Brownfield use of a digital twin allows the operation and maintenance team to familiarize themselves with an existing installation and try out various solutions before undertaking modifications or repairs.
A twin is born
Before undertaking modifications, maintenance, or repairs on an offshore platform or a ship, a highly accurate 3D visual replica of the asset is created with all parameters represented.
Data for the model is gathered from multiple sources, including design data, 2D drawings and 3D models, operational data from the field, together with a physical model of the asset and specialist systems. Once the model is established, teams have a virtual parallel asset where they can introduce more detailed data to simulate the anticipated modifications or variations of the basic design.
The model functions much like a flight simulator, where teams can create many different scenarios, run the system and test the outcomes. Information accessed from multiple expert applications affords the operator full overview of all disciplines contributing to the process as well.
At the heart of it all is Kognifai, the Kongsberg Digital platform for data sharing and analysis. Kognifai provides the infrastructure for the twin, interfacing all data required to carry out a fully virtual operability test and validate the behavior of the asset. The results are fed back and stored in the client’s master database.
To boldly go
The digital twin allows the operator to experience perspectives that would not be possible to attain in real life, getting inside the system and inspecting configurations and materials otherwise inaccessible on the physical unit.
Locating a particular part or section can be difficult as well, as the physical layout often differs from the drawings. Here the twin functions something like a virtual map, giving the user a “street view” of the system, providing the operator with additional information and allowing them to make betterinformed decisions.
Decisions include not only design configurations but also material choices, helping teams to know how different materials will perform before ordering equipment. The twin can be run in various time scenarios to simulate material wear and pinpoint maintenance requirements or probability of failure through the entire life of the unit.
Conditions change on installations over time. On an offshore platform, there may be a new well or a field tie-in requiring modification of the existing system. Then the digital twin becomes the team’s “sandbox”, a space where they can experiment with various options without physical consequences or having to shut down the actual system. They can also run what-if scenarios to test outcomes under extreme conditions or equipment failure, without risk to human life or the physical asset.
The digital twin not only allows engineers to explore options on a particular system, the control structure for an entire facility can also be plotted in to test operational procedures. Collecting that data has previously been a manual task involving numerous expert systems and applications.
Using Kognifai, the twin can be linked to various management systems. When connected to a maintenance system, the history of failures, weaknesses, and repairs can be incorporated in the model, allowing teams to predict maintenance requirements. The entire control structure and implemented control functions can be modified and tested in a safe environment before being installed in the field.
The main benefits of utilizing a digital twin in brownfield operations are related to increased production efficiency (PE) and improved implementation on modification projects. Experience has shown an increase of 2–5 % PE due to improved control schemes and more robust solutions, resulting in fewer unplanned shutdowns.
Modification projects are normally implemented during planned shutdown,resulting in reduced production. Downtime can be significantly reduced by testing and validating the changes up front with a digital twin. This not only makes for a smoother and safer start-up, but also avoids operational instabilities over several months of operation.