The evolution of digital twins in subsea operations

As digitalisation grasps hold of the oil and gas industry, digital twinning is becoming a widely discussed topic. But for a technology that is the subject of so many conversations, there is still some confusion about what it actually is. Indeed, the definition of a digital twin often depends on who you are talking to. By Alan Whooley, Subsea Manager, Wood.

  • 3 years ago Posted in
As such, discussions around digital twinning tend to reflect the siloed thinking and operations that can still characterise some of the sector. Speak to a structural engineering company, and it is a structural engineering model. Discuss digital twinning with a data management company, however, and you’re talking about a data management system. This is ironic, given that breaking down these silos is one of the many advantages that digital twins can offer.

What is a digital twin?

To understand digital twins, it helps to take a step back and view it in a broader context. Rather than thinking of it as a specific function or a portfolio of technologies, digital twinning can be considered more as an approach that can take a number of specific forms.

One of the most widely deployed definitions is that digital twinning is a multi-faceted engineering model that enables design collaboration across all disciplines. Certainly, this is the accepted definition within the construction sector, where 3D building information models have evolved to become 4D and even 5D models that incorporate time and cost dimensions respectively.

This has enabled construction firms to develop central project models that, in effect, are digital representations of all of the systems, processes and information that form each project. With the central model in place, structural, electrical, and mechanical engineers can collaborate far more effectively when designing and constructing a building. Rather than a workflow that relies on completed documents and reports being exchanged, the digital twin transmits data to where it needs to be.

Since the construction and hydrocarbons sectors interact most frequently in the building of onshore facilities, the application of these principles has already crossed over. From there it has journeyed to the offshore sector in the past 18-24 months.

In practice, at a basic level, a digital twin is a computer simulation that represents a physical or statistical model of a given asset, system or facility. This virtual replica allows companies to manage the operation or integrity of the modelled asset from inception to decommissioning. Nonetheless, the definition gives room to incorporate a number of different approaches that are still grounded in the familiar. For example, smaller independent firms without robust data management systems could deploy a cloud-hosted geographic information system and a document management system that would allow all users – from engineers to procurement teams – to access and use live information to make joined up, effective decisions.

Digital twins and subsea operations

We have already seen digital twinning transition from onshore to offshore, so subsea is an obvious next step for its application. As elsewhere, subsea is experiencing a drive to commoditise and automate engineering processes, and digital twins fit perfectly into this agenda.

More specifically, there are two main use cases for digital twins in subsea operations:

  • Simulation: digital twins can be used to plan, investigate, and train individuals using ‘what if’ scenarios. For example, the integrated processes of an entire subsea, pipeline and facility can be simulated to train operators or to understand the system response to a planned change in operating conditions.
  • Asset performance and integrity monitoring: digital twins can be used in real time (or near-real time) to determine an asset’s physical response to current operating conditions and the output of decision-ready monitoring and advisory information. For example, a digital twin of a subsea spool that is subject to vibration caused by unstable flow can calculate the rate of fatigue based on real-time production data.

Eventually, a very large and sophisticated digital twin could combine all these and more, with the aim of allowing operators to manage every facet of their system through a remote digital replica.

As these use cases indicate, subsea’s unique challenges, particularly in deepwater, lend themselves to a digital twin solution. When even an infield flow line can have 30 miles of pipeline tied back to a facility, linear assets are spread over vast distances, and control systems represent an underwater version of spaghetti junction, even the slightest improvements to inspection regimes can deliver significant safety, efficiency and cost benefits.

With an established, robust, and proven digital twin of the asset in place, the traditional method of inspections can be transformed. Rather than sending an inspector offshore to operate an ROV, tag information on videos, communicate with the operations team on the asset or on the beach, an inspector can pilot the ROV from the safety and security of an onshore office building, using a digital model of the field.

Not only does this reduce the cost of sending an inspector offshore, the ROV pilot can be more efficient because flight paths can be included in the twin that make it easier to inspect the asset. Early estimates show that a digital twin can be used to improve inspector efficiency by up to 30 per cent.

Next steps for digital twins

Looking further ahead, digital twins could enable autonomous inspection. Autonomous vehicles are already being trialled in offshore settings as part of the industry-wide drive to reduce costs.

But with a digital twin, we will soon be at the point where an autonomous vehicle that is either resident at the facility or deployed from a vessel will be able to navigate a pre-defined inspection path. Deep-machine learning techniques and artificial intelligence will take us to the point where the vehicle will be able to identify structural changes and detect leaks or anomalies automatically. Eliminating wastage associated with video review and manual anomaly annotation.

There’s also the issue of life extension of assets that are either approaching or technically past their expected decommissioning date. Whereas levels of fatigue, corrosion and erosion may have been accurately anticipated during the planned lifecycle, many assets, notably those in the North Sea, are now far less predictable.

The time dimension in a robust digital twin, combined with the advanced analytics that are a critical component of any digital model, give operators a more accurate predictive capability. Operators can therefore look at leading indicators and accurately predict where a riser, pipeline or jumper may become overstressed or a flow might become choked– and put remedial measures in place proactively.

Digital twins as a totex solution

As these few examples indicate the digital twin concept fits into two broad trends: one technological, the other operational.

Looking at the operational first, firms around the world are looking at ways to overcome the historical disconnect between opex and capex and the transition from the design and construction phase to operations. Totex, the total project expenditure, may sound like the latest buzzword of the month, but it reflects the broader reality, in which operational staff are involved much earlier in projects.

Digital twins provide technological support to this process, and can reduce the traditional headache that accompanies the handover of a capital project to operations. In the traditional IT estate, systems used to design a field or facility are typically entirely separate from those used to manage integrity, maintenance or operations. In the world of digital twins, these systems can be joined together across the whole lifecycle – with obvious financial advantages and operational benefits.

With regards to technology, digital twins bring together all of the major IT trends of the past few years: data and advanced analytics; sensors and connectivity; the industrial internet of things; robotics, AI and deep machine learning; cloud and utility computing. Even augmented and virtual reality have a role to play.

To date, the major specialist software houses have not focused on subsea operations: there has been more to gain from general application that can be replicated across an onshore refinery, a process plant, or a process production facility. But as we have seen, digital twins are not an obscure branch of technology with limited business potential.

As new models of digital twin become established, with a combination of replicable and bespoke components, we should see some of the most entrenched challenges in safe subsea operations being broken down.

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