Market insight
Big Oil is dreaming big with digital twin technology, as Giacomo Lee reports.
The impact of Covid-19 is 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’s clear that a pandemic can have an effect on oil prices, there are other problems facing the fossil fuel business. In response, the oil industry is deploying artificial intelligence, digitalisation through edge and cloud computing, and – increasingly – digital twin technology.
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.
Digitised Siberia
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 the drop, the biggest cause was the shortage of easily available resources. But a tech solution has been discovered for this problem by the Russian national oil company Gazprom.
The number of global oil and gas contracts decreased by 28% between 2019 and 2020.
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 new digital twin, comprising of integrated maps and well data, has helped Gazprom identify around ten potentially large discoveries, with resource potential in excess of 34 billion tonnes.
Last year it was reported that initial production from a single well in the strata currently stands 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.
Reducing costs
Gazprom’s manoeuvres make sense considering the operational phase of industry projects accounts for around 75% of all costs. As GlobalData notes, even a 10% reduction in operational expenses (OPEX) 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 OPEX and capital expenditures (CAPEX) to maintain cash flows.
In this way digital twins have helped Norwegian oil major Equinor save 30% and 50% in CAPEX and OPEX 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.
Digital twins have helped Norwegian oil major Equinor save 30% and 50% in CAPEX and OPEX respectively.
The system also aids in reducing 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 makers Akselos has proven this with predictive digital twins across a range of oil and gas facilities. In the 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.
The Royal Dutch Shell digital twin also helped its real-life equivalent by reducing an oil and gas problem which 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 industry as $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 CO2 emissions is released every year into the atmosphere from gas flaring.
Gas flaring is the combustion of excess product, typically released during an unplanned shutdown when a plant experiences over-pressuring. Around 145 billion cubic metres of gas is released during gas flaring each year.
Digital twins have helped Norwegian oil major Equinor save 30% and 50% in CAPEX and OPEX respectively.
By reducing downtime, digital twins can prevent the environmental harm of needless gas flaring, while saving money. This benefits the industry as it increasingly aims to offset its effects on the environment.
But there is a catch, in that digital twins can often rely on cloud data to provide all parties with the information they need. Cloud computing requires data centres, the running of which requires a lot of energy. Given that a typical oil platform can generate up to 2TB of data every day, running their data centres has an environmental cost.
To counteract this cost, Akselos works on algorithmic efficiency, which can achieve operations using "100,000 times less resource" than the equivalent calculation with legacy algorithms, according to Thomas Leurent, CEO at Akselos.
On the edge of the world
Another difficulty when it comes to the 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 startup 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. 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.”
Cloud services offer a host of benefits with digital twins but can suffer from latency issues.
James Morris-Manuel, EMEA managing director at Matterport, adds that while edge computing brings large digital assets such as twins closer to the user, in an oil and gas context it's 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.
That such cutting-edge tech is being adopted by the oil and gas industry is interesting progress. The fossil fuel industry is traditionally not the fastest to adopt connected technologies.
But with the use of digital twins, edge and cloud computing, augmented reality, and even artificial intelligence, it's clear a digital revolution is underway in the sector, one aiming to clean up its image whilst 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.
Digital twins in oil: how futuristic tech is keeping fossil fuels alive