2019
DOI: 10.3390/geosciences9100440
|View full text |Cite
|
Sign up to set email alerts
|

Dipole and Convergent Single-Well Thermal Tracer Tests for Characterizing the Effect of Flow Configuration on Thermal Recovery

Abstract: Experimental characterization of thermal transport in fractured media through thermal tracer tests is crucial for environmental and industrial applications such as the prediction of geothermal system efficiency. However, such experiments have been poorly achieved in fractured rock due to the low permeability and complexity of these media. We have thus little knowledge about the effect of flow configuration on thermal recovery during thermal tracer tests in such systems. We present here the experimental set up … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
6
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
4

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(6 citation statements)
references
References 49 publications
0
6
0
Order By: Relevance
“…Following the observations of breakthrough curve tailing, two different conceptual models for the fracture geometry are tested: the parallel plate model and the channel model (Figure S5). The analytical solutions described by De La Bernardie (2018) and De La Bernardie et al (2018, 2019) based on Laplace transforms (Text S2) are used. These Laplace transform solutions are inverted using the algorithms from Hoog et al (1982) and Hollenbeck (1998).…”
Section: Resultsmentioning
confidence: 99%
“…Following the observations of breakthrough curve tailing, two different conceptual models for the fracture geometry are tested: the parallel plate model and the channel model (Figure S5). The analytical solutions described by De La Bernardie (2018) and De La Bernardie et al (2018, 2019) based on Laplace transforms (Text S2) are used. These Laplace transform solutions are inverted using the algorithms from Hoog et al (1982) and Hollenbeck (1998).…”
Section: Resultsmentioning
confidence: 99%
“…Equation (3) can be used to express the thermal power, individually for the injection and pumping points, by dividing the thermal energy change by the corresponding injection and observation time, respectively. For fractured rocks, the thermal recovery rate r thermal ( t ) expresses the relation between the injection power P in and the instantaneous recovery power P ( t ) (Equation 4) (de la Bernardie et al 2019): rthermal(t)goodbreak=P(t)Pingoodbreak=Ethermal(t)tEinjectedtinjectiongoodbreak=cwρw(T)0.25emQoutflowcwρw(T)0.25emQinflowT(t)false(TinjectionTBackgroundfalse) where P ( t ) is the instantaneous recovery power (W); P in is the injection power (W); Q inflow is the water injection flow rate (m 3 s −1 ); Q outflow is the water extraction flow rate (m 3 s −1 ); T injection is the temperature of the injected water (°C); and Tfalse(tfalse) is the temperature difference (Equation 1) (°C or K).…”
Section: Methodsmentioning
confidence: 99%
“…Consequently, solutions based only on the advection–dispersion equation can have limited prediction capabilities for transport in fractured rocks (e.g., Bodin et al 2003 ). Recent studies using stronger diffusing tracers such as dissolved gases (Hoffmann et al 2020 ) or heat (Read et al 2013 ; Klepikova et al 2016a ; de la Bernardie et al 2018 ; de la Bernardie et al 2019 ; Hoffmann et al 2021 ) have shown a potential to better constrain fractured aquifer conceptualizations with matrix diffusion information. Although reliable temperature tracer experiments have been performed in porous alluvial aquifers (Wagner et al 2014 ; Wildemeersch et al 2014 ; Klepikova et al 2016b ; Sarris et al 2018 ) and fractured porous media (Read et al 2013 ; Klepikova et al 2016a ; de la Bernardie et al 2018 ; de la Bernardie et al 2019 ; Hoffmann et al 2021 ), temperature information is still rarely analyzed by hydrogeologists, because dilution is high (Kurylyk and Irvine 2019 ) and the signal may be difficult to detect.…”
Section: Introductionmentioning
confidence: 99%
See 2 more Smart Citations