Stuck-Pipe Prediction With Automated Real-Time Modeling and Data Analysis

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A real-time method is presented to predict impending stuck pipe with sufficient warning to prevent it. The new method uses automated analysis of real-time modeling coupled with real-time-data analysis. It can be applied to all well types for any well operation. The new method combines two types of analysis: (1) deviation of real-time data from real-time model predictions by use of hydraulics and torque-and-drag software, and (2) trend analysis of real-time data.

Data Types and Frequency

The approach taken was to first study real-time data sets from wells in which stuck-pipe incidents occurred and determine the root cause of each. The majority of these wells were drilled between 2009 and 2013 in the Eagle Ford shale. Specific patterns in the data were then identified as potential leading indicators of stuck pipe.

One of the first issues identified was that the type, frequency, and quality of data available are not consistent from well to well. To ensure that the alerting system was configured to work on different well types with a high degree of functionality, the decision was made that it would be designed to monitor a well and provide alerts even if only “critical” data streams are available.
 

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 178888, “Stuck-Pipe Prediction Using Automated Real-Time Modeling and Data Analysis,” by Kent Salminen, SPE, Curtis Cheatham, SPE, Mark Smith, SPE, and Khaydar Valiulin, SPE, Weatherford, prepared for the 2016 SPE/IADC Drilling Conference and Exhibition, Fort Worth, Texas, USA, 1–3 March. The paper has not been peer reviewed.
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Stuck-Pipe Prediction With Automated Real-Time Modeling and Data Analysis

14 May 2016

Volume: 68 | Issue: 6

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