Abstract
Abstract
The industry is undergoing a transition into efficient technologies and it has digitalization written all over it. Digitalization not only should be about data, a fancy software, touchscreens and the internet, it is important that solutions are able to connect within existing work processes and with people for companies to truly lead to more efficient and safer drilling operations.
Oil and gas industries are now moving towards using Digital Twin's during the life-cycle of well construction. The concept of Digital Twins was first introduced by Dr. Michael Grieves at the University of Michigan in 2002 through Grieves’ Executive Course on Product Lifecycle Management. Digital Twin is a digital copy of the physical systems and act as a connection between physics and digital world. The digital system gets the real-time data from the mechanical systems which include all functionality and operational status of the physical system. An example from another industry; A Formula 1 team uses data from many sensors used in the car, harnessing data and using algorithms to make projections about what's ahead, and apply complex computer models to relay optimal race strategies back to the driver. Ultimately, to drive faster and safer.
By means of the digital twin of the drilling wells during the life cycle of the drilling by combining digital and real-time data together with predictive diagnostic messages there is seen a lot of advantageous in the improvement of accuracy in decision making and results. This again will help the industry to increase safety, improve efficiency and gain the best economic-value-based decision. A Digital Twin driven by real-time data helps to give operations the optimal plan with focus on safety, risk reduction and improved performance.
In this paper, the concept will first be explained in creating and utilizing a Digital Twin of your well for drilling and how it will directly influence how Drilling/well engineers, managers and supervisors plan, prepare and monitor their drilling operations and then implement learnings on future wells; for faster and improved decision making with direct relation to predicting and avoiding/mitigating NPT while also optimizing operations along with it. Case examples will be shared, showing value from use of the Digital Twin from first introduced in 2008 up until now where operators around the globe have implemented it for multiple uses in the drilling lifecycle.
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