Chapter 3. Heat flux from magmatic hydrothermal systems related to availability of fluid recharge
M.C. Harvey1, J.V. Rowland1, G. Chiodini2, C.F. Rissmann3, S. Bloomberg4, P.A. Hernández5,6, A. Mazot7, F. Viveiros8 and C. Werner9.
1School of Environment, University of Auckland, Auckland, New Zealand, 2Istituto Nazionale di Geofisica e Vulcanologia sezione di Bologna“Osservatorio Vesuviano,” Via Diocleziano, Napoli 328-80124, Italy, 3Environment Southland, Private Bag 90116, Invercargill, New Zealand, 4Department of Geological Sciences, University of Canterbury, Private Bag 4800, Canterbury, New Zealand, 5Environmental Research Division, Instituto Tecnológico y de Energías Renovables (ITER), 38611 Granadilla de Abona, Spain, 6Instituto Volcanológico de Canarias (INVOLCAN), 38400 Puerto de la Cruz, Spain 7GNS Science, Private Bag 2000, Taupo, New Zealand, 8Centro de Vulcanologia e Avaliação de Riscos Geológicos, University of the Azores, Rua Mãe de Deus, Ponta Delgada 9501-801, Portugal, 9Alaska Volcano Observatory, Volcano Science Center, U.S. Geological Survey, 4200 University Drive, Anchorage, AK 99508, USA
Published: Journal of Volcanology and Geothermal Research, August 2015
Mr. Harvey conducted the literature review, undertook data processing, and wrote the manuscript. Other authors provided raw data (C.F. Rissmann, S. Bloomberg, P.A. Hernández, F. Viveiros and C. Werner) and/or provided advice and review of the manuscript.
Magmatic hydrothermal systems are of increasing interest as a renewable energy source. Surface heat flux indicates system resource potential, and can be inferred from soil CO2 flux measurements and fumarole gas chemistry. Here we compile and reanalyze results from previous CO2 flux surveys worldwide to compare heat flux from a variety of magma-hydrothermal areas. We infer that availability of water to recharge magmatic hydrothermal systems is correlated with heat flux. Recharge availability is in turn governed by permeability, structure, lithology, rainfall, topography, and perhaps unsurprisingly, proximity to a large supply of water such as the ocean. The relationship between recharge and heat flux interpreted by this study is consistent with recent numerical modelling that relates hydrothermal system heat output to rainfall catchment area. This result highlights the importance of recharge as a consideration when evaluating hydrothermal systems for electricity generation, and the utility of CO2 flux as a resource evaluation tool.
A common model of a magmatic hydrothermal system consists of a convecting cell of fluid. Meteoric water exchanges heat with a magmatic body at depth then rises toward the surface through permeable rock formations as a high temperature plume of low density water, steam and gas (mostly CO2). Most of the rising steam condenses in the shallow subsurface, and the resulting liquid condensate is discharged from the system either by lateral outflow (Chiodini et al., 2005; Chiodini et al., 1996), or evaporation (Chiodini et al., 2005; Hochstein and Bromley, 2005; Werner et al., 2006). A proportion of the condensate may recycle back into the system through a “heat-pipe” mechanism (Hochstein and Bromley, 2005). Water discharged from the system (according to the above processes) is typically recharged at the margins by meteoric water (Giggenbach, 1995; Dempsey et al., 2012), or seawater in some coastal settings (Sveinbjornsdottir et al., 1986; Parello et al., 2000; Dotsika et al., 2009). In many systems, magmatic water is a minor component of recharge (Giggenbach, 1995). For most systems examined here, water is predominantly of meteoric origin. The quiescent-state heat flow from the system is useful for volcanic hazard monitoring, where a sudden increase in heat flow could precede a period of volcanic unrest. Heat flow evaluation is also useful for exploration of hydrothermal energy resources (Hochstein and Sudarman, 2008); magmatic hydrothermal systems are of increasing interest as low carbon sources of base load electricity (Chamorro et al., 2012).
When the CO2/H2O (unitless mass ratio) of the rising plume is known from fumarole gas analysis, and soil CO2 flux can be quantified at the surface (using a portable CO2 flux meter), the two can be combined to provide a proxy for heat flow, usually reported as Megawatts (MW) (Brombach et al., 2001; Chiodini et al., 2005; Fridriksson et al., 2006; Hernández et al., 2012; Rissmann et al., 2012). The geostatistical methods used to quantify soil CO2 flux were previously explored and compared (Lewicki et al., 2005). Accordingly, fumarole chemistry provides complementary information to CO2 flux measurements (i.e. by allowing CO2 flux to be used as a proxy for heat flow). However, in order to compare the intensity of heat flow from various volcanic and hydrothermal systems it is also useful to consider heat flux (MW/km2), as distinct from heat flow (MW). Although the terms are often (erroneously) used interchangeably, heat flux is heat flow normalized to unit area (Bird et al., 19 Hydrothermal systems are generally characterized according to a number of factors including geochemistry (Giggenbach, 1996), reservoir phase (liquid or vapour), temperature, lithology, and structural setting (Henley and Ellis, 1983). Here we compile and reanalyze results from 22 hydrothermal areas representing a wide variety of settings. The objective is to determine how CO2 flux, CO2/H2O and the associated heat flux vary according to structural setting, reservoir phase, recharge source and recharge availability. Refer to Table 5 for a detailed summary of the physical and chemical characteristics of these systems. Hydrothermal studies were included on the basis that they provided both system CO2/H2O, and mapping of the hydrothermal CO2 flux and a total CO2 flow, allowing an estimate of heat flow.
The data provided in Table 6 is used to construct Figure 4. The data for 9 of the 22 systems in Table 6 comes from a previous study of CO2 flux and fumarole analysis for a variety of hydrothermal systems (Chiodini et al., 2005). Our study expands the previous study with the addition of new systems, and by considering the relationship between system heat flux and system setting.
Where possible, we have adopted the methodology of the earlier study so additional systems can be included and meaningfully compared (refer to Notes in Table 7 and Table 8 for exceptions). This methodology provides the mean soil diffuse CO2 flux of diffuse degassing structures (DDS) present within the various systems. DDS correspond to discrete areas of anomalous CO2 flux, commonly associated with areas of high permeability (faults). The methodology delineates DDS areas using sequential Gaussian simulation; for most surveys, DDS are defined as areas of anomalous CO2 flux where simulated flux values have a >50% probability of exceeding twice the mean background (biogenic) flux (Chiodini et al., 2005).
Some surveys were confined to thermal ground with little or no vegetation. In these cases the DDS area was assumed to be where CO2 fluxes exceeded zero; the biogenic flux was assumed to be negligible (refer Table 7 and Table 8). The uncertainty of the CO2 flux estimate was computed from the simulation results, and found to be a function of CO2 flux measurement density. The measurement density defined by number of measurements falling in the area contained by circle with radius equal to the range of the CO2 flux variogram (circle range area (CRA))(Cardellini et al., 2003). Raw data from recent CO2 flux surveys at Ohaaki, Rotokawa, White Island (New Zealand) and San Jacinto (Nicaragua) were reprocessed using this approach (refer Table 7 and Table 8).
Summary data from a variety of surveyed hydrothermal areas are tabulated (Table 6). The calculated mean CO2 flux for the various DDS areas is plotted against CO2/H2O ratios (from fumarole or deep well gas analysis) for each area on a log-log plot (Figure 4). For most DDS considered here, the contribution of focused venting from fumaroles inside the DDS has been previously reported or is assumed minor (<10%). Table 6 and Figure 4 include the contribution of focused venting. Mean CO2 flux error bars are larger (+/-50%) than previously used (+/-30%) (Chiodini et al., 2005), to allow for the added uncertainty in this contribution. There are no hot, neutral chloride springs within the studied DDS areas, so no contribution of deep reservoir liquid outflows to the surface heat flux.
Data points are color coded according to the hydrothermal reservoir type (liquid, vapour dominated, or vapour core: Section 3.2). Because heat flux is simply the product of CO2 flux and fumarole H2O/CO2, straight lines of constant heat flux (50 and 500 MW km-1, assumes steam condensation at 1 bar and 12°C) can be conveniently represented on Figure 4. These lines encompass most of the data points. Error bars show the inherent uncertainty in fumarole measurements due to condensation processes (negative vertical bars), and the determination of mean CO2 flux (horizontal bars)(Chiodini et al., 2005). The rationale for assumptions, uncertainty, and other details of the method are provided in Table 7 and Table 8.
Chapter 1. Research aims and objectives
1.2. Aims and objectives
1.3. Thesis Structure
Chapter 2. CO2 flux sources, signals and pathways
2.2. Sources of CO2
2.3. The CO2 flux signal
2.4. Pathways of CO2 and H2O from reservoir to surface
2.5. Solubility of CO2 in magma
Chapter 3. Heat flux from magmatic hydrothermal systems related to availability of fluid recharge
3.4. Results and Discussion
Chapter 4. CO2 flux and 13CO2 isotope investigations of active faults and the system boundary at Te Mihi
4.3. Geological and hydrothermal background
Chapter 5. Drone with thermal infrared camera provides high resolution georeferenced imagery of the Waikite Geothermal Area, New Zealand
5.4. Discussion and Conclusions
Chapter 6. CO2 flux, shallow temperature and aerial thermal infrared surveys on steam heated ground in the Taupo Volcanic Zone
6.3. Study Areas
Chapter 7. CO2 flux geothermometer for geothermal exploration
Chapter 8. Summary and conclusions
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CO2 and Heat Release from Magmatic Hydrothermal Systems: Insights from CO2 Flux and Other Modern Methods