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New Methods to Spatially Extend Thermal Response Test Assessments
This document describes two new methods for spatially extending thermal response test (TRT) assessments: 1) Inverse numerical modeling of temperature profiles from multiple boreholes at a site can be used to evaluate subsurface thermal conductivity beyond a single TRT well. 2) At a district scale, geostatistical simulation using thermal conductivity data from outcrops, boreholes, and multiple TRTs can provide stochastic realizations of subsurface properties to spatially interpolate between test locations. Both methods allow TRT assessments to be expanded beyond their typical limited spatial scope, creating new opportunities for evaluating ground source heat potential.
New Methods to Spatially Extend Thermal Response Test Assessments
- 1. 1 IGSHPA Technical /Research Conference and Expo 2017 Denver, Colorado March 15th, 2017 jasmin.raymond@inrs.ca New Methods to Spatially Extend Thermal Response Test Assessments Jasmin Raymond, Michel Malo, Louis Lamarche, Lorenzo Perozzi, Erwan Gloaguen & Carl Bégin
- 2. 2 Thermal response test(TRT) Raymondetal.2011.Groundwater • Evaluation of the subsurface thermal conductivity • To design ground coupled heat pump (GCHP) systems • Single test commonly carried out for a commercial size system • Limited use because of important cost
- 3. 3 TRT radius ofinfluence Raymond et al. 2014. ASHRAE Trans. • Limited to ~1 - 2 m • Heterogeneous subsurface
- 4. 4 How to extendTRT assessment beyond a single well? 1) Inverse numerical modeling of a temperature profile – site scale, large project 2) Geostatistical simulation – district scale, many small projects
- 5. 5 1) Site scaleextrapolation of thermal conductivity Validated at an experimental site with 2 boreholes Versaprofiles test site
- 6. 6 Measurement of temperatureprofiles Submersible pressure and temperature probe Depth compensated by the rise in water level inside the U-pipe 𝐷∗ (𝐿) = 𝐷 − 𝑉logger + 𝑉wire(𝐿) 2𝜋𝑟pipe,in 2
- 7. 7 Numerical model development Transientconductive Heat transfer t T c y T λ yx T λ x
- 8. 8 PG-08-01: Evaluation ofthe Earth heat flux with inverse numerical simulations λ = 3.0 W/mK (TRT) Squared residuals are minimized to find q
- 9. 9 PG-08-02: Evaluation ofthe subsurface thermal conductivity with inverse numerical simulations q = 25 mW/m2 (inversion) Squared residuals are minimized to find λ
- 10. 10 Inverse numerical simulationsto extent TRT assessment Raymond et al. 2017. Renewable Energy λ inversed = 3.2 W/mK λ TRT = 3.5 W/mK
- 11. 2) District scaleextrapolation of thermal conductivity Geothermal potential of an urban area with multiple projects 11 350 km2 zone in the northern part of Montreal Perozzi et al. 2016. R1663
- 12. 4 TRTs witha heating cable 12 Wireless hub Wireless switch Variable transformer Intelligent power meter To power supply To heating cable
- 13. TRT analysis example 13 ∆𝑇(𝑡) ∆ln(𝑡) = 𝑄 4𝜋λs 𝐻 Q = V𝐴 Infinite line source equation with the temporal superposition principle for the recovery period Slope method ∆𝑇(𝑡c, 𝑡h) ∆ ln( 𝑡c + 𝑡h 𝑡c ) = 𝑄 4𝜋λs 𝐻 Test 3 Thermal conductivity (W/mK) Depth(m) Overburden Bedrock
- 14. 14 10 lab measurementson outcrop samples Transient plane source method ctherm.com
- 15. 15 Measurements summary Latitude Longitude Thermal conductivity (W/mK) Thermostratigraphicunit Measurement type 45.519249 -73.652824 2.10 T-BR-C Outcrop/TPS 45.519249 -73.652824 2.22 T-BR-C Outcrop/TPS 45.547637 -73.696752 2.90 T-BR-C Outcrop/TPS 45.60307 -73.656963 2.90 T-BR-C Outcrop/TPS 45.604803 -73.659649 3.15 T-BR-C Outcrop/TPS 45.605735 -73.661411 2.31 T-BR-C Outcrop/TPS 45.60307 -73.656963 2.60 T-BR-C Outcrop/TPS 45.602381 -73.658056 2.93 T-BR-C Outcrop/TPS 45.50964 -73.627682 2.24 T-BR-C Outcrop/TPS 45.604803 -73.659649 2.16 T-BR-C Outcrop/TPS 45.511454 -73.6518 2.39 T-BR-C Borehole/TRT cable 45.504581 -73.65772 2.39 T-BR-C Borehole/TRT cable 45.516988 -73.648486 2.81 T-BR-C Borehole/TRT cable 45.527392 -73.855424 4.20 Beauharnois Borehole/TRT cable
- 16. 16 Synthetic data 45 measurements atthe sedimentary basin scale Thermostratigraphy of the St. Lawrence Lowlands Average thermal properties Thermal conductivity (W/mK) Thermostratigraphic unit N Average Standard deviation Trenton, Black River, Chazy 23 2.67 0.44 Beauharnois 6 3.40 0.55 Raymondetal.2017.EnvironmentalEarthSciences
- 17. 17 Sequential Gaussian simulations Toevaluate the spatial distribution of the host rock thermal conductivity 35 000 pixels 100 m × 100 m
- 18. 18 Single stochastic realization Perozziet al. 2016. R1663
- 19. 19 Mean of 10stochastic realizations Perozzi et al. 2016. R1663
- 20. 20 Perozzi et al.2016. R1663 Standard deviation of 10 stochastic realizations
- 21. 21 Conclusions Two methods areproposed to extend TRT assessments: • Inverse numerical modeling of temperature profiles to extend at the site scale beyond a first TRT • Geostatistical simulations to interpolate TRT assessments at the district scale Can create new opportunities for TRT assessments!
- 22. 22 Past and currentTRT research - Field and analytical methods The next challenge - Spatial limitation Conclusions