IT & SECURITY

Enter the digital twin

The next evolution in advanced predictive analytics is upon the oil and LNG sectors.

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DNV GL oil and gas country manager Australia, NZ and PNG Richard Palmer described the digital twin concept as being a virtual image of an asset, maintained throughout the lifecycle and easily accessible at any time - a central part of the industry's digital asset ecosystem.
 
The digital twin integrates data from many different software products, and Palmer said data smart asset solutions were critical to reducing operational costs. 
 
"It has been done in elements (power supply systems, DP systems, blowout preventers etc) but not as a whole unit or plant … this is only a matter of time," Palmer told Energy News. 
 
"Poor information management is often a hidden cost, accounting for up to a fifth of operational budgets, while a single unscheduled downtime can cost millions of dollars per day." 
 
About half of these are due to various types of mechanical failures, which data monitoring can prevent. 
 
"The digital twin is a concept that will enhance information management and collaboration, where the experts can work together, preventing costly mistakes and rework," Palmer told a DNV GL breakfast on digitisation in the oil and gas industry in Perth last week.
 
DNV GL currently has a Recommended Practice about data quality and hardware in loop testing (DNVGL-ST-0373), among other things in the evolving technology. 
 
The digital twin brings experts together within a cloud-based platform where all data and analyses are available at any time.
 
Information could be updated throughout the lifecycle with real-time information, with a collaboration platform that prevents working in silos and gives early insight into potential conflicts, which subsequently boosts efficiency.
 
The opportunity presented by DNV GL last week provides one solution to the challenge posted by Siemens' Germany-based vice president oil and gas strategy and technology Thomas Sparks told Energy News on the sidelines of APPEA 2017 in Perth this month.
 
Sparks said internal silos were one of the biggest challenges that oil and gas companies face in sharing information, and suggested digital solutions could be the key.
 
Industrial assets are designed, built and operated by engineers who rely on many different data sources and various models, working with enormous amounts of data. 
 
Palmer said that while specialised teams created models separately conducting analyses for their specific tasks, that way of working meant the most current information and calculations may not be readily available for crucial decisions, as the teams operate in silos. 
 
Data smart asset solutions, therefore, are a key to improved business performance and risk management. 
 
The challenges of managing and using the growing amounts of data for analytics are rapidly increasing, he said. 
 
"Poor information management is often a hidden cost, accounting for up to 20% of operational budgets," Palmer said. 
 
"An example is lost data, which is costly and sometimes impossible to track down or reproduce. 
 
"Add to that the cost of replicated data, which over time becomes something of a parallel reality used in many business processes, and often fails to reflect the current state of the asset." 
 
Information management is even more critical when assets are moved into the operational phase, the transition which Australia's LNG boom is currently making. 
 
On top of this are the ever-increasing trends in mergers or assets changing ownership, particularly toward the end of design life when asset history information handover is seldom a priority. 
 
"At this point the need for accurate historical detail is at its most critical in the assessment of fitness for purpose and extension beyond design life," Palmer said.

 

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