{Increasing Operation Efficiency Using Digital Twin Technology}

Gazprom Neft saw the need to improve and increase production efficiency using new technologies and design solutions in the field. They found that data acquisition, engineering information processing, and analysis of the data would consume as much as 75% (or more) of the employees' time resources. 


Utilizing software solutions leveraging artificial intelligence was the solution to aid in decision making, as well as addressing routine task automation and cross-team collaboration. Applying digital representations or versions - digital twins - of their wells combined with predictive analytics and automated diagnostics, to obtain lasting, efficiency gains in hard-to-recover reserves development. 


Since the introduction of the Drilling Management Center, NPT has been reduced by 8-10%, and the drilling rate has improved by 20%.  For example, safer tripping and proper ECD management with fewer surge & swab incidents, as well as borehole stability issues were achieved. In addition, the digital twin gave control of the wellbore friction and back-reaming has helped to prevent pack-off situations.

300% increase in wells supported 

NPT reduced by 60%

Drilling rate improved by 20%

Zero sidetracks 

From 100 to 150 supported wells annually

By utilizing digital twin technology, DMC managed to increase the number of support from 100 to 150 annually with the same personnel count. This helps save rig costs by early risk detection and predictive analytics, enabling the drilling team to react quickly and make efficient decisions. By using what-if analysis, our software can simulate multiple scenarios in real time. 

The digital twin of the well is continuously updated by the real-time data from the rig. The principle is to enforce continuous optimization by using artificial intelligence and machine learning to provide diagnostic messages when abnormal activities are detected. Predictive analytics and forecasting have the main objective to cause awareness of upcoming risks, followed up by what-if analysis to optimize the operation. 

Artificial intelligence and predictive analytics provide the drilling team with a decision-making tool during planning and drilling operations. 

This is also a key enabler toward Automated Drilling Control.