By Dan Jeavons, Vice President for Digital Innovation and Computational Science on May 10, 2022
The greatest value of digitalisation comes from transformed work processes. Digitalisation is not ‘just a drone flying around’ or ‘an algorithm monitoring the performance of a compressor’. It provides tools to optimise end-to-end processes– challenging where and how work gets done. Over the past decade, we have been grown a pool of digitally savvy remote engineers who provide remote surveillance and operational support to our assets. This started with proactive technical monitoring with a focus on reliability but is now expanding to cover asset integrity and optimisation.
Proactive Technical Monitoring integrates people, process and technology, allowing us to “find small and fix small” thereby minimizing process safety and reliability risks. Algorithms can process years of historical data and monitor equipment 24 hours a day, 7 day a week to alert engineers when they detect anomalies. We have access to vast amounts of valuable data, and we are using that information to make better decisions and improve the efficiency and reliability of our operations. We have aggregated ~2.7 trillion rows of sensor data. We are now enhancing this with artificial intelligence. We monitor over 10k pieces of equipment across our operating assets with machine learning – helping us maximise their utilisation and prevent unplanned downtime.
Remote teams respond to automated alerts from the asset, check the situation and contact the local operations team if their intervention is required. We use AI not only to predict equipment failure but to optimise our asset performance. Shell’s Real Time Process Optimiser uses AI to enhance asset performance, helping our engineers close the gap to potential.
Our ambition is to move towards semi-automated operations powered by remote surveillance centres. We are moving towards AI, continually screening processes identifying anomalies and drift from modelled optimal behaviour and recommending adjustments. Advanced satellite technology in conjunction with drones and advanced sensors could provide real-time information about greenhouse gas emissions enabling industry-leading performance. Issues such as corrosion are quantified, compared with process and structural criticality, and prioritised for action. The whole production process could be optimised for market conditions. Whilst this may sound far-fetched, all of these examples are drawn from real projects which are showing promise in Shell today.
We are deploying Digital Twins to provide a virtual representation of the physical elements and dynamic behaviour of an asset over its lifecycle. Digital Twins allow us to replicate and simulate conditions at physical assets through digital replicas - allowing our staff to take actions and make decisions in the virtual environment that can be quickly manifested in the real world.
At Shell Energy and Chemical Park Rotterdam, autonomous, ATEX-certified robots drive around the facility collecting data and video. These robots gather high-definition video data that are analysed on the cloud by an advanced machine vision system that can read gauges, assess lubricant levels, identify corrosion and track its growth and report problems such as a missing safety equipment or unsafe working practices. The robots have proven their value by identifying fugitive emissions before they were found by established systems. We use machine vision to automate corrosion and damage identification. Our autonomous integrity recognition system provides automated inspection capabilities using machine vision technology, with the ambition to improve visual inspection quality and reducing HSE exposure.
At Shell, our vision is bold - to create an integrated digital ecosystem that is equipped to accelerate the transition towards a future with more renewable and low-carbon energy options for customers.
We are developing solutions which can improve the way we monitor and track GHG emissions across our business; help us manage the reliability of our growing renewables business; can provide diagnostics to our customers on the basis of real-time lube oil monitoring.
We can’t do this alone - we recognise that the greatest and fastest change will come from collaboration and broad coalitions to transform our digital work processes. We have to rely on each other’s strengths and do this together to deliver the competitive and affordable technology that can support the transition to lower-carbon energy systems. That’s why we founded the Open AI Energy Initiative (OAI) together with C3 AI, Baker Hughes and Microsoft. OAI is an ecosystem of AI solutions to help the energy industry’s digital transformation. The vision of the OAI is to put together a set of digital solutions which can transform digital work processes rapidly in the energy sector.
By bringing our solutions to market and encouraging others to do the same we hope to accelerate the adoption AI technology across the industry. We also hope to incentivise integration between solution providers to accelerate the end-to-end transformation of work processes in the energy sector.
As founding members of the OAI, we are working hard to develop a curated ecosystem of integrated solutions and creating fair value exchange for the companies that build on top of this platform. By doing so, ecosystem participants hope to accelerate the adoption of AI technology across the energy industry, which will reduce integration and operating costs for all parties and accelerate digital transformation in heavy industrial sectors.
As digitalisation advances it is facilitating highly automated and self-optimising assets, supported through remote operations, that are generating more value, reducing CO2 emissions and improving safety.