Anomaly recognition system and methodology

Patent metadata

Field	Value
Publication number	US-9671371-B2
Application number	US-201414318187-A
Country	US
Kind code	B2
Filing date	Jun 27, 2014
Priority date	Jun 27, 2014
Publication date	Jun 6, 2017
Grant date	Jun 6, 2017

Abstract

A technique facilitates anomaly recognition and tracking in a variety of components, such as tubular components. The technique comprises sensing for anomalies in the component, and storing detected anomalies in a storage medium. The detected anomalies are matched with stored digital descriptions of anomalies. The stored digital descriptions may be anomalies of similar types and/or anomalies detected on the specific component being tested. The detected anomalies are ranked according to similarities with respect to the stored digital descriptions.

First claim

What is claimed is:

1. A method for anomaly recognition and tracking, comprising:
storing digital descriptions of anomalies in a digital storage medium;
providing a well component;
positioning an anomaly sensor adjacent the well component;
moving the well component and the anomaly sensor relative to each other to detect anomalies in the well component;
running an anomaly matching algorithm on a processor system to determine at least one matching coefficient between the anomalies in the well component and a digital description of the anomalies stored in the digital storage medium; and
ranking the matching coefficients to determine highly ranked matches between anomalies detected in the well component via the anomaly sensor and the digital descriptions of anomalies stored in the digital storage medium.

2. The method as recited in claim 1 , wherein storing comprises accumulating digital descriptions of anomalies during inspections of well components.

3. The method as recited in claim 1 , wherein storing comprises storing digital descriptions according to specific well components to enable monitoring of each specific well component used repetitively for multiple jobs.

4. The method as recited in claim 1 , wherein storing comprises storing digital pictures of anomalies.

5. The method as recited in claim 1 , wherein storing comprises storing magnetic flux leakage data profiles of anomalies.

6. The method as recited in claim 1 , wherein moving the well component comprises moving a well pipe past the anomaly sensor.

7. The method as recited in claim 1 , wherein moving the well component comprises moving a well pipe past the anomaly sensor as the well pipe is conveyed downhole into a wellbore.

8. The method as recited in claim 1 , wherein storing comprises storing at least an anomaly dimension or an anomaly orientation.

9. The method as recited in claim 1 , wherein running comprises determining matching coefficients regarding a similarity of the anomalies.

10. The method as recited in claim 1 , wherein ranking comprises outputting graphically both anomaly matches and match ranking.

11. A method for anomaly recognition and tracking, comprising:
providing a well tubular;
positioning an anomaly sensor adjacent the well tubular;
deploying the well tubular downhole into a wellbore
sensing for anomalies with the anomaly sensor as the well tubular is deployed downhole into the wellbore;
storing detected anomalies in a digital storage medium;
matching detected anomalies with stored digital descriptions of anomalies and with anomalies detected on the well tubular during a job run; and
ranking the detected anomalies according to similarities with respect to the stored digital descriptions of anomalies.

12. The method as recited in claim 11 , wherein positioning comprises positioning a magnetic flux leakage sensor adjacent the well tubular and wherein sensing comprises sensing using the magnetic flux leakage sensor to detect anomalies.

13. The method as recited in claim 11 , wherein storing comprises storing detected anomalies as additional stored digital descriptions to expand an anomaly library of stored digital descriptions.

14. The method as recited in claim 13 , wherein running comprises running a pattern matching algorithm to match signal patterns of anomalies detected from a job with signal patterns of anomalies already stored in the digital storage medium.

15. The method as recited in claim 11 , wherein ranking comprises outputting data to a user regarding matching and relative rankings of those matches.

16. The method as recited in claim 11 , further comprising tracking an anomaly progression for the well tubular as the well tubular is used over a series of jobs.

17. The method as recited in claim 11 , wherein sensing comprises sensing for anomalies in coiled tubing as the coiled tubing is deployed downhole.

18. The method as recited in claim 11 , wherein running further comprises tracking the progress of anomalies for a well component as the well component is used over a series of job.

19. A system for detecting anomalies, comprising:
a tubular deployment system to deploy a tubular downhole into a wellbore;
a sensor positioned along the tubular to monitor for anomalies related to the tubular;
a storage medium which stores digital descriptions of characteristics of anomalies; and
a processor to compare data from the sensor with the digital descriptions stored in the storage medium, the processor configured to output a ranking of comparisons to indicate a strength of a match between data from the sensor and the digital descriptions.

20. The system as recited in claim 19 , wherein the sensor is used to detect anomalies as the tubular is moving into or retrieved from a well bore.

Assignees

• Schlumberger Technology Corp

Inventors

• Liu Zhanke
• Zheng Shunfeng
• Zwanenburg Mirjam

Classifications

• G01N27/83 Primary

  by investigating stray magnetic fields · CPC title

• E21B19/22

  Handling reeled pipe or rod units, e.g. flexible drilling pipes {(lifting or hauling appliances using two or more cooperating endless chains B66D3/003)} · CPC title