Identifying Small Leaks with Ultrasonic Leak Detection-Lessons Learned in Alaska

Author:

Julian J. Y.1,Duerr A. D.2,Jackson J. C.3,Johns J. E.4

Affiliation:

1. BP

2. ASD

3. University of Alaska

4. Archer, Inc

Abstract

Abstract Detection of very small tubing leaks (less than one gpm) is difficult using conventional logging techniques such as spinners and temperature logs. Leak identification is an even greater challenge for leaks behind tubing. Ultrasonic leak detection was introduced in 2005 to Alaska, and 260 logs have been run to date with an 88% success rate. Leak identification has been accomplished in wellheads, tubing, tubing connections, jewelry, gas lift mandrels, packers and production casing. Development of this tool to be conveyed on memory with wireline and coiled tubing has resulted in cost savings due to rig up efficiencies. It has also led to additional opportunities for logging higher pressure wells in which it is difficult to maintain a pressure seal with electric line. The ultrasonic logging tool incorporates data acquisition equipment and filtering algorithms which allow continuous logging, filtering out the "road noise" of the tool as it travels up and down the wellbore. This advantage makes it far superior to old-style noise logs which require time consuming stationary counts. Ultrasound energy attenuates very rapidly, but has the ability to transmit through tubulars, wellbore fluids, and cement. These two attributes allow pinpoint accuracy for leaks as small as 0.005 gallons per minute (gpm) even behind multiple strings of tubulars. The advantage of finding small leaks is that once the leak is identified, the well can often be remediated without the use of a rig at a fraction of the cost. Application of this tool has great significance for any operator concerned with well integrity, and particularly, in areas where rig workovers are expensive, including remote, offshore, and arctic locations. This paper discusses the history and success rate of jobs performed to date in Alaska. It provides success statistics for both real-time and memory mode, and details non-rig remediation success and lessons learned in field operations.

Publisher

SPE

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on Downhole Tubing Leakage Identification Method Based on Extreme Learning Machine;2023 5th International Communication Engineering and Cloud Computing Conference (CECCC);2023-10-27

2. An Assessment of Seal Ability of Tubing Threaded Connections: A Hybrid Empirical-Numerical Method;Journal of Energy Resources Technology;2022-12-27

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