The ability to continue through the various production cycles unabated (zero unplanned downtime) in the oil and gas industry means that practical efficiencies using digitisation are essential. The most practical, accurate and efficient digitisation method to manage production cycle continuity is a digital twin – an accurate virtual representation of a plant or asset. In addition to improving production efficiency and reducing the likelihood of unplanned maintenance, a digital twin provides numerous other benefits.
These include proper visualisation, sharing and collaboration on projects; faster and better decision-making; asset integrity monitoring and management; and advanced project planning. WorldsView vendors Topcon, Esri, Autodesk and Clearedge each provide solutions that help facilitate the ‘building’ of a truly representative digital twin. Improved revenue is realised through increased production, reduced project start-up times and improved operational efficiencies.
The real digital twin
Most interpretations of a digital twin have been limited to 3D visualisation of physical assets. This is an inaccurate description. A digital twin, in the true sense, is a virtual representation of a potential or physical asset that integrates artificial intelligence, machine learning and software analytics. In so doing, it creates a real-time, dynamic digital model of a physical system. “The model can be developed into a living, functional, intelligent digital model that provides live data on physical assets and their operations,” says Edwin Atiegoba, technical account manager, WorldsView. “This allows effective remote management of real assets. WorldsView stocks and distributes OEM products that help facilitate the four-step pathway required for digital twins.”
Creating a digital twin step-by-step
Step 1 – capture
Data capturing using a 3D laser scanner facilitates data collection from an asset, which can be used to generate new as-built drawings and 3D models of facilities. It is more accurate and faster than traditional techniques, especially when there are no existing drawings. It has also proven highly cost-effective when collecting data from large areas like oil and gas platforms and refineries. WorldsView vendor, Topcon, has developed a revolutionary 3D laser scanner – the GLS2000 – to this end.
Step 2 – process
Raw data must be processed before it can be interpreted. Two of WorldsView’s vendors, Topcon and Autodesk, provide solutions for this aspect of the digital twin build. Topcon Magnet Collage is an intuitive, flexible software that analyses point cloud data from any 3D laser scanner. It does this quickly and includes point clouds and panoramic images from the field when processing and analysing raw data. Autodesk Recap (Reality Capture) is a point cloud processing software and 3D scanning software for intelligent model creation.
Step 3 – model and design
Once the above two steps are complete, designing a 3D model based on the accurate point cloud follows. Topcon and Clearedge 3D teamed up to develop feature-extraction software called EdgeWise. It is an inbuilt modelling platform that uses advanced algorithms and pattern-matching technologies to extract plant features. The adoption of these technologies speeds up the process of creating an intelligent 3D model of your plant.
Step 4 – share and collaborate
Esri, another of WorldsView’s vendors, provides tailored share and collaboration software called ArcGIS Online. It is a cloud-based software used to create and share interactive web maps and apps, collaborate online and analyse and work with data. A Nextspace software application called Bruce Digital Twin is used to integrate CAD, BIM, GIS, IoT, Point Clouds/LIDAR, multimedia data and other spatial and non-spatial data for facilities and asset management.
Bruce is used to store, search, view, analyse, collaborate and present from an open standards cloud-based web user interface. It allows users to directly import from various IFC (industry foundation classes) data sources, including Revit IFC and others. A distinct advantage of this software is that it provides a modern digital version of the ‘Method of Loci’, making the visual data navigation available to everyone.
“Yet another benefit of Bruce,” concludes Atiegoba, “is it enables sophisticated data integration, visualisation, analytics and machine learning not just for the oil and gas applications, but also for architecture, engineering, construction, agriculture and other industries. With the aid of this digital twin workflow, a living, intelligent and location-based digital twin model of an oil and gas facility can easily be developed.”
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