Hydrocarbon Processing - September 2021 - 44

Refining Technology
FIG. 5 shows an overview of the dashFIG.
4. Hydrocracker simulation model.
board representing the hydrocracker
configuration. The dashboard shows
plant data validating KPIs and calculated
to determine the plant data quality. It
also determines when an investigation
is required or when the dataset can be
dropped for the period of bad data. The
results of the process digital twin are displayed
via a dashboard.
The pilot dashboard contains mulFIG.
5. Hydrocracker configuration dashboard.
FIG. 6. MIIs assign a relative dollar value
to KPIs to guide unit operation.
between the RTR operations, RTR technical
support, advanced solutions support
and the co-author's company.
The process digital twin uses a kinetic
hydrocracker reactor model to predict
KPIs based on measured data. This model
is also capable of predicting unmeasured
KPIs, such as catalyst life and hydrogen
solubility. The model also includes the
effluent stripper, main fractionator, gas
plant and a hydrocracker LP planning submodel
to track the RTR planning model
accuracy. FIG. 4 shows the model of the
hydrocracker unit.
Saudi Aramco chose not to use the coauthor's
company's default architecturea
because the IT policies did not support
data transfer to an outside cloud. Instead,
the applications were hosted on Aramco
servers, with a view to transferring them
to the Aramco private cloud once the pilot
was completed. A proprietary dashboard
was chosen to display the process digital
twin results. Multiple servers were used
to enable the transfer of the data from
the plant and from simulations to the
dashboard and to create a process digital
twin. Connectivity to plant data allows
automation of the process digital twin application,
including retrieving plant data,
running the simulation engine, executing
gap calculations and other analytics.
44 SEPTEMBER 2021 | HydrocarbonProcessing.com
tiple displays, with each display configured
to present a subset of KPIs, depending
on the user. For example, the
model quality parameters (such as mass
balance) are displayed for the owner of
the process digital twin to allow maintenance
when required, while the reactor
and overall unit KPIs are tracked by the
process engineers. Process engineers can
also access higher-level KPIs, such as
MIIs. The dashboard is available via an
HTML interface to authorized personnel.
Other dashboards include:
* Unit performance indicators,
including conversion, volume gain,
yields, key product properties
(e.g., density, distillation, nitrogen,
sulfur and flash point) and plant
data quality parameters
* Reactor performance indicators,
including weighted average bed
temperature, exotherm, catalyst
life, treat gas ratio, CFR, stage
hydrogen consumption,
hydrogen solubility and leakage
* Model vs. simulation vs. LP
submodel performance for yields,
volume gain, hydrogen consumption,
distillation 90% cut points, swing
cuts and/or cut point shift
* MIIs that assign a relative
dollar value to KPIs to guide
the unit operation (FIG. 6).
The benefits from the process digital
twin include:
* Improved unit production, yield
and availability
* Enhanced unit energy performance
* Identified operational risks
and hazards
* Improved productivity and
operational effectiveness
* Consistent and systematic
monitoring of multiple sites
* Knowledge sharing between
Aramco departments.
The application can easily be expanded
to include tray calculation and
other equipment monitoring, as well as
gap analysis on the results. In addition,
data analytics can be included to calculate
new LP shift vectors and other predictive
analytics. The simulation model
is always available to plant engineers for
case studies, and the simulation data can
be loaded for any past period. The results
are available to authorized personnel via
the web interface.
The process digital twin automates a
significant portion of the process engineers'
daily collection of data and KPI
calculations, allowing personnel to refer
to one consistent source of information.
The process digital twin will allow engineers
to spend more time identifying
opportunities to improve refinery operations
and margins, with less time validating
and sorting data.
This application provides RTR engineers
with a basic process digital twin of
the hydrocracking unit to track the primary
KPIs, including conversion, yields,
catalyst life and others. The application
also tracks the LP submodel performance
and will enable the RTR manufacturing
and planning economic unit (MPEU) to
keep the hydrocracker shift vectors continuously
aligned with the operation.
NOTE
a KBC Co-Pilot
JITENDRA CHELLANI is a Senior Consultant with
KBC, a Yokogawa Company, in Abu Dhabi. He has
more than 15 yr of experience in delivering consulting
solutions for the refining and petrochemical
industries. He is a subject matter expert for
identifying and implementing opportunities for
margin improvement. He earned an MS degree in
chemical engineering from the Institute of Chemical
Technology, Mumbai, India.
GABRIEL WINTER is an Engineering Specialist with
Saudi Aramco. He has more than 20 yr of experience
in the areas of process design, process simulation and
optimization. In his current position at Aramco, he
works with various departments and business lines
to develop applications and solutions, using process
simulation and optimization models. He earned a Bch
degree in chemical engineering from the University of
Texas at Austin.
AHMED ALSHAIKH is a Process Modeling and
Optimization Engineer at Saudi Aramco. He has
experience in planning, scheduling and supply chain
optimization of Saudi Aramco's downstream business,
including refining, terminal and distribution networks.
In addition, Mr. Alshaikh has recently focused on
the applications of the process digital twin and
operational data analytics to the downstream oil and
gas industry. He earned a Bch degree in chemical
engineering from Heriot-Watt University in Scotland,
and is pursuing his MS degree in business analytics
and big data from IE University in Madrid.
http://www.HydrocarbonProcessing.com
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