnostic investigation.
Leading HPI companies are also
integrating the health index with
their maintenance management
systems (MMSs) to trigger work
orders and to link in metadata

FIG. 2. Example of use of the real-time operational data infrastructure for advanced CBM.2

FIG. 3. Example of a configured HTHA corrosion smart asset template.2

APRIL 2021 | HydrocarbonProcessing.com

found in the MMS, such as the
last maintenance date, spare parts
inventory, or manufacturer's make
and model information, which
are commonly used in the health
index calculation. FIG. 2 provides
an example of an advanced
condition-based maintenance
(ACBM) system created using
a data infrastructurea. MOL has
configured health indexes for
all its critical assets (such as all
rotating equipment, exchangers,
crucial valves and heaters),
and has integrated the indexes
with its MMS.
3. HTHA corrosion-As with
other HPI processes that
utilize high temperatures and
hydrogen in carbon alloy metal
environments, HTHA can occur,
leading to embrittlement and loss
of containment. FIG. 3 illustrates
MOL's use of an HTHA smart
asset template, and demonstrates
how a data infrastructurea can
address various corrosion regimes,
including HTHA, carbonic acid
and others. The template uses
a table lookup for the regressed
coefficients from the Nelson
curve, which provides correlation
of hydrogen and temperatures
with various carbon steel alloys
to determine when an alloy node
is approaching or has entered an
HTHA regime. The start and end
of this event can be configured,
which is, in effect, codification
of the SMEs' knowledge.
Notifications can be triggered
in both cases, and analytics can
determine the length of exposure
and the exposure details. A similar
approach can be used for any
corrosion or process condition.
4. Carbonic acid corrosion-As
a result of the conversion of
triglycerides to hydrocarbons,
water and large amounts of
carbon dioxide are formed. Apart
from these substances needing to
be handled safely on an individual
basis, they can combine to form
carbonic acid that can be very
corrosive in the liquid effluent
air coolers and sour water
disposal systems. To address this
corrosion regime, the operational

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Hydrocarbon Processing - April 2021

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