Quantifying tubing defect severity

Patent metadata

Field	Value
Publication number	US-2018266992-A1
Application number	US-201515534709-A
Country	US
Kind code	A1
Filing date	Dec 11, 2015
Priority date	Dec 11, 2014
Publication date	Sep 20, 2018
Grant date	—

Abstract

A technique facilitates examination of a tubing string which may comprise coiled tubing or other types of pipe. The technique involves evaluation of defect severity as it relates to tubing fatigue life reduction. A sensor may be positioned to monitor a pipe for a magnetic flux leakage signal indicating a defect in the pipe. The sensor outputs data on the magnetic flux leakage signal to a data processing system. The sensor data is used by the data processing system to identify the defect type via computer modeling, e.g. by utilizing a benchmark defect library, and to determine its relationship with respect to pipe fatigue life.

First claim

What is claimed is:

1 . A method for examining a tubing string, comprising:
providing a sensor to monitor a pipe for a magnetic flux leakage signal indicating a defect in the pipe; outputting data on the magnetic flux leakage signal detected by the sensor to a data processing system; using correlations between magnetic flux leakage signals and defect severity to automatically predict a fatigue life of the pipe via the data processing system based on the data detected by the sensor; and selecting an operation with respect to the pipe which is appropriate given the determined fatigue life.

2 . The method as recited in claim 1 , wherein using comprises using correlations between a magnetic flux leakage intensity and a fatigue life ratio.

3 . The method as recited in claim 2 , wherein using comprises using an intermediate parameter to construct magnetic flux leakage intensity and the fatigue life ratio relationships.

4 . The method as recited in claim 3 , wherein using the intermediate parameter comprises using a geometrical severity parameter.

5 . The method as recited in claim 1 , wherein using comprises identifying the type of defect through defect matching with defects stored in a memory associated with the data processing system.

6 . The method as recited in claim 1 , wherein using comprises evaluating the fatigue life as a function of the fatigue life of the pipe without the defect.

7 . The method as recited in claim 1 , wherein providing comprises providing the sensor to monitor coiled tubing.

8 . The method as recited in claim 1 , wherein selecting comprises using the data processing system to automatically recommend a future action with respect to the pipe.

9 . The method as recited in claim 1 , further comprising storing data on the correlations between magnetic flux leakage signal and the corresponding type of defect in the defect library.

10 . A method, comprising:
using a sensor to monitor coiled tubing for the presence of a magnetic flux leakage signal indicative of a defect in the coiled tubing; outputting data from the sensor to a data processing system having a processor; providing the data processing system with correlations between the magnetic flux leakage signal intensity and a fatigue life ratio; processing the data from the sensor regarding the magnetic flux leakage signal and from a benchmark defect library, via the data processing system, to determine magnetic flux leakage intensity; predicting a fatigue life based on the corresponding defect severity; and taking an action with respect to future use of the coiled tubing based on the fatigue life.

11 . The method as recited in claim 10 , wherein taking the action comprises pulling the coiled tubing from service.

12 . The method as recited in claim 10 , wherein taking the action comprises repairing the coiled tubing.

13 . The method as recited in claim 10 , wherein processing the data comprises detecting fatigue life ratio, wherein fatigue life ratio comprises a ratio of fatigue life of a pipe with a defect over fatigue life of the pipe without the defect.

14 . The method as recited in claim 10 , wherein processing the data comprises using an intermediate parameter to construct magnetic flux leakage intensity and fatigue life ratio relationships.

15 . The method as recited in claim 10 , further comprising supplementing the benchmark defect library with data obtained during evaluation of coiled tubing.

16 . The method as recited in claim 10 , wherein using comprises using a plurality of magnetic flux leakage sensors.

17 . The method as recited in claim 10 , further comprising using the processing system to output data related to fatigue life on a computer display.

18 . A system for defect evaluation, comprising:
a sensor positioned along a pipe to monitor for a magnetic flux leakage signal associated with a defect in the pipe; and a data processing system coupled to the sensor, the data processing system comprising:
a display;
a memory in which a benchmark defect library is stored; and
a processor which uses a computer model to determine correlations between data stored in the benchmark defect library and magnetic flux leakage signals obtained via the sensor to determine a defect severity, the defect severity being associated with a fatigue life which is output to the display.

19 . The system as recited in claim 18 , wherein the pipe comprises coiled tubing.

Assignees

• Schlumberger Technology Corp

Inventors

• Liu Zhanke
• Zheng Shunfeng
• Rivas-Diaz Oscar
• Hauglund Loren

Classifications

• G01R33/02

  Measuring direction or magnitude of magnetic fields or magnetic flux (G01R33/20 takes precedence) · CPC title

• G01R33/10

  Plotting field distribution {; Measuring field distribution} · CPC title

• G01N27/83

  by investigating stray magnetic fields · CPC title

• G01N27/82 Primary

  for investigating the presence of flaws · CPC title