Oil and Gas Digital Twin Is Made Possible by Super-FEA Algorithm

MIT-licenced Reduced Basis FEA algorithm can boost simulation speed by 1000x.

As computer processing power increases, our capacity to simulate increasingly complex systems grows with it. It is getting to the point where we can use simulation not only to make predictions, but also to act as a twin, which thanks to modern algorithms developed by MIT, can be used for monitoring assets in real time—assets such as offshore oil and gas drilling platforms.

Digital twin of a shiploader structure. (Image courtesy of Askelos.)

Digital twin of a shiploader structure. (Image courtesy of Askelos.)

Digital twins are nothing new. But unfortunately, the very mathematics that power the concept of the digital twin are not new either. Classical finite element analysis simply does not have the capacity to simulate systems and structures of this magnitude.

This is where Askelos comes in. Askelos is based in Lausanne, Switzerland, and has been working to create a physics simulation engine utilizing the Reduced Basis FEA algorithm, which is under licence from MIT. This algorithm allows for large-scale simulations to be carried out 1000x faster than would be possible using any other commercially available method.

According to the Askelos website, its Askelos Integra platform has the power to model assets of huge scale, from a bridge to a space station. For customers, this allows for greater operational efficiency in terms of reduced unplanned downtime, as well as a greater understanding of risk and structural safety.

Askelos has recently turned its simulation skills to the oil and gas industry and is focused on designing and operating digital twins for aging offshore drilling platforms.

The initiative, a joint venture between Askelos and Industry Technology Facilitator (ITF) that will bring a joint industry project (JIP) to ITF member companies and beyond, can potentially prove the transformative impact of using a digital twin (or “digital guardian”) for aging offshore assets.

The aim of the project is to combine sensors, big data analytics and simulation to create an exact virtual replication of an oil rig. This will provide operators with real-time access to the condition of their asset from anywhere at any time, and allow a move toward greater operational efficiency via predictive and preventative maintenance.

“The creation of a digital guardian or twin of an offshore asset is a huge step forward for the oil and gas industry and will reap long-term benefits to enhance operational and cost-efficiencies as well as significantly reduce risk,” said Patrick O’Brien, CEO of ITF. “It will also advance information management and collaboration, where the experts and operators can work together, preventing costly mistakes and rework.”

The $2million project, which has been partly funded by Eurostars and the Swiss Commission for Tech Innovation, will last two years. Currently, one oil and gas company has signed up to the project in the North Sea, and ITF is currently looking for other project participants.

The oil and gas project is still in the R&D phase. However, you can see a case study of how Askelos used a digital twin to extend the life of a ship loader at this link.