Drilling in the Digital Age: Sensors in Bit and Underreamer Improves Future BHA Design Offshore Mexico

Abstract

Abstract Downhole vibration is the primary cause of low Rate of Penetration (ROP), and severe vibration causes Bottom Hole Assembly (BHA) tool failure; it is especially apparent during Hole Enlargement While Drilling (HEWD) due to multiple points of cutter contact with the formation at the bit and the underreamer. Electronic, high data rate sensors, embedded in the 17-1/2 in. bit and the 22 in. underreamer, generated detailed insights on the location, mechanism, and magnitude of downhole vibration. Time-based downhole vibration logs from the sensors were plotted alongside mudlogging data. Finite Element Analysis (FEA) models were run using actual drilling parameters to simulate downhole conditions and provide a baseline model for further optimization. Sensor data was isolated for each of the bit and underreamer to better understand the individual and combined vibration mechanisms during hole enlargement while drilling operations. The FEA model was then used to optimize BHA configuration and underreamer placement that result in the largest drilling parameter window for future BHAs. The data from sensors showed that whirl occurred when the bit entered sandstone bodies and the underreamer was still in shale. The data also showed that when the bit was in shale and the underreamer in sandstone, the underreamer experienced stick slip which induced stick slip at the bit. The BHA dynamics model run with actual drilling parameters showed a narrow drilling window with multiple critical vibration points at the same rotation speed (RPM). A new BHA was developed for the next well with a wider drilling window and less critical vibration points for the same RPM. The analysis identified key operational mitigations when stick slip or whirl are encountered. This work leveraged technology and insights generated from data to shorten the learning curve and improve operations after just one well. In a drilling age where operations are becoming increasingly complex, relying on surface data is no longer enough.