KONGSBERG’s technical evolution continues with the latest offering from Kongsberg Digital for the oil and gas industry – Digital Twin – a virtual model that provides a collaborative platform from which offshore and onshore users can explore a dynamic simulation that can be accessed via PC or tablet – or by using virtual reality gear for a totally immersive experience.
To start, the focus has been on unmanned oil and gas facilities, and according to Kongsberg Digital, employing Digital Twin can provide impressive cost savings, with up to a 40% reduction in CapEx and a 50% reduction in OpEx.
The goal is to improve decision support, which is accomplished by applying KONGSBERG’s Kognifai solution, allowing the Digital Twin to work as a collaborative arena in which users onshore to explore offshore planned or existing assets.
Moreover, during day-to-day operations, the Digital Twin will identify errors and calculate consequences to the adjustments that are about to be made. Risk and uncertainty will be accounted for and minimised before going offshore, resulting in a smarter, safer and more productive operation.
To find out more about the potential of the new Digital Twin, Energy Northern Perspective queried Kenneth Nakken, VP Digital Twin at Kongsberg Digital, via email.
ENP: What are the main differences between setting up a new, greenfield project Digital Twin versus setting up from an established, brownfield platform’s Digital Twin? What sorts of sources, such as 3D design and 3D scanning, are used to generate the Digital Twin?
Kenneth Nakken: “For greenfields the Digital Twin will always be ahead of the physical asset. As you detail the design of components and systems, the Digital Twin will be the platform for integrating data from the various design tools, and it can be the test bench for testing and verifying different concepts. When the design of the asset is completed, and the asset is being built, the Digital Twin is ready to go into ‘production’. Since you do not have real measurements from the field at that time yet, the data stimulating the twin is coming from a simulator. In this case, you have a simulator representing the physical asset not yet built, and one digital twin ‘living’ in the cloud where you can apply various tools to test, analyse and optimise.”
“This is a valuable cross discipline arena for testing and training while waiting for the real thing to go into production. At the time when the real asset is ready, it will replace the simulator and start stimulating the digital twin with real data. At this time operational personnel will be well trained on start-up sequences of the facility and ramping up the production.”
“For brownfields it is slightly different. As long as you have updated design documentation of the facility, building the digital twin is quite straight forward. Based on the 3D models used to design and build, process flow diagrams, P&IDs and the control system logic, we build the visual and functional models of the twin. In addition to building on the technical documentation, the twin also integrates business and maintenance information to encompass the asset life cycle aspect.”
“If you do not have the 3D models, using 3D scanning is a good alternative for building the 3D representation. However, this will require quite some manual processing to identify objects and connect to the relevant data tags.”
What are the challenges involved when dealing with the amount of information concerning all the different components of a platform – as well as the data generated during condition monitoring – considering the number of equipment suppliers?
“Dealing with the amount of information coming from the different components in the platform is not really a problem. The amount or volume of data is not really a limiting factor as long as there is an established, robust asset model, connecting data to the relevant components and equipment. With well-established naming conventions and asset structures this is pretty much an automated process.”
“The various equipment suppliers have their own instrumentation and condition monitoring solutions that work well. This type of data can be consumed by the twin and we see great value in combining this type of data with operational data and business data to do analytics across the silos that exist today. Bringing data from the other sources, e.g. from expert and business systems traditionally in siloed IT systems is more of a challenge. To maximise the value of Digital Twins – it is essential to combine the technical – operational – and business dimensions.”
Now that the Equinor project has shown Digital Twin’s potential, how have others in the industry responded?
“During ONS we attracted a lot of attention and received a lot of positive feedback on our Digital Twin presentations and demos, we have follow-up activities with several operators. The main differentiators between our digital twin and other players in the market, are our analytics capabilities, level of integration, our visualisation technologies and our ability to model the behaviour of equipment and processes. For many other players in this market, digital twins are pretty much limited to view data in 3D models, we articulate a solution with a much greater potential.”
Is Kongsberg Digital considering other offshore applications – offshore wind, for example?
“The digital twin concept is applicable to many industries. In fact, we have been utilising digital twins for many years in our wind solutions. We use digital twins of components and subsystems in the drive train in wind turbines. We have physical and data driven models running in real time stimulated by operational data from the turbines. The models are used to detect changes in the condition of components and can detect degradation long before it is detected by the condition monitoring systems delivered by the OEMs. The models detect changes at an early stage and calculates the remaining useful life of the components. This is valuable information when you are planning your operations and when planning maintenance campaigns.”
How do you foresee your Digital Twin solution evolving in the future?
“Looking a bit into the future, we see that more and more players in the value chain will both deliver data and consume data from the Digital Twin, where e.g. suppliers will not only deliver equipment and services, but also models and data associated with their deliveries. This will enrich the digital twin and enable more valuable insights and decision support – the twin becomes more like an eco-system.”
“This will drive changes to workflows and potentially disrupt established value chain. The players that are open to share data and understand the potential in how data can be used across disciplines and the players in the value chain, are the ones that will strengthen their positions and gain terrain in the long run.”