Orbital Eye technology has the potential to produce a cleaner, more effective, and reliable monitoring package with the use of satellite imagery. This system compared to the conventional process which uses a helicopter to fly the line as well as foot patrols, would offer SGN and National Grid a higher frequency of monitoring (weekly) and have a less environmental impact where the helicopter releases approx. 173 tonnes per CO2 a year. Unlike our helicopter process, Orbital Eye is not subject to weather and would be able to analyse gradual encroachments like ground movement using artificial intelligence. This offers new opportunities for earlier indication of potential landslides permitting SGN and National Grid to proactively divert high risk pipeline protecting our assets and our customer’s supply.
Benefits
The project aims to conduct a side-by-side trial of CoSMiC-EYE and SGNs current monitoring services to assess their performance, efficiency, and cost-effectiveness for SGN's pipeline network. A successful trial outcome will allow SGN to make an informed decision on the most suitable pipeline monitoring solution, resulting in various benefits. These include improved accuracy and reliability in detecting potential threats or anomalies, timely response to emerging issues, and comprehensive coverage of the pipeline network. Additionally, the project is expected to provide cost savings and environmental benefits by identifying a more efficient and sustainable monitoring method that reduces carbon emissions. The trial also seeks to ensure seamless integration with SGN's existing applications and infrastructure, as well as scalability to cover the entire pipeline network without significant additional costs or complexities. Lastly, the project aims to enhance stakeholder satisfaction by selecting a monitoring solution that aligns with SGN's strategic goals and priorities, while meeting the expectations of pipeline operators, management, and other stakeholders.
Learnings
Outcomes
Project Outcomes:
Throughout the project’s life, significant data has been collected and analysed to gauge the effectiveness of satellite monitoring technology. This data includes key performance indicators such as the number of detected pipeline anomalies, response times to potential threats, and the accuracy of threat identification.
Technology Readiness Level (TRL) Advancement:
At the project's inception, the satellite monitoring technology was assessed at TRL 7. Following rigorous trial and refinement phases, it is now evaluated at TRL 8, indicating that the system is fully functional and can be tested in a variety of operational environments.
Performance Improvement:
The integration of satellite technology has led to:
• Increased surveillance coverage, ensuring comprehensive monitoring without geographical constraints.
• Enhanced data analytics capabilities, providing SGN and NGT with more accurate and actionable insights.
• A reduction in the environmental impact through decreased reliance on helicopter surveillance, which also aligns with the company's commitment to sustainability.
Lessons Learnt
Integration and Industry Compatibility:
Any future project should prioritise the integration aspect, evaluating the industry's current state and preparedness of business culture and engineering capabilities to adopt a new technology on a larger scale.
Strategic Training and Workforce Preparation:
The necessity for strategic training face to face initiatives was highlighted. Future projects should build a comprehensive training framework to ensure all employees are adept and understanding the new technology effectively.
Assessment of Industry Evolution Readiness:
Despite the high TRL of the satellite technology, we noted the industry's readiness is another matter.
Customised and Adaptable Solutions:
Customisation to fit our unique operational needs was crucial. Going forward, projects should seek to co-develop tailored solutions with the internal Information technology within the business, ensuring adaptability to our specific needs beforehand.
Continual R&D and Innovation:
The project reinforced the need for ongoing innovation to keep up with evolving technological methods. We must engage in continuous demonstrations and development cycles, even post-deployment, to maintain relevance. We would look to optimise the data with our Data Analytics team going forward.
Intelligent Risk Management:
Integrating AI to filter out non-threats and false alarms proved invaluable. Future methods should embed such intelligent systems from the beginning to enhance risk management and decision-making processes.
Complementary Technological Solutions:
We acknowledged the limitations encountered, such as satellite data reliability issues under certain conditions and image quality for the engineers. Once trained of use of past historical images, it was detained but if we wanted a on demand view – the engineering judgement of triage was compromised.
Potential for Widespread Adoption:
The success of the trial suggests high potential for large-scale deployment. However, lessons learned regarding gradual integration and continuous optimisation are crucial for scaling up.
Post-Implementation Review and Adaptation:
The close down meeting emphasised the value of post-implementation reviews. Future projects should include such reviews as a standard practice to refine and adapt methodologies continually.
