Spe 178888 Stuck Pipe Prevention

SPE 178888 Stuck Pipe Prediction Using Automated RealTime Modeling and Data Analysis Chuck Salminen, Curtis Cheatham, Mark Smith, Khaydar Valiullin; Weatherford

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Stuck Pipe: An Old Problem, But Still Relevant •

Project initiated in late 2014

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Drilling records indicated that stuck pipe was one of the leading causes of lost time

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With this in mind, stuck pipe prevention was selected as the first service to be developed

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Stuck Pipe Mechanisms

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Data Criteria and Parameter Selection •

Detection mechanism should be based on time-based drilling data

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Detection should be possible during all common drilling activities • 70% or more of stuck pipe incidents occur off-bottom

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Detection methods should utilize commonly available drilling data

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Success will be defined in two ways: • Successful detection of actual stuck pipe events with sufficient warning time • Minimization of false alarms

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Historical Data Analysis •

Thirty four (34) historical instances of stuck pipe were studied to determine root cause of each • Primarily in Eagle Ford Shale, USA • Most common mechanism is hole packoff due to wellbore instability or insufficient hole cleaning • Study showed that the behavior of “critical parameters” can reliably indicate impending stuck pipe

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Critical Parameters

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Detection Methods

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Depth-Based Threshold Determination

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Alert Criteria and Weighting •

Initial efforts used a “pass-fail” criteria • If deviation / rate of change is outside acceptable limit  generate an alert • This criteria is far too simplistic since: • It does not allow that one parameter may be out of range while others are not, possibly indicating that no problem exists • Significant violations of acceptable range are not given greater weight than small violations • A weighting system needed to be developed

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Depth-Based Threshold Determination

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Adaption to Time-Based Drilling Software •

New software system introduced significant improvements to modeling capability

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Real-time updates to SPP, Hookload, Torque, and ECD predictions based on actual drilling parameters

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On-the-fly custom calculations

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Adaption to Time-Based Drilling Software

Original depthbased threshold

Input parameter adjustment

Axial speed adjustment

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Case History 1: Stuck Pipe While Back Reaming Out of Hole

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Case History 2: Near Miss While Back Reaming Near TD

SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Summary, Next Steps, and Conclusions

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The method was found to be effective in detecting stuck pipe for a variety of well types, rig activities, and BHA configurations • In all cases where calculated risk exceeded 50%, a stuck pipe or near miss incident occurred within the next 2 hours • Future development will focus on automatic root cause determination SPE 178888 • Stuck Pipe Prediction Using Real-Time Modeling and Data Analysis • Chuck Salminen

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Questions?