Rotating Control Device Wear Prediction for Closed-Loop Drilling
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Solution Overview
Problem
Closed-loop drilling operations face challenges in maintaining optimal wellbore pressure and reducing rotating control device (RCD) failure, leading to non-productive time and reduced average rate of penetration (ROP) due to the RCD's inability to maintain a consistent seal and pressure balance.
Innovation Solution
A method that uses sensors to monitor RCD conditions and predict wear estimates, combined with dynamic input parameters, to optimize the ROP by adjusting controllable parameters such as weight on bit, rotary speed, and pump flow rate, minimizing RCD failure through derivative-free optimization solvers and machine learning algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the RCD operates continuously to maintain seal and pressure balance, then the instantaneous rate of penetration is maximized, but the RCD wear increases leading to device failure
Solution Approach 1:
The system performs preliminary wear assessment using sensor measurements and prediction models to forecast RCD condition before failure occurs. This allows operators to take preventive action by adjusting drilling parameters or replacing the RCD before actual failure, thus maintaining high productivity while preventing reliability deterioration.
Solution Approach 2:
The system continuously monitors RCD condition through sensors and feeds this information back to the optimization algorithm. The feedback loop enables real-time adjustment of drilling parameters to balance productivity and reliability, maximizing instantaneous ROP while preventing RCD failure through continuous condition monitoring and adaptive parameter adjustment.
2Reliability
If the RCD is replaced frequently to prevent failure, then RCD reliability is maintained, but non-productive time increases reducing average rate of penetration
Solution Approach 1:
The prediction model assesses RCD wear in advance and provides early warning of potential failures. This allows operators to plan RCD replacement during scheduled maintenance windows rather than performing emergency replacements, thereby maintaining reliability while minimizing non-productive time associated with unexpected failures.
Solution Approach 2:
The system enables self-monitoring and self-diagnosis of RCD condition through integrated sensors and prediction algorithms. This autonomous condition assessment reduces the need for frequent manual inspections and proactive replacements, allowing the RCD to operate until actual wear thresholds are approached, thus reducing non-productive time while maintaining reliability.
3Productivity
If drilling parameters are optimized for maximum instantaneous ROP, then productivity increases, but RCD wear accelerates leading to increased failure risk
Solution Approach 1:
The system dynamically adjusts drilling parameters based on real-time RCD condition assessments. Instead of using fixed aggressive parameters that maximize instantaneous ROP but accelerate wear, the system adaptively modulates parameters like weight on bit and rotary speed according to the current RCD wear state, thereby optimizing the balance between productivity and service life extension.
Solution Approach 2:
The optimization algorithm changes operational parameters based on predicted RCD wear trajectories. When wear is predicted to be high, the system adjusts parameters to reduce stress on the RCD, extending its service life. When wear is low, parameters are optimized for maximum productivity. This dynamic parameter adjustment resolves the contradiction between instantaneous ROP and RCD service life.
Data Source
AI summary
A method for a well includes obtaining a dynamic input parameter combination for the well, determining measurements for a rotating control device using a sensor, and predicting a rotating control device wear estimate using rotating control device estimation methods, the measurements, and the dynamic input parameter combination. The method for a well further includes maximizing an instantaneous rate of penetration, while reducing rotating control device failure, to determine an optimized average rate of penetration using the rotating control device wear estimate. Finally, the optimized average rate of penetration is executed for a well.