Oil and Gas Digital Twin
In this white paper, Richard Black, Director Engineering Operations, reveals the best emerging practices within oil and gas firms.
Please click on the video to the right to learn more about the author, his paper’s key points, and his motivation for writing on this subject.
To discuss this white paper in more detail, please contact the author using the information provided at the bottom of the page.
Vee Technologies has already seen the benefits of digital twin modeling within the energy modeling world, but it is becoming beneficial to other disciplines throughout engineering. The digital twin is a virtual representation of any existing object or process and analyzes the data and any other systems involved as a brand-new concept before they have ever happened. It is a link between both the physical and digital world. It allows simulations and predictions to be made on any physical object by adjusting inputs and acting out various scenarios.
With the industry at the forefront of technology that already works with dynamic software models, oil and gas can take advantage of this concept, both in ensuring efficient and safe ongoing operations and in designing new techniques and facilities. Gartner predicts that In the near future, half of large industrial companies will use digital twins, resulting in those organizations gaining a 10% improvement in effectiveness.1.
Cloud computing, advanced simulation, virtual system testing, virtual/augmented reality and machine learning will all progressively merge into full digital twins which combine data analytics, real-time and near-real-time data on installations, subsurface geology, and reservoirs.
Several best practices in this area are emerging among the major engineering and oil and gas firms:
Digital twins can help companies optimize the following value drivers: capital expenditure reduction, time-to-first-oil acceleration, recovery rate increase, production acceleration, and operating expense reduction, with both health and safety and environmental improvement.
Uses vary both during the project life cycle and during the upstream, midstream and downstream environment.
Digital twins can enable automatic improvements and decision making (for example, by using an algorithm to alter valve settings).
Customer value can be created through quicker response times, deeper insights into how to optimize production and maintenance, and a more integrated service. A fully integrated digital twin could simulate hydrocarbon flows from the reservoir to the receiving facility using real-time data. This would provide the operator with a bird’s-eye view of flows throughout the pipeline at any time.
For new developments, companies can use digital twins to make better use of capital and accelerate the time to first oil. Digital twins allow work once done offshore to be moved onshore, eliminating the need to mobilize offshore to see and inspect the asset. This reduces the number of personnel mobilizing offshore, resulting in lower emissions and the cost of executing work.
In 2017, BP attributed more than 30,000 additional barrels to optimization efforts from its digital twins. Much of this increased production came from simulations, using digital twin data to anticipate well yields.
There is a digital twin of a gas-collection facility in snowy Alaska, used to plan maintenance, identify equipment for decommissioning and perform planning for equipment installation – all from the warmth and comfort of an offsite office.
While digital twins can consume a lot of time and a large amount of money to produce, once established they can save both by being a tool to run infinite scenarios without impacting the asset, not only in terms of real data entry but scenarios that would cause danger to personnel or even loss of life.
Any investment can quickly be recouped once the digital twin is up and running, sometimes in less than a year.
One word of warning, however. There is a lack of talent available to produce and maintain a digital twin. “. . millennials, projected to constitute most of the US workforce by the early 2020s, currently favor working in industries perceived to be "greener" than oil and gas.”2. This may mean that in order to get the right talent, the price of labor to maintain a digital twin is going to get more expensive as the current oil and gas talent pool ages.
Note 1. https://www.gartner.com/smarterwithgartner/prepare-for-the-impact-of-digital-twins/
Figure 1. https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9104682
Figure 2. https://www.bcg.com/publications/2019/creating-value-digital-twins-oil-gas
Note 2. https://www.bp.com/en_gb/united-kingdom/home/community/stem-education/stem-stories/creating-a-digital-mindset-in-the-oil-industry.html
Oil and Gas Digital Twin