Real-Time Reamer Vibration Predicting, Monitoring, and Decision-Making using Hybrid Modeling and a Process Digital Twin

Abstract

Abstract In hole enlargement while drilling (HEWD) operations, reamers are extensively used to enlarge the pilot hole. Reamer wipeout failure can cause additional bottom hole assembly (BHA) trips, which can cost operators millions of dollars. Excessive reamer shock and vibration is a leading cause of reamer wipeout; therefore, careful monitoring of reamer vibration is important in mitigating such a risk. Currently, downhole vibration sensors and drilling dynamics simulations are used to comprehend and reduce downhole vibration, but vibration sensors cannot be placed exactly at the reamer to monitor the vibrations in real time. Drilling dynamics simulations are difficult to calibrate and are computationally expensive for use in real time; therefore, the real-time reamer vibration status is typically unknown during drilling operations. A process digital twin using a hybrid modeling approach is proposed and tested to address the vibration issue. Large amounts of field data are used in advanced drilling dynamics simulations to calibrate the HEWD runs. For each HEWD section, calibrated drilling dynamics simulations are performed to comprehend the downhole vibration at the reamer and downhole vibration sensors. A surrogate regression model between reamer vibration and sensor vibration is built using machine learning. This surrogate model is implemented in a drilling monitoring software platform as a process digital twin. During drilling, the surrogate model uses downhole measurement while drilling (MWD) data as input to predict reamer vibration. Wipeout risk levels are calculated and sent to the operators for real-time decision making to reduce the possibility of reamer wipeout. Large volumes of reamer field data, including field recorded vibration and reamer dull conditions were used to validate the digital twin workflow. Then, the process digital twin was implemented and tested in two reamer runs in the Gulf of Mexico. A downhole high-frequency sensor was placed at the reamer in one field run and the recorded sensor vibration data and corresponding reamer dull conditions showed a very good match with the real-time digital twin predictions. The field tests demonstrated the feasibility and accuracy of the digital twin and established a method for aiding in future real-time decision making. State-of-the-art downhole sensors, drilling dynamics simulation packages, large amounts of field data, and a hybrid approach are the solutions to building, calibrating, and field testing the reamer digital twin to ensure its effectiveness and accuracy. Such a hybrid modeling approach can not only be applied to reamers, but also to other critical BHA components.