How can digital twins be trusted to deliver value?

By Kjell Eriksson and Per Myrseth, DNV GL

The digital twin is a virtual image of an asset maintained throughout the lifecycle and easily accessible at any time
The digital twin is a virtual image of an asset maintained throughout the lifecycle and easily accessible at any time (illustration: DNV GL)

In the first of our two-part series, DNV GL’s Kjell Eriksson, VP digital partnering and Per Myrseth, service lead: data management, analytics and assurance of digital assets, explore how trust is critical to adopt, implement and accelerate value from digital twins…

Physical oil and gas assets are built to perform to the highest standards and undergo rigorous assurance processes throughout their lifetime. However, there has up to now not been any requirement for their digital counterparts to undergo the same processes.

Some digital twins are simple, covering a single component. Others are highly complex, spanning entire facilities. All of them must be trusted, as millions of decisions about the design, construction and operation of hundreds of thousands of real-world assets will be taken based on them.

Oil and gas companies are increasingly utilising digital twin technology to bring asset information from multiple sources together in a single and secure place, connecting 3D models with real-time field data during the operation phase.

For example, in October 2019, Kongsberg Digital, a subsidiary of KONGSBERG, signed a NOK 100 million (USD 10.5 million) contract scope to digitalise the Nyhamna facility, a gas processing and export hub for Ormen Lange and other fields connected to the Polarled pipeline. [1]

Rather than think of it as a single, all-encompassing virtual system, this digital duplication should be seen as a collection of elements or components, of various levels of complexity, each with their own distinct role and function (figure).

The journey from data as “raw materials” to where you serve the data for consumption can sometimes be very long and pass through several stakeholders. Therefore, the activity to monitor the condition of the data so that it is fit for use all the way to where it is needed, is often challenging.

Building trust and efficiency in the digital era
Digital twins are a rapidly developing technology widely expected to become a significant contributor to the future management of major industrial sites. The digital twin market is estimated to grow from USD 3.8 billion in 2019 to USD 35.8 billion by 2025. [2]

As this technology evolves, it is vital to combine the criticality and the use cases of the digital twin to fully understand the quality and all the components in it. According to Gartner, 75% of organisations implementing Internet of Things (IoT) already use digital twins or plan to within a year. [3]

As oil and gas operators demand proof that digital twins can be trusted and deliver value over time, DNV GL in partnership with TechnipFMC, has published the oil and gas industry’s first recommended practice (RP) on how to build and quality-assure digital twins.

DNVGL-RP-A204: Qualification and assurance of digital twins sets a benchmark for the sector’s varying approaches to building and operating the technology. It provides valuable guidance for digital twin developers, introduces a contractual reference between suppliers and users, and acts as a framework for verification and validation of the technology. It builds upon the principles of DNV GL’s Recommended Practices for data quality assessment and assurance of machine learning.

The methodology has been piloted on ten projects with companies including Aker BP, Kongsberg Digital and NOV Offshore Cranes. It has also been through an extensive external hearing process involving the industry at large. In addition, TechnipFMC’s deep domain knowledge and expertise in digital technologies and oil and gas infrastructures has made an essential contribution to jointly developing the RP.

The framework provides clarity on the definition of a digital twin; required data quality and algorithm performance; and requirements on the interaction between the digital twin and the operating system.

The aim is to bring a level playing field to the sector’s varying technical definitions of, and expectations of, digital twins. The key is to set a benchmark for oil and gas operators, supply chain partners and regulators to establish trust in digital twin-generated data for performance and safety decision-making in projects and operations.



Kjell Eriksson, DNV GL

Kjell Eriksson has more than 30 years of international experience from the oil, gas and energy sector. He has managed DNV GL’s operations in the Middle East, Asia and Norway. He is currently responsible for establishing new partnerships and ways of collaborating with partners and customers enabled by digital solutions in DNVGL. He also holds the position as Chairman of the Faculty of Engineering at the Norwegian National University of Technology and Science (NTNU).

Per Myrseth, DNV GL

Per Myrseth has a master in informatics from University at Oslo. He has worked as a consultant and researcher for more than 30 years on topics related to creating interoperability, trust and value in data. He joined DNV GL in 2005.