Unlocking Operational Efficiencies for Milling Plugs in Large Monobore Completions Using Coiled Tubing with Real-Time Downhole Measurements - A Case Study from Offshore Middle East

Abstract

Abstract Coiled tubing (CT) milling of downhole plugs in large monobore completions is considered one of the most challenging CT workover operations, especially when conducted in offshore environments where intervention workflows are driven by efficiency gains for operators and service companies alike. Experience gained from milling operations using CT instrumented with real-time data enabled measurable improvements in efficiency. Post-job data analysis offered additional insights to improve methodologies and further unleash untapped efficiencies. Real-time bottomhole assembly data were collected during plug milling operations using a positive displacement motor. Critical downhole readings, such as CT internal and annular pressure, axial force (thrust), and torque were monitored during the operation to identify tagging of isolation plug targets, onset of milling, and stalls. The real-time data not only added confidence to event confirmation, but also increased the accuracy in estimating efficiency metrics such as rate of penetration (ROP) and stall recovery duration. Post-job analysis calculated the error and shortcomings associated with estimating event detection based on surface measurements. Additionally, error in event detection was tied back to inaccuracies in estimating efficiency metrics when relying on surface measurements alone. Analysis of downhole measurements in CT milling improves the precision of event detection and enables rapid reactions. Target tagging reflects instantly in thrust, and motor activation reflects synchronously in downhole differential pressures and torque, which together provide certainty of motor engagement on the target. Stalls reflect in differential pressure and torque spikes that coincide with motor specifications. ROP more than doubled by leveraging these event detection techniques throughout milling operations. New torque-thrust signatures were also identified to detect material interfaces. Changes in signature behavior indicated when the bit milled through one target and reached the next. This is particularly useful when the operator must mill through a target but stop at a subsequent, contiguous one. Post-job data also suggested that some events may have been mistaken as stalls during the operation, with downhole data confirming they were false positives. Finally, at operating conditions in the case study, a 7-second lead-time window was identified to anticipate and react to stalls. This highlights the importance of access to real-time downhole information, such as differential pressure, to avoid both stalls and false positives, and ultimately, to make breakthroughs in operational efficiency. Integrated analysis of downhole measurements during CT milling lent visibility to actual ROP, stall rates, and stall recoveries. These constitute important baselines against which any improvement in efficiency must be compared. The methodologies proposed here for event detection, with special attention to stall anticipation and milling interface detection, pave the way for smarter, more efficient operations.