DNV GL has launched a program to pilot a methodology that will prove whether the data generated by digital twins can be trusted, and if the technology is delivering value. An initial partnership with TechnipFMC has led to the creation of the pilot, which is now being opened to the wider industry.
The program will develop and test a methodology for the qualification of digital twins to assure their dependability and value, aiming ultimately to encourage wider adoption of the technology in the oil and gas sector.
DNV GL’s methodology will address the fact that many digital twins—some created at the point of construction or completion of a new asset—represent an asset’s initial form and struggle to reflect developments in their physical counterparts as the asset matures.
DNV GL expects cloud computing, advanced simulation, virtual system testing, virtual-augmented reality, and machine learning will progressively merge into full digital twins which combine data analytics, real-time and near-real-time data on installations, subsurface geology, and reservoirs. The use of twins and trust in their accuracy is restricted by the fact that the data they contain does not always reflect the most up-to-date condition of the physical asset, the company said.
“Solving the digital trust challenge will be key to the dramatic evolution that we expect to see in digital twin technology in the years to come. If more sophisticated digital twins are to be widely accepted and developed at scale by the oil and gas industry, they need to be supported by accurate, valuable, and trusted technology,” said Liv A. Hovem, chief executive officer of DNV GL - Oil & Gas.