Having a Digital Twin of the drilling well, pairing digital and physical data combined with predictive analytics and diagnostic messages, improves accuracy in planning and decision making of the drilling operation. It helps the industry to increase safety, improve efficiency and gain the best economic-value-based decision as well as reduce operational cost. Today advanced monitoring is normally done using real-time measurements, compare pre-simulation results with measurements, perform manual diagnostics and run new simulations when abnormalities are seen. All done manually by people.
Drilling can move beyond advanced monitoring using Digital Twin's by implementing automatic ‘forward-looking’ and multiple ‘what-if’ simulation to give operations the optimal plan with focus on safety, risk reduction and improved performance.
The Digital Twin examples in the current paper can do more advanced and complex automatic forecasting simulations, diagnostics, ‘forward-looking’ and ‘what-if’ simulation as well as predictive analytics in the wellbore in the 2D and 3D simulation view.
By using the advanced models (Digital Twin), all relevant challenges and risks were identified during the drilling operations of one well under high pressure high temperature (HPHT) conditions. The stand pipe pressure (SPP), equivalent circulating density (ECD) and temperature behavior were studied during the drilling and circulation of this well. The Digital Twin was also used to evaluate possible losses during 9 7/8″ casing running and cementing with special focus on when casing was passing through the formations. In another well the Digital Twin triggered an early notification regarding high cuttings concentration during drilling 8 ½″ section. The flow rate was adjusted and helped to prevent sidetrack and pack-off due to losses.
Morover during drilling 17 ½″ section in another case, large losses were prevented by comparing the modeled active pit calculation and measured tank volume. The Digital Twin enables advanced automatic forecasting simulation, self-diagnostics, automatic ‘forward-looking’, multiple ‘what-if’ simulation and predictive analytics to improve safety, reduce risk, increase drilling performance and reduce costs.