DNV GL issues guidance on digital twins

Nov. 16, 2020
DNV GL has published a recommended practice to the oil and gas industry on digital twins.

Offshore staff

OSLO, NorwayDNV GL has published a recommended practice (RP) to the oil and gas industry on digital twins.

DNVGL-RP-A204: Qualification and assurance of digital twins, provides advice on assessing whether a digital twin will deliver to expectations from start of a project; gaining confidence in the data and computational models that a digital twin runs on; and assessing the readiness of an organization to work with a digital twin.

According to DNV GL, although many companies already use digital twins or plan to do so over the coming year, there has not been an agreed methodology for developing and operating the technology among oil and gas operators and the supply chain.

The new RP provides guidance for digital twin developers, introduces a contractual reference between suppliers and users, and is intended to serve as a framework for verification and validation of the technology.

It also builds on earlier DNV GL RPs concerning the qualification of novel hardware technology and assurance of data and data-driven models.

The methodology behind the new RP has been piloted on 10 projects with the involvement of Aker BP, Kongsberg Digital, NOV Offshore Cranes, and others.

The framework is said to provide clarity on the definition of a digital twin; data quality and algorithm performance; and requirements for the interaction between the digital twin and the operating system.

It addresses the physical asset, the virtual representation, and the connection between the two – the latter is the data streams that flow between the physical asset to the digital twin and the information available from the digital twin to the asset and operator for decision making.

“Some digital twins are simple, covering a single component. Others are highly complex, spanning entire facilities,” said Kjell Eriksson, vice president, Digital Partnering, DNV GL – Oil & Gas.

“All of them must be trusted because millions of decisions about the design, construction and operation of hundreds of thousands of real-world assets will be taken based on them.”