Quantitative temperature monitoring of a heat tracing experiment using cross-borehole ERT
Graphical abstract
Introduction
Shallow alluvial aquifers constitute potential shallow geothermal energy reservoirs, relatively abundant and easily accessible. In these low temperature systems, groundwater has an average temperature ranging from 5 to 30 °C and may be used for domestic or industrial cooling and heating (Allen and Milenic, 2003, Haehnlein et al., 2010).
The two main techniques to exploit shallow geothermal energy systems are ground source heat pump (GSHP), which are closed systems with a vertical or horizontal heat exchanger, and groundwater heat pump (GWHP), which are open systems circulating groundwater between production and injection wells. Designing such systems requires a multidisciplinary approach including geological and hydrogeological aspects. The most common approach is to model the system using a coupled groundwater and heat flow simulator. However, such models require estimating parameters governing heat transport such as heat capacity, thermal conductivity and density. Due to a lack of data, authors often have to rely on standard calculation charts, values found in the literature or default values implemented in softwares (e.g. Busby et al., 2009, Lo Russo and Civita, 2009, Liang et al., 2011, de Paly et al., 2012). In situ tests, such as thermal response tests (Raymond et al., 2011, Mattsson et al., 2008), or laboratory measurements (e.g. Haffen et al., 2013) are sometimes possible but the deduced values may deliver only well-centered information or may not always be representative of in situ conditions.
Thermal tracing experiments are performed for decades in hydrogeology (Anderson, 2005, Saar, 2011). Such experiments are used to improve the characterization of hydrogeological parameters (e.g. hydraulic conductivity or dispersivity), but the same methodologies may be used to study the thermal properties of shallow geothermal systems (e.g. Vandenbohede et al., 2009, Vandenbohede et al., 2011, Giambastiani et al., 2012). However, the heterogeneity of geothermal and hydrogeological systems may be too complex to be fully caught by thermal or solute tracer experiments alone (e.g. Brouyère, 2001).
In this context, electrical resistivity tomography (ERT) can bring relevant and spatially distributed information both on the heterogeneity of aquifers and on the temporal behavior of tracers. Indeed, ERT has proven its efficiency to image and/or monitor spatial phenomena (Vereecken et al., 2006) such as salt water intrusions (Nguyen et al., 2009, Hermans et al., 2012c), variations in moisture content (Binley et al., 2002), biodegradation of hydrocarbons (Atekwana et al., 2000), salt tracer experiments (Kemna et al., 2002, Robert et al., 2012) and heat injection experiments (Hermans et al., 2012b). It was also used in the characterization of geological structures, for example in the exploration of geothermal systems, where hydrothermal fluids may generate high contrasts of resistivity (Pérez Flores and Gomez Trevino, 1997, Bruno et al., 2000, Garg et al., 2007, Arango-Galván et al., 2011).
Besides the characterization of shallow geothermal systems themselves, their impact on the groundwater temperatures in the aquifer may be important since their exploitation yields cold and heat plumes (Molson et al., 1992, Palmer et al., 1992, Warner and Algan, 1984) which may influence aquifer properties and groundwater chemistry (e.g. Jesuβek et al., 2013) and microbiology (Brielmann et al., 2009). Haehnlein et al. (2010) pointed out that, if laws and rules exist in some countries to limit the temperature difference caused by the use of geothermal systems, the development of anomalies is rarely monitored. With the growth of the demand for renewable energy, we can expect that regulations will become stricter and controls of installations more common. New monitoring technologies will be needed and ERT may play an important role to monitor spatially, i.e. not only in wells, the variations of temperature in the aquifer. For example, the temperature changes observed on operating GWHP systems (e.g. Vanhoudt et al., 2011) are typically in the range of temperature that could be detected by ERT.
ERT aims at imaging the electrical resistivity distribution of the subsurface. Using petrophysical relationships such as Archie's law, one may recover indirect parameters such as saturation, water electrical conductivity or total dissolved solid content. Bulk electrical resistivity also decreases with temperature (e.g. Revil et al., 1998). In most studies, temperature effects are undesirable and may create artifacts in the interpretation, a correction term is applied to remove the influence of temperature variations (Hayley et al., 2007, Sherrod et al., 2012). Few studies used time-lapse ERT to monitor directly temperature changes (Ramirez et al., 1993, LaBrecque et al., 1996b), generally in a context quite different from GWHP or GSHP systems.
Hermans et al. (2012b) monitored with time-lapse surface ERT a heat injection experiment at a relatively small scale (45 m) and at shallow depth (2–4.5 m). Their results show that ERT is a reliable tool to monitor temperature changes and may be a method of choice for the design and the monitoring of geothermal systems. However, the results need to be extended to deeper and more complex, heterogeneous reservoirs, as it will be considered in this paper. ERT-derived temperatures were very close to temperatures modeled using a calibrated coupled groundwater and heat flow and transport model bringing additional constraints on the thermal properties of the aquifer.
For deeper reservoirs, the rapid decrease in resolution and sensitivity of surface ERT becomes a major drawback (Caterina et al., 2013). It is then necessary to consider borehole ERT to improve resolution (Perri et al., 2012). For example, Prevedel et al. (2009) installed deep (600–750 m) borehole electrodes to monitor the migration of CO2 within a storage reservoir (Bergmann et al., 2012). For cross-hole ERT, the results obtained for a specific study are more easily extendable than for surface ERT because resolution patterns are not depth dependent.
In borehole ERT, electrodes are located under the ground surface, either fixed at the outer-edge of the casing or mounted on cables with the borehole fluid ensuring the electrical contact with the surrounding rock. In the latter case, borehole fluid is generally more conductive than the rock and may influence resistance measurements (Doetsch et al., 2010). Using time-lapse ERT, the relative fluid effect will be almost similar at each time-step and should be insignificant in inversion results (Nimmer et al., 2008).
In this paper, we study the ability of ERT to monitor temperature changes in a heterogeneous aquifer and follow thermal tracing experiments. We pumped water from a gravel aquifer, heated it and reinjected it in a second well, similar to a GWHP system operation.
The paper is organized as follows: first, the field site is described; second, the methodology is presented; then, the results of the ERT monitoring are compared with direct measurements in wells; finally, conclusions are presented.
Section snippets
Field site
The study site is located in Hermalle-sous-Argenteau in Belgium near the Belgian-Dutch border (Fig. 1). It lies on the alluvial aquifer of the Meuse River. A pumping well and 8 piezometers were already present on the site since the 1980s and 11 new piezometers were drilled in June 2012 together with an injection well. They were arranged in three different panels crossing the main flow direction between the injection well and the pumping well in order to study the spatial variability during
Heating and injection procedure
The experiment consists of an injection and pumping test. The groundwater is pumped from the pumping well, located in the northeastern part of the site, downstream from the injection well. We used a pumping rate of 30 m3/h. Given the high hydraulic conductivity values of the aquifer, the corresponding drawdown is only 5 cm in the pumping well and 4 cm in Pz19 (5 m upgradient from the well). The pumping process ensures that the main direction of flow will cross the three intermediate panels. Pumping
Cross-borehole ERT background
The background image was obtained using Eq. (7), corresponding to the smoothness-constrained solution (Fig. 4). In the zone between the boreholes, we see that the resistivity lies between 100 and 200 Ω m, with lower resistivities at the bottom of the section. These resistivity values are characteristic of saturated sand and gravel. The lower resistivity observed at the bottom of the aquifer corresponds with coarser gravel and a lower sand content.
The resistivity tends to increase toward the
Conclusion
The growing demand for renewable energy leads to an increase in the development of geothermal energy projects. Heat storage has become a common energy storage technology and heat is a common tracer in hydrology and hydrogeology. The variation of electrical resistivity/conductivity of water, soils and rocks is a well-known phenomenon and has been studied for several decades. However, the potential of ERT, a method mapping the electrical resistivity of the subsurface, to monitor and quantify
Acknowledgements
We would like to thank the associate editor and two anonymous reviewers for their pertinent comments and suggestions which have helped to improve the manuscript. We also thank the F.R.S. - FNRS (grant no. FC 87116) and the Fondation Roi Baudouin – Prix Ernest Dubois (grant no. 2013-8126501-F002) for their financial support during the PhD of Thomas Hermans.
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