The challenge
3D models can help your engineers and technicians interact directly with a digital twin of an oil rig, navigating their way through an immersive and user-friendly interface to find the locations of equipment that need maintenance with ease.
However, if your 3D model contains incomplete links to the asset register, or you haven’t increased the quality of your data to be able to correlate the asset register with the model, the 3D model will just slow you down. An average oil rig might have 100,000 pieces of equipment that need to be linked with vital data (like maintenance schedules) and made available in your data visualisation. If they haven’t been linked, it’s just another data silo of undefined information loosely connected to an outdated 3D map.
Many companies have taken the first step to digitise everything, but haven’t yet addressed issues of data quality or linked each data point. This impacts the 3D model’s usability, as the data visualisation lacks integrity and accuracy.
How did we fix this?
Generally speaking, 3D models in digital twins must be built on quality data — they are the basis for your 3D navigation. However, there are other two main components you need to build an effective 3D model: correlated tags to help you correctly identify assets and proper links to your asset register to access relevant information.
In a recent project our team searched for equipment with incomplete links and tags in 14 existing 3D models. Once we identified all of the components that needed fixing, we began correlating any relevant data to the centralised asset register where we completed the data for the two features.
The results
