Globally, leading oil and gas companies are strengthening their frameworks to increase resilience and agility, by leveraging automation. Technology advancement has ushered us into the era of predictive maintenance and production optimisation by leveraging the digital twin.
Why should oil and gas enterprises embrace the digital twin technology?
The oil and gas sector has a tremendous opportunity to carefully evaluate the risk and innovate to enhance their operations to meet changing environments by embracing the digital twin. The energy sector has always valued innovation and adopted advanced technologies before other industry sectors. As such, a digital twin is a real opportunity that allows real-time data analytics to elevate benchmarks for the predictive analysis of assets. It also supports measuring the performance through the multiple channels across the entire supply chain management.
Digital twins deliver productive and sustainable results that optimise the maintenance cycle to remove the limitations in IoT space, thus extending the asset’s life by reducing unplanned maintenance and labour costs. The benefit of digital twins is massive with significant impacts on cost savings and strategic competitiveness in the market
What makes the Digital Twins special?
A digital twin is a form of the digital system, method, or device that mimics the actual process with enough prior experience or data information. When the assets are stimulated, the data triggers the future predictive algorithm where the digital twin can offer agile and comprehensive operational understanding based on the environment. No doubt that boosts productivity, encourages effective decision-making and helps to achieve strategic goals of maximizing safety, reliability, and profitability.
The Benefits of Digital Twin Technology
13% of organisations implementing Internet of Things (IoT) projects already use digital twins, while 62% are either in the process of establishing digital twin use or plan to do so. *Infoq 2021
Below are 10 reasons why oil and gas companies should embrace digital twin technology:
Increased reliability of equipment and production lines
Enhanced production optimization and faster production times
Reduced HSE risk and reputation damage due to errors
Improved efficiencies through reduced downtime and improved performance
Decreased maintenance costs as predictive maintenance ensures breakdowns do not occur
Enhanced business opportunities through customised manufacturing based on real time insights
Enhanced customer experience through remote product customisation
Enhanced insights vial multiple real-time environments to improve process and product quality
Enhanced efficiencies in operations and supply chain
Enhanced bottom-line impact and profits
Digital twin and maintenance
Every business needs to ensure essential assets are running at optimal efficiency to maximise the return on capital investment. The digital twin system can numerate process-model simulation that provides real-time data analytics across the entire chain of processes. There are different types of maintenance stages of the equipment where leading enterprises can adopt digital twins:
Corrective Maintenance:
Most organisations rely on corrective maintenance to manage the equipment breakdown, however, overheads in downtime, labour, unscheduled maintenance requirements, need to be factored in.
Preventive Maintenance:
Some customer-oriented companies have been developed into the next step by working preventative maintenance where the data monitoring rapidly upon the lifetime of equipment and performance cycle before the actual failure happens. This process prevents unscheduled and catastrophic failures but still takes an expensive and higher risk when scheduled downtime, under-utilization of remaining helpful lifetime.
Predictive Maintenance:
Some technologically advanced market leaders are already using IoT & Digital Twins systems that optimize the maintenance cycle and stabilize corrective factors and preventative maintenance techniques. This maintenance achieves the cutting-edge management system to monitor the equipment lifetime data, predict precisely when projected replacement and help increase the expected component lifetime by reducing unscheduled maintenance and labour expenses.
How do the digital twins promote an intelligent transformational journey?
Nevertheless, Digital Twins are part of the Intelligence Automation (IA) scheme that leverages AI to create scenarios and decide on the action plan. The main points of difference between Digital Twins and AI applications such as machine learning (ML) are:
Machine Learning (ML) algorithms deduct the information from asset behaviour patterns and assume possible outcomes. Thus, they have blind spots in the deep knowledge of underlying physical properties that digital twins help to uncover.
Digital Twins can deliver better and faster decisions for the software application based on "What If" and "What is the probability?" scenarios to trial efficient revenue approaches.
It can expand its ability to predict and calculate the likelihood of asset situations when combined digital twin and physical data optimizes, solve problems, and perform various actions.
How does a digital twin deliver value to the oil and gas sector?
According to Forbes, 13% of enterprises that initiated internet of Things (IoT) projects are already stepping up the implementation of Digital Twins. In comparison, 62% are aware of establishing Digital Twin benefit and plan to do so.
Digitals Twins have been leveraged by Chevron Corporation, where they are addressing unresolved critical maintenance problems in oil fields. This will save millions of dollars annually reserved towards preventative equipment failure. According to a survey by Gartner 75% of organisations implementing industrial Internet of Things (IoT) plan to leverage digital twin.
Relation between digital twins and digital transformation
Digital transformation leverages the technology journey to extend business strategy and execution to meet changing market environment, challenges in dynamic workforces, environmental regulation, sustainability goals, geopolitical uncertainties, amongst others. Thus, digital transformation focuses on creating a resilient value chain, asset life cycle, and intelligent manufacturing based on exploiting emerging technologies in big data, cloud computing, control systems, automation networks, AI, IoT, and digital twins.
There are four types of digital twin tools used to progress digital transformation.
Component Twin
Component twin focuses on one component in the production process. Component twin assists bottom-line service technicians supports constant performance monitoring and offers predictive maintenance insights while reducing equipment downtime thus enabling a proactive, service-based business model execution.
Asset Twin
Asset twin creates a digital twin of a single piece of equipment within a production line.
System/ Unit Twin
System twin helps manage an entire production line. It is used to help product engineers, designers and architects to increase product mix features and value innovation to optimize efficiency and accelerate time to market.
Process Twin:
Process twin focuses on the entire manufacturing process – process design, production optimisation, maintenance and reliability. It is used to help senior management get reliable insights from real-time data feeds thus enabling faster decision making across production, processing and planning models.
Where to Next?
IA and Digital twin technologies enable the oil and gas industry to reap enormous benefits in the short-term as well as the medium and long-term. Oil and gas companies should start analysing and implementing these new and potentially disruptive technologies to remain competitive.