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Condition monitoring techniques for geothermal well casings

Overview

Geothermal wells capture energy from the earth and could be an extremely efficient way to address climate change.  Adequate inspection of the well casings, which are essentially large diameter pipes, is a key part of well management.  Existing techniques include mechanical integrity testing, pressure and temperature monitoring, underground water sampling and distributed temperature sensing.  All these techniques are used either for monitoring of a specific part of a borehole or for generic well monitoring.  There are several advantages to using condition monitoring techniques to increase the lifetime of the equipment through early detection and therefore lower maintenance costs.

TWI is involved in the collaborative project Science for Clean Energy (S4CE), which includes 22 partners from nine countries whose aim is to address different subjects such as carbon sequestration and geothermal energy, with a view to reducing the carbon footprint of our expanding society.

Objectives

TWI’s role is to identify the most appropriate technique or combination of techniques for monitoring geothermal well casings.  The condition monitoring techniques being assessed are:

  • Acoustic emission(AE)
  • Guided wave(GW)
  • Vibration analysis(VA)

The objective is to identify any failure, well in advance of it happening and consequently avoid catastrophic failure.

AE experiment on a typical production casing
AE experiment on a typical production casing

Solution

AE testing was performed on a production steel casing from a geothermal field site in Cornwall and on a pipe covered with concrete.  GW was deployed on the same concrete pipe with the aim of comparing the two methods.  Finite Element Analysis was performed for a typical production steel casing in order to examine the ability of guided waves to travel along different layers of steel and concrete.  VA was carried out on the same production steel casing using a hammer to simulate a crack.

The results have shown that for AE, the attenuation rate is very promising in terms of the possibility of identifying the crack while it is being developed.

GW deployed on the concrete pipe unveiled a higher attenuation rate but still acceptable for the purpose of this application.  Finally, for VA performed on the production steel casing, a much higher attenuation rate was obtained compared with AE and GW, particularly for higher amplitude stimuli.

Conclusion

Based on the promising attenuation rate for AE and GW, TWI is currently finalising a system which features the capability of both techniques for casing monitoring in the same platform.  The system’s software will be responsible for managing the data acquired during AE and GW experiments.  These data will be processed using an appropriate signal processing algorithm, which will ultimately target the identification of a casing failure, well in advance of it propagating through the structure.

This project has received funding from the European Union’s H2020 research and innovation programme under grant agreement number 764810.

GW experiment on a pipe covered with concrete
GW experiment on a pipe covered with concrete
Avatar Sofia Sampethai Project Leader - Condition and Structural Health Monitoring

Sofia is a Project Leader at TWI in the Condition and Structural Health Monitoring section. She is a Chartered Engineer and a Member of the Welding Institute. She has studied Chemical Engineering and her MSc was carried out at ETH Zurich in the department of Process Engineering. Sofia manages funded collaborative projects, including Innovate UK, FP7 and H2020, and the majority of them are in the areas of condition monitoring, sensor development targeting composites failure, and integrity monitoring for casings used in oil and gas industry. She has also been involved in proposal writing for European and national funded projects, and in developing partnerships within industry. Sofia’s work is focused on the research and development of innovative solutions in the area of condition and structural health monitoring.

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