| Title | Modelling Thermal Response Tests for Deep Coaxial Borehole Heat Exchangers |
|---|---|
| Authors | Christopher S Brown, Isa Kolo, David Banks, Hannah R Doran, Gioia Falcone |
| Year | 2023 |
| Conference | World Geothermal Congress |
| Keywords | Thermal response test, deep borehole heat exchanger, Newcastle Science Central Deep Geothermal Borehole, Numerical Modelling |
| Abstract | Deep borehole heat exchangers (DBHEs) have been proposed as a method for repurposing petroleum and geothermal exploration wells for further use, yet, typically the in-situ rock properties may be poorly defined or not recorded. Therefore, thermal response tests (TRTs) can provide estimates of the subsurface radial thermal conductivity and borehole thermal resistance. This data can then be utilised to model the resource, determining the thermal capacity and potential. In this study, we focus on the capability of several modelling tools (T2Well-EOS1/TOUGH2, MATLAB and OpenGeoSys) to simulate thermal response tests and their ability to estimate subsurface parameters. The Newcastle Science Central Deep Geothermal Borehole was selected as a case study as plans are in place to carry out a TRT as a DBHE. The borehole was initially drilled as a geothermal exploration well targeting the Mississippian Fell Sandstone Formation; however, it proved to have low hydraulic conductivity and subsequently would not be suitable for development using conventional methods. The borehole was drilled to a total depth of 1821 m, but we regard only the top 922 m as being available for testing due to a 4.5 inch liner inserted below this depth meaning it is hydraulically unattractive to repurpose the well at depths exceeding the casing. In this study we are, therefore, able to compare data and model results from the case study to develop an understanding of subsurface characteristics. Model results show that the accuracy of thermal conductivity and thermal resistance estimates improve in comparison to model inputs with increased TRT time. The analytical solution estimate of thermal conductivity converges more quickly towards the true input value, compared to numerical modelling methods. |