Making Sense of IoT Data With Visualisations

eVision’s Technology and R&D Lead, Ralph Maroun, on empowering enterprises with cutting edge technologies, utilising IoT to its fullest extent through powerful data visualisations.

The Internet of Things (IoT) is an emerging technology in the oil and gas industry, and a great means for upgrading brownfields to operate within the modern digital ecosystem. But the amount of data that the IoT is predicted to generate will remain unactionable without an application that provides context to it.

Taking over a legacy production plant, or a brownfield, means bringing old equipment and infrastructure up-to-speed with the organisation’s more modern operations management systems. Brownfields are a challenge as they are less digitalised; yet they make up around 80 percent of the oil and gas market. (Greenfields—new capital investments—make up the rest). How can you get the most value out of these brownfield investments?

Digitalising Brownfields

The first step in modernising a brownfield is to take control of all of the existing plant info by digitalising it. Information and historical data for the existing plant is usually paper-based. Once digitalised, the brownfield can plug into the data management initiatives that are taking place across the rest of the business. Existing service buses can capture data stores, and data management systems are able to scale with the existing network infrastructure. Workflow digitalisation is the first, crucial step toward achieving operational efficiency.

Incorporating the brownfield into the IoT brings the organisation further into digital maturity. BP, for example, is leveraging a new IoT plant surveillance initiative to optimise its barrel production even further, given the low oil price environment.

“Data from IoT sensors empowers BP with dynamic modelling and real-time digital monitoring capabilities to quickly assess actual versus optimal performance deltas. Once fully deployed, BP predicts a four percent increase in production at a relatively small cost.”

But plants still run the risk of gathering too much IoT data. In another example, experts predict that new volume-measurement sensors from HP will produce at least 10 exabytes of IoT data, if Shell deploys these sensors in combination with new fiber-optic network infrastructure across its 10,000 oil wells. In comparison, all the words ever spoken in the world only amounts to around 5 exabytes, according to one estimate. That is a lot of data to sift through and manage.

So, Shell partnered with DreamWorks Animation and IBM to create 3D and 4D renderings of the oil wells. These digital maps of the IoT data give the plant teams more intuition over oil and gas levels in their reservoirs than the raw data would alone.

New visualisation technology, like Shell’s 3D and 4D maps, will make sense out of these huge caches of IoT data and make them relevant and manageable.

New IoT Visualisation Technology

A brownfield could take yet another bold move into the IoT: creating a full 3D point cloud model of the physical plant. New, affordable 3D laser scanning technology can scan brownfields and create these 3D models, the digital twins of the physical plants.

“Using the digital twin, you can link equipment to the data and show it to the user, either in the field with smart glasses combined with Augmented Reality technology or in the back office for simulations or training using virtual reality.”

By partnering with experts in GIS, 3D modelling and augmented reality, digitalised Control of Work (CoW) processes can be implemented in brownfields. Visualisations in a CoW solution can show 3D models with real-time plant data in a Geospatial system.

Leveraging IoT Visualisations for CoW and Process Safety Management

When designing isolations, the IoT could speed up the process of point confirmation and issuing work permits. Now, if you receive a verbal confirmation of the isolation, you can, at best, double-check the confirmation in the data historian in real-time, and a second person would go to the field to do a visual cross-check. Using GIS, however, two people can track the confirmation at the same time, saving a trip to the field. Meanwhile, 3D models of the plant could allow someone in the back office to gather all the information they need about a piece of equipment and aid in authorising a permit. You can save travel time by doing calculations in the back office to determine if a plant visit is necessary or not. These IoT connections can help.

IoT connections can also help visualise the plant’s state-of-fitness in a 2D plot plan, in real time. In an interactive P&ID, for instance, you can see real-time data from a valve.

The next step would be to take all of the 3D point cloud models into augmented reality. The data is laid directly over the equipment, keeping the operator’s focus directly on the work in front of him. This helps avoid incidents by not giving him an incentive to look away from the equipment while working.

Quickly adaptable software creates so many possibilities for leveraging IoT data to achieve operational efficiency. In these 3D models, you can link tag numbers directly to the equipment, use machine learning to leverage big data to predict failure before it happens and determine if failures will be safety critical.

Wearable devices could deliver real-time information over the location and status of field operators to a unified process safety management platform. When combined with mobile gas detectors and atmospheric weather monitors in the field, the platform could leverage all of this IoT data to strengthen a barrier management tool.

Any IoT data could feed into the process safety management platform and feed into a real-time cumulative risk model of the plant. This sets the stage for the operations team to implement a predictive cumulative risk framework on the plant in order to avoid major incidents in the future.

Given the right way to visualise the data, mixing the virtual with the physical could lead to boundless gains in efficiency and productivity.

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