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Assessment of the Subsurface Thermal Conductivity for Geothermal Applications

GeoVancouver - 69th Canadian Geotechnical Conference - CGS Colloquium
by

Jasmin Raymond

on 27 November 2017

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Transcript of Assessment of the Subsurface Thermal Conductivity for Geothermal Applications

Geothermal
system design
context
St. Lawrence Lowlands
Regional
scale
Urban district
scale
jasmin.raymond @ . ca
Assessment of the Subsurface
Thermal Conductivity for
Geothermal Applications

Geothermal Heat
Pump System

In Situ
Assessment

Laboratory
Analysis

Field Example
Ground Source
Heat Pump Systems
Heating
and
cooling
buildings
Shallow
subsurface <200 m depth
Energy
savings
~60%
Low carbon
footprint
Types of Ground Source Heat Pumps
~80% of installations in Canada
Heat exchanged by
conduction
Energy Piles
www.gscltd.co.uk
The Canadian Geothermal Market
Canadian GeoExchange Coalition (2012)
Installation of systems in Canada
Raymond et al. (2015, World Geothermal Congress)
Installed capacity
1 458 MWt
Energy used
11 338 TJ/yr
Ground source heat pumps
Classified according to the
ground heat exchanger
operation
System Design and Simulations
T
0
r
b
q
The Subsurface Thermal Conductivity
Host rock thermal conductivity distribution in Canada
Grasby et al. (2011, GSC 6914)
Assessment of the Subsurface Thermal Conductivity
in the Context of Geothermal System Design
Linked to the
building industry
Demand in the
multi-residential
,
institutional
,
commercial
and
industrial
sectors
www.ecb.europa.eu
New market for
geo-scientists
and
engineers
The
borehole length
(Lb) is
optimized
to fulfill the building energy needs
On Site Evaluation
of Subsurface Properties
An
exploration borehole
is drilled
A
pilot ground heat exchanger
is installed
The test can be carried with:
Active
methods
Passive
methods
Active Methods
Heat
is
injected
or extracted from the subsurface
Thermal equilibrium
is perturbed
Temperature evolution
is measured
Thermal conductivity
is inferred

Often called
Thermal response test
(Mogensen 1983)
Analogous to a
pumping test
(Theis 1935)
Raymond et al. (2011 Ground Water)
www.waterencyclopedia.com
Analysis of a Thermal Response Test
The
borehole temperature
(Tb) is
computed
to predict energy savings



Impacted by the
subsurface thermal conductivity
(ks)
Commonly achieved with the
infinite line source equation
The
superposition principle
can be used for
variable heat injection rates
or the
thermal recovery
T
0
q
Analysis of a Thermal Response Test
with interpretation of the thermal recovery
Raymond et al. (2011 Ground Water)
Raymond et al. (2011 Geothermics)
ks = 3.0 W/mK
Rb=0.065 mK/W
Distributed Thermal Response Test
Optical fibers
are used to measured downhole temperature (Fujii et al. 2006)
Data analysis provides a
thermal conductivity profile
Fujii et al. (2009 Geothermics)
Acuna (2013 PhD Thesis)
Power Requirements
30 to 80 W/m of borehole
4.5 to 12 kW
240 V / 30-60 A
To create a
temperature difference
of 3 to 7 °C between
inlet
and
outlet

Thermal Response Test with a Heating Cable
To
decrease power
requirement (<1.2 kW)
To
avoid fluctuations
in heat injection rate
Continuous
heating
cable
for short borehole
Heating
cable sections
for long borehole

Raymond et al. (2014 Geothermics)
Heating Cable Test Analysis
Infinite
line-source equation for a
continuous
heating
cable

Finite
line-source equation for heating
cable sections



Ideally based on
thermal recovery


Raymond et al. (2011 Geothermics)
T
0
q
ICS
ILS
FLS
H
Test with a Continuous Heating Cable
At experimental site
In the ground heat exchanger of a
direct exchange
system
Talaboulma (2013, Master Thesis)
Test with Heating Cable Sections
At experimental site
In a
single U-pipe
ground heat exchanger
Raymond et al. (2015, Applied Energy)
k
s
Passive Methods
Thermal conductivity is inferred from
borehole signals
(without heat injection)
Temperature profile
Geophysical well log
Rohner et al. (2015, World Geothermal Congress)
Grasby et al. (2011, GSC 6914)
Surface Heat Flow Distribution
Covering 40% of the Canadian territory
Numerical Inversion of Temperature Profile
Takes into account
paleoclimates
and
topography
Basal heat flow
inferred in a first borehole
Thermal conductivity extended
in next boreholes
Raymond et al. (2016, Renewable Energy)
Well Log Analysis
Log
signals
are
inverted
to infer the
mineralogy
and
porosity
of the formation
Thermal conductivity is calculated with
mixing models
GR-Gamma Ray; NPHI-Neutron density; D-Density, PEF-Photo electric; deltaT-Transit time (Naser et al., 2013, Master Thesis)
Thermal Conductivity
Analyses on Samples
From surface
outcrop
or
drilled core
Thermal
monitoring
experiment
is performed in the lab with:
Steady-state
methods
Transient
methods
Steady-State Method
Divided bar
Core plug
is placed between two zones of conductive material kept at
constant temperature
Temperature difference
across the sample is proportional to the thermal conductivity
Transient Method
Heat
is
injected
in the sample with:
Needle
probe
Plane
source
Temperature increments
are monitored to evaluate the thermal conductivity
www.labcell.com
www.ctherm.com
Steady-State VS Transient
Solid rock

Whole sample

Heterogeneous and homogenous materials
Friable or soft rock

Sample surface

Homogeneous materials
www.geology.com
www.geology.com
k
s
X-Ray Tomography
A tool to quantify
density distribution
and determine the appropriate method for thermal conductivity analysis
Homogeneity index
is calculated from X-ray images
Samples with homogeneity large index (>2500) are classified heterogeneous and unsuitable for transient thermal conductivity analysis

Comparison of Divided Bar and Transient Plane Source Analysis
10 sedimentary rocks
from the St. Lawrence Lowlands
Core plugs of
high quality
(parallelism of faces < 0.1 mm)
8 samples with
homogeneity index (H.I.) < 2250
showed
<12 % difference
in thermal conductivity analysis
Photography
X-ray
Photography
X-ray
H.I.=2613, 28 %
k
diff.
H.I.=3101, 24%
k
diff.
Subsurface Thermal
Conductivity Assessment Studies
The St. Lawrence Lowlands Sedimentary Basin
20 000 km in Québec
Undeformed
Cambro-Ordovician
platform

Thermostratigraphic Assessment
45 outcrop samples
Needle probe method

>4 W/mK
Potsdam Group and Theresa Formation
3 -4 W/mK
Beauharnois Formation, Queenston and Lorraine groups
<3 W/mK
Trenton, Black River, Chazy, Utica and Sainte-Rosalie groups
Geothermal Potential and Borehole Length
Sizing calculations for a residential system based on each sample

< 130 m
Potsdam Group and Theresa Formation
130 to 160 m
Beauharnois Formation, Queenston and Lorraine groups
> 160 m
Trenton, Black River, Chazy, Utica and Sainte-Rosalie groups
Cirois et al. (2015, AGU-GAC-MAC)
Cirois et al. (2015, AGU-GAC-MAC)
Comeau et al. (2012, INRS R001442)
Urban District Scale Assessment to the North of Montreal
4
thermal response tests
with a heating cable
10 l
aboratory measurements
with transient plane source
27
synthetic data
points from regional
thermostratigraphy
Work performed for
Stochastic Thermal Conductivity Distribution
Sequential Gaussian simulations to interpolate values
1) Method
2) Single realization
3) Mean of ten realizations
4) Variance of ten realizations
Alternatively, an
empirical relation
can be used to find the thermal conductivity
For example, in Postdam Sandstone λ
k
s
= 6.95 -0.026 *
GR
- 9.50 *
NPHI

Φ
GR-Gamma Ray; NPHI-Neutron density; D-Density, PEF-Photo electric; deltaT-Transit time (Naser et al., 2013, Master Thesis)
www.geotechenv.com
Inversion of Well Logs from a Oil Exploration Well
Public well log data available in the St. Lawrence Lowlands
For
deep geothermal
resource assessment
Inversion to find
mineralogy
Calculation of
thermal conductivity
with
geometric
average
www.prezi.com/user/jasminraymond
A Recent Field of Practice That Can Benefit From Geoscientific Knowledge
Next Step to this Research
Technology
improvement
Thermal conductivity measurement with X-ray and infrared scanners
Geothermal Open Lab
(CFI)
Regional
and
urban district
scale
mapping
of the subsurface thermal conductivity
Southern
populated regions with industrial partners
Northern
mines and communities to reduce fossil fuel consumption
INQ Research chair
Kuujjuaq
2
Colloquium Lecture Series
www.aaas.org/news
Full transcript