As digital technologies make deep inroads into the oil and gas industry, the concept of a ‘digital twin’ is coming under the spotlight as a significant driver of business value. Though coined in 2002 and applied by NASA for its space missions since 2010, the concept’s popularity in the business world is a recent phenomenon.
The ascendance of technologies such as Internet of Things (IoT), data analytics, artificial intelligence (AI) played a key role in bringing the concept to the forefront of business operations and planning, effectively becoming a mainstream topic. The global digital twin market was valued at USD $3.8bn in 2019 and is expected to reach USD $35.8bn by 2025. Gartner predicts that half of all large companies will use some form of one by 2021 – resulting in a 10% improvement in effectiveness.
Fundamentally, a digital twin is a 360-degree digital or virtual copy of a physical asset or product with real-time, two-way communication between the physical and virtual worlds. The digital replica converges geometry, asset information and real time process data of the physical asset/product to create a dynamic, engineering-led business system. This enables companies to optimise operating processes and improve capital investments in the virtual world before applying them in the physical one.
The digital twin has a role to play virtually in every step of the asset lifecycle – from immersive technology in the design phase, to informing the supply chain in the operations phase. In the oil & gas industry, digital twins can be used to simulate ‘what-if’ or ‘what-will’ scenarios to ultimately raise asset productivity, reliability and performance. It enables owners-operators to gather real-time data feeds from sensors in an operational asset to know the exact state and condition, no matter where it is located. They can model drilling and extractions to determine whether virtual equipment designs are feasible. And most important, digital twins can help detect early signs of equipment failure or degradation and move from reacting and responding to a failure to being proactive, which enables planning and implementing corrective maintenance actions before failure occurs and often at much lower cost.
Given the above, the digital twin has a direct impact on the industry’s digital transformation agenda. On the flip side, there is no question that it requires additional investment, and not all operators will find it feasible to build a digital twin from scratch and incur all related costs upfront. Costs of developing digital twins will also increase in line with the maturity level of information that’s known about a physical asset and its environment. A more feasible approach would be to look at the digital twin as a roadmap, which can yield increasing financial benefits throughout its evolution. Delivering some tangible benefits in line with the maturity level will reduce uncertainty about the big gains to be made further down the evolutionary path. SNC-Lavalin works closely with oil and gas operators in the Middle East to assess organisation's digital twin maturity level and develop a master digital twin that covers drilling, design, construction, operations, production, sales and analysis activities.
Financially, the value of digital twin data should be recognised on the balance sheet, alongside the asset it “twins”. Return on Investment (ROI) is typically calculated by attributing costs to increases in production either by increased throughput or reduced downtime. According to GE Digital, the use of digital twin has seen customers increase reliability from 93% to 99.49% in less than two years, reduce reactive maintenance by 40% in less than one year, contributing to significant maintenance cost savings, and save $360,000 by predicting a power outage in a gas plant.
Beyond the technical challenges, the oil and industry will need to review its work processes to align with new technology tools. For this reason, operational change management remains a key component in the successful implementation of any digital transformation project, and the digital twin is no exception.
The digital twin concept is implicitly built upon a common data environment (CDE), a single source of the truth, where data is the centre of knowledge. While one can start from scratch in greenfield sites, for brownfield sites, it may not be commercially viable to create a wholly new digital twin CDE. In these cases, the more viable option is to build new data sources where needed and create gateways from existing data systems that will allow gathering data together from disparate siloes to create a pseudo CDE.
Undoubtedly, digital twins are an imperative in achieving operational excellence in the oil and gas industry. It is equally important, however, not to get distracted by the hype but to establish a framework that clearly defines goals and outcomes. The digital twin roadmap must focus on creating business value at every step, through better integration across various technical disciplines, organisational functions and key players in the value chain.