Hydrocarbon Processing - April 2022 - GP-17

SPECIAL FOCUS: GREEN TECHNOLOGIES
The carbon conundrum: Digital technologies drive
sustainability in LNG production and transmission
C. HARCLERODE, AVEVA, Houston, Texas
Shell's Prelude FLNG (floating LNG)
vessel is the largest floating production,
storage and offtake vessel in the world,
weighing as much as six aircraft carriers
and stretching 1,601 ft. The offshore facility,
which is currently anchored hundreds
of miles off the coast of Western Australia,
produces natural gas, then liquefies it at sea
so that there is no need for long pipelines
to deliver gas to processing plants onshore.
Of much concern to vessels like Prelude
FLNG and to the larger LNG industry is
a new initiative from the COP26 conference
in Glasgow that is significantly increasing
pressure on oil and gas to reduce
gas emissions for cleaner energy production.
Simultaneously, governments are
also passing their own regulations to limit
emissions, placing new caps and restrictions
on production. On multiple fronts,
LNG companies are facing rising demands
to improve the efficiency and the
sustainability of their operations.
The challenge is to accomplish these
goals while avoiding massive new capital
investments, which is why many LNG facilities
have already turned to new digital
tools to make the most of their existing assets
and systems. Many of these use digital
twin technology-a complete and integrated
data model of all the engineering
and operations information about the facility,
which can be accessed using shared
platforms by everyone working on, and
remotely supporting, the site.
For example, Shell uses no-code operational
digital twin technology to remotely
monitor everything on the Prelude FLNG
vessel, from the giant chain winches in
the hull to the 50 MM liters (l) of ocean
water used to cool the natural gas. From
Perth, Shell engineers advise operators
thousands of miles away, saving the company
millions in transportation costs and
enabling teams to spot potential issues before
they become problems far out to sea.
With its digital twin program, the company
is not just building cleaner operations
at sea, it is building more efficient, reliable
and profitable operations, as well.
Site planning with the support of
digital twins. Simply put, a digital twin is
comprised of individual, focused twins-
the process twin combined with the operational
twin, and, for example, the financial
twin, the asset registry twin, the human resources
twin and so on-which, together,
form an integrated system of systems.
Digital
twin
technology has
been
around for many years. In this time, industry
users have built up a wealth of experience
with these digital tools and have developed
a much keener understanding of
process stimulation. Cutting-edge users are
adopting a layers-of-analytics approach,
which moves beyond steady-state simulation
models to more advanced, dynamic
models fed with contextualized, highquality,
real-time data and associated intelligence.
The results of the simulation models
feed back to the operational twin to be
operationalized in the form of targets and
forecasts, which enables further layers of
analytics, such as plan-vs.-actual analytics.
A process digital twin is a replica of a
plant, with information about pumps,
compressors, heat exchangers and any
other relevant equipment modeled to
mimic the workflow of the plant. This simulation
can help improve plant efficiency
throughout the entire plant lifecycle, from
planning to process optimization to predictive
analytics. Creating a process twin
is a crucial step in optimizing the liquefaction
process and detecting equipment
problems before failures occur. The integration
of the process twin and the operational
twin, along with the other focused
twins, produces a truly holistic digital twin
of the business, which empowers remote
and on-premises operator teams with the
augmented intelligence they need to optimize
operations and reduce emissions.
A digital twin also helps in the planning
process for a new facility. The digital twin
can evaluate hundreds of cases and scenarios
within minutes to find a solution that
will reduce emissions from the beginning,
dramatically speeding up the engineering
cycle. Modern steady-state simulation
models can optimize design and the same
model can be used later to monitor and
optimize operations. It also enables engineers
to model different scenarios and
equipment locations in the front-end engineering
and design (FEED) stage.
Steady-state simulation models can help
optimize LNG plant design. Engineers can
perform studies and look at different heat
exchangers, distillation columns or flare
designs to see which options will deliver
maximum results, while increasing plant
safety and minimizing both emissions
from steady-state operations and fugitive
emissions from operational failures.
For example, if an engineering team
needs a certain throughput capacity for
a reaction vessel, and the team is debating
between using one large vessel or two
smaller vessels, it can model the cooling
and energy costs for the different scenarios,
look at the pressure on specific lines
and total throughput capacity to decide
how the control design and operability of
the two scenarios compare.
These types of major capital decisions
create significant risks. A holistic digital
twin can help companies manage the risk
associated with huge capital projects by
providing shared data and facilitating collaboration
between project managers,
vendors and suppliers. Simultaneously,
a layer-of-analytics approach supports
quicker and more accurate decision-makGas
Processing & LNG | MARCH/APRIL 2022 17
Hydrocarbon Processing - April 2022

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