Hydrocarbon Processing - April 2022 - GP-31

LNG
Digital transformation in LNG requires
a long-term, data-driven approach
C. TORRES, Cognite, Houston, Texas
The energy transition has begun, and natural gas, especially
in its liquefied form, promises to play a key role in enabling the
shift to a greener and cleaner global power picture. The potential
is there, but the LNG industry finds itself facing continually
mounting pressure from all fronts-the foremost being the rise
in production levels while prices continue to fall, putting companies
in a cost crunch at a time when investment is sorely needed.
The solution to this conundrum lies within the LNG industry's
ability to leverage three concepts: efficiency, profitability
and sustainability.
The LNG players who have managed to tackle these challenges
are the ones who have succeeded with a longer-term digital
roadmap and an investment in a data operations (DataOps) platform
on which to build their digital solutions. They have understood
the underlying power of connecting data from across their
operations and putting it to work to optimize decision-making,
rather than driving one-off digital projects intermittently.
There are three commonalities seen among the digital leaders
in the LNG industry. The first is that these frontrunners have
stopped seeing their data as something in silos and, rather, have
made concerted efforts to bring data together into one, bigger,
connected picture. Second, they have used that data to gain real-time
situational awareness about their operation. Lastly, they
can act on that awareness to drive better, more sustainable and
more cost-effective decision-making. The following will show
these aspects in practice.
Break down the data silos across your LNG operation.
This is an industry with a large and diverse set of operational
data, production data, meta data and financial data. In a digital
transformation, all this data must be brought together and
made accessible from a centralized place. This could be a data
platform or a digital twin, but, most importantly, this transformation
is about combining the data from multiple sources so it
is made meaningful and can be accessed by anyone from across
the operation or even the entire value chain.
For example, monoethylene glycol (MEG) is injected into
pipelines for thermodynamic hydrate prevention. Without
knowing the minimum concentration for the current production
rate, MEG is often either underdosed or overdosed, introducing
risk of hydrate formation. The information needed to
predict hydrate formation and to estimate the required MEG
concentration, given operational conditions, is spread across
production, sensors, piping and instrumentation diagrams and
well data sources, as well as in pipeline layouts, height profiles
and laboratory data. It is not until this data is consolidated and
made available for easy use that it can be leveraged to estimate
the current MEG concentration and to compute a recommended
maximum pipeline flowrate.
Put the data to work to gain real-time situational awareness.
According to a McKinsey & Company industry report on
the digital era of the autonomous plant,1
a carefully determined
combination of conventional technologies, artificial intelligence
(AI), ubiquitous data, connectivity and collaboration can work
in concert to consider the future state of refineries or petrochemical
plants. While data is at the core of the digital plant, it must be
part of a bigger strategy of digital solutions, working in tandem,
to extract its full potential. Data has no real value until it is put
in context, which requires layers of analytics to give it meaning.
Success will depend on fast and accurate information, in
context, from across the LNG value chain. For example, sensor
data-when contextualized-can help forecast potential incidents
before they happen, enabling the operators to take decisive
action before an incident occurs. Connecting data provides
a gateway to the world of predictive maintenance, optimized
uptime, reduced downtime, and a significant reduction in safety
and environmental risk. In an environment with increasing
regulations and greater transparency requirements, this window
into the live operation can reveal where there is excessive waste,
where efficiencies can be gained and what steps can be taken to
optimize production even further.
The author's company has had conversations with Lundin
Energy about what digitalization has done for its gas business.
The following is how Lundin is working with the author's company
to reduce its carbon emissions: " Trouble in the gas chain
means you may have to burn the gas, which is not good for the
environment, " said Stig Pettersen, Principal Engineer Automation,
Lundin Energy. " But we are looking into the data, using the
dashboard for energy losses and carbon dioxide (CO2
) releases.
Then, we can follow up, using key performance indicators. Now,
there is even competition between the different shifts to release
as little CO2
as possible! "
Make smarter decisions that help you get closer to fully
optimized production. There is no doubt that LNG companies
want to lower their costs and operate more efficiently and
sustainably. They also want to have the competence and capacity
to invest in new technologies, and to ensure that those technologies
are not wasted in cases of one-off use.
Gas Processing & LNG | MARCH/APRIL 2022 31
Hydrocarbon Processing - April 2022

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