Large oil companies are turning to digital twins to keep their rigs running for longer and more consistently. (Photo by Jonathan Nackstrand/AFP via Getty Images)

The impact of Covid-19 is being felt everywhere. Even in remote and isolated locations, the far-flung facilities of the oil and gas industry have not been impervious to Covid’s effects on the world economy, but while it is clear that a pandemic can have an effect on oil prices, there are other problems facing the fossil fuel business. Big Oil is responding by deploying artificial intelligence (AI), digitalisation through edge and cloud computing, and – increasingly – digital twin technology.

There are many ways to build a digital twin. As GlobalData’s recent thematic report on digital twins in oil and gas states: “There is no single template, solution, or indeed platform that will magically create digital twins” and there is no specific technology needed to build one.

A digital twin is tech designed to optimise and protect the physical environment. This is done through real-time analytics and the use of simulations and visualisations. Digital twins also reduce operating costs and extend equipment life through troubleshooting and predictive maintenance, as made possible by data model forecasts. While the actual number of dedicated deals centred on digital twins remains small for now, the technology can be found not just in oil and gas but sectors such as healthcare, automotive, construction and defence.

Gazprom: a digital twin pioneer in the oil industry

“In the oil and gas industries, devices can be connected to smart sensors and meters that collect valuable data and information for smart energy management,” explains Giuseppe Surace, chief product and marketing officer at Eurotech.

In the oil and gas industries, devices can be connected to smart sensors and meters that collect valuable data and information for smart energy management. Giuseppe Surace, Eurotech

The internet of things [IoT] allows remote access to these networks, enabling smart grids, power distribution infrastructures and metering. Digital twins are being used in the industry to make the process smarter and to help companies understand how processes and systems react to changing situations.”

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The use of digital twins in oil and gas comes after a massive revenue slump for the sector. As GlobalData analysts reported in their recent review of industry contracts, the number of global oil and gas contracts decreased by 28% between 2019 and 2020.

While Covid-19 contributed to this drop, the biggest cause was the shortage of easily available resources. However, a tech solution has been discovered for this problem by the Russian oil company Gazprom.

Gazprom Neft, Gazprom’s oil-focused subsidiary, harnessed the power of digital twins in 2018 to make the first ever digital model of the Achimovsky strata, a subsurface formation in Western Siberia. The strata are estimated to hold vast deposits of hydrocarbons, many of which are classified as 'hard to recover'. The new digital twin comprising of integrated maps and well data has helped Gazprom identify about ten potentially large discoveries, with resource potential in excess of 34 billion tonnes.

In 2020 it was reported that initial production from a single well in the strata stood at 300 tonnes per day, three times higher than forecast. The company now expects to produce seven million tonnes-worth of oil from the Achimovsky reserves by 2025, and has already produced other digital field twins as recently as February.

How a digital twin helped Royal Dutch Shell

Gazprom’s manoeuvres make sense considering the operational phase of industry projects accounts for approximately 75% of all costs. As GlobalData notes, even a 10% reduction in operational expenses could result in savings worth millions of dollars over a project’s lifetime.

With issues of supply scarcity and dwindling demand from the pandemic, oil companies need innovative ways to reduce operational expenses and capital expenditure to maintain cash flows.

Through modelling an entire structure in the highest detail, asset potential is unlocked either through life extension or optimisation. Thomas Leurent, Akselos

For James Morris-Manuel, Europe, the Middle East and Africa managing director at Matterport, digital twin software is the only cloud software that enables oil and gas companies to manipulate large digital assets of physical structures.

To this, Surace adds: "Those who understand the operational aspects of an asset can quickly identify the source location and its relation to everything else around it. Using real-time data from connected sensors on the physical asset, digital twins evolve using machine learning and simulation, and allow users to see what is happening with the physical asset in the here and now, and make data-based predictions for the future."

In this way, digital twins have helped Norwegian oil major Equinor save 30% and 50% in capital expenditure and operational expenses, respectively. The company’s Echo digital twin solution enables an interface hosting essential information for all involved in project development and operations, improving collaboration in each phase. This data includes design, construction, operation, maintenance, and supplementary functions such as logistics and finance.

Echo also supports augmented reality (AR) for personnel to review 3D visualisation of facilities in real time. Such tools can greatly support the training of new personnel and help them familiarise themselves with the surroundings before going offshore, all through using Hololens headsets.

The system also helps to reduce potential errors and delays by providing up-to-date information in real time. Finally, Echo future-proofs Equinor facilities by providing for the incorporation of future modifications to the project design. This flexibility in the interface can assist in the efficient planning and execution of inspection and maintenance activities. In some cases, such efficiency can even extend the life cycle of facilities.

Digital twin maker Akselos has proven this with predictive digital twins across a range of oil and gas facilities. In the southern North Sea, the company has worked with Shell to extend the life of the half-century-old Royal Dutch Shell platform by a further 20 years. This was done through optimised asset inspection and enhanced monitoring.

"Through modelling an entire structure in the highest detail, asset potential is unlocked either through life extension or optimisation," says Thomas Leurent, CEO at Akselos.

The Royal Dutch Shell digital twin also helped its real-life equivalent by reducing an oil and gas problem that hits both asset life cycles and the environment: downtime.

Down with downtime

A 2016 study by Kimberlite puts the cost of unplanned downtime to the oil and gas industry at $38m annually. The cost is even bigger for the environment, with data from the World Bank’s Global Gas Flaring Reduction programme suggesting the equivalent of 270 million tonnes of carbon emissions are released into the atmosphere every year from gas flaring.

The energy transition is an opportunity for many mature assets to be repurposed, therefore it is critical asset owners optimise operations today for future life extension. Thomas Leurent

Gas flaring is the combustion of excess product typically released during an unplanned shutdown when a plant experiences over-pressuring. About 145 billion cubic metres of gas is released during gas flaring each year.

By reducing downtime, digital twins can prevent the environmental harm of needless gas flaring while saving money for energy companies. This benefits the oil and gas industry as it increasingly aims to offset its effects on the environment. Such efforts are seen as increasingly important against the background of the coming transition to cleaner forms of energy.

There is a catch, however. Digital twins often rely on cloud data to provide all parties with the information they need. Big oil means big data, and cloud computing requires data centres, the running of which requires a lot of energy. Given that a typical oil platform can generate up to two terrabytes of data every day, running their data centres has an environmental cost. To counter this, Akselos works on algorithmic efficiency, which can achieve operations using "100,000 times less resource" than the equivalent calculation with legacy algorithms, according to Leurent.

In Leurent's view, asset owners want environmentally friendly solutions for existing infrastructure, while avoiding new builds with a 20–30 year life cycle.

"The energy transition is also an opportunity for many mature assets to be repurposed, therefore it is critical asset owners optimise operations today for future life extension," he says.

On the edge of the world

Another difficulty when it comes to Big Oil's big data flow is that many offshore facilities work on satellite communications with sharply limited bandwidth and significant latency.

"Cloud services offer a host of benefits with digital twins but can suffer from latency issues when analysing and communicating time-sensitive data," says Craig Beddis, CEO and co-founder of deep tech distributed computing start-up Hadean.

Cloud services offer a host of benefits with digital twins but can suffer from latency issues when analysing and communicating time-sensitive data. Craig Beddis, Hadean

For Beddis, an obvious solution would be using edge computing as it keeps computation and data storage closer to the location where it is needed.

"By processing data nearer the source with edge networks, simulations can be reliably kept up to date," he says. "Combining edge computing with cloud infrastructure ultimately gives you the advantages of decentralised control and real-time data streaming.

"The advent of 5G and IoT devices will go hand in hand with edge and decentralised cloud and definitely allow large systems to be properly represented.”

Matterport's Morris-Manuel adds that while edge computing brings large digital assets such as twins closer to the user, in an oil and gas context it is a moot point as the user often doesn’t need to load the entire asset all at once before viewing it. Digital twins also help lessen the strain on data.

"Digital twin technology enables assets to be sequentially loaded, making them available in real time from anywhere," he says. "Users can dive right in and quickly access specific areas at high resolution."

Louis-Philippe Lamoureux, senior product manager at AspenTech, suggests that "the future of edge computing is complementary to cloud capabilities".

"The duality will promote an infrastructure risk distribution between the offshore facility and the data centre," he adds. "Running digital twins on the edge will ensure real-time response and resilient execution of a model while the cloud continues its distant global monitoring.”

That such cutting-edge tech is being adopted by the oil and gas industry is interesting in terms of progress. The fossil fuel industry is traditionally not the fastest to adopt connected technologies.

However, with the use of digital twins, edge and cloud computing, AR and even AI, it is clear a digital revolution is under way in Big Oil, one that aims to clean up its image while also keeping its outposts operating for longer in an ever-changing world.

Find the GlobalData Digital Twins in Oil and Gas – Thematic Research report here.