Assessment of performance and parameter sensitivity of multicomponent geothermometry applied to a medium enthalpy geothermal system
© The Author(s) 2017
Received: 17 March 2017
Accepted: 10 July 2017
Published: 18 July 2017
The determination of reservoir temperatures represents a major task when exploring geothermal systems. Since the uncertainties of classical solute geothermometry are still preventing reliable reservoir temperature estimations, we assess the performance of classical geothermometers and multicomponent geothermometry by applying them to fluids composed from long-term batch-type equilibration experiments and to fluids from natural geothermal springs in the Villarrica area, Southern Chile. The experiments, weathering two reservoir rock analogues from the Villarrica area, highlight a strong impact of reservoir rock composition on the fluid chemistry and, consequently, on calculated in situ temperatures. Especially temperatures calculated from classical solute geothermometry are strongly affected. Multicomponent geothermometry is obviously more robust and independent from rock composition leading to significantly smaller temperature spreads. In a sensitivity analysis, the dilution of geothermal fluid with surficial water, the pH and the aluminum concentration are anticipated to be the factors causing underestimations of reservoir temperatures. We quantify these parameters and correct the results to obtain realistic in situ conditions. Thus, enabling the application of the method also on basis of standard fluid analysis, our approach represents an easy-to-use modification of the original multicomponent geothermometry leading to very plausible subsurface temperatures with significantly low scattering.
The estimation of reservoir temperatures is a major goal in geothermal exploration. The in situ temperature is a key parameter for the assessment of geothermal potentials and the economic efficiency of prospected reservoirs. Deducing these temperatures from the chemical composition of geothermal fluids emerging at the earth’s surface is a commonly used and relatively cost-effective method. Over more than five decades a large number of solute geothermometers have been established and constantly improved [e.g., Fournier and Rowe (1966), Giggenbach (1988), Can (2002), Sanjuan et al. (2014)]. Many of these interrelations, linking the concentration of one constituent or the ratios of cations (SiO2, Na/K, K/Mg, Na/K/Ca) to the in situ temperature, are based on rather well known water–rock interaction processes (silica solubility, cation exchange in the feldspar system and equilibria of micas). Furthermore, empirical geothermometers using the ratios of Na/Li and Mg/Li (Fouillac and Michard 1981; Kharaka and Mariner 1989; Sanjuan et al. 2014) has been established, additionally accounting for fluid salinity, chloride concentration and the geology of the reservoir. However, solute geothermometry still is afflicted with great uncertainties often leading to a broad range and often inconsistent calculated reservoir temperatures (Santoyo and Díaz-González 2010; Verma and Santoyo 1997), in particular exploring geothermal systems, where only few information (geology, borehole data etc.) is available. Even in studies in which the individual geothermometers has been carefully selected regarding their applicability and validity for the expected conditions, the resulting temperatures show variations of often more than 100 K for the same sample (e.g., Pepin et al. 2015; Aquilina et al. 2002; Mutlu 1998; D’Amore et al. 1994).
Recently, a number of geochemical surveys have evaluated the in situ temperatures of the geothermal system in the Villarrica area in Southern Chile, where many natural geothermal springs discharge in direct vicinity of the active Villarrica volcano. The estimations of subsurface temperatures resulted in widely differing and even inconsistent data. Sánchez et al. (2013) roughly determined temperatures of 100–180 °C from cation ratio geothermometers, with the warmest temperatures close to the volcanoes. Whereas, estimations based on the temperature-dependent oxygen isotope fractionation in the system SO4 2−–H2O (Held et al. 2015), temperatures ranging from 80 to 130 °C, are significantly lower. Although, in a previous work from these authors (Nitschke et al. 2016), the warmer temperatures of the first study (in the North) as well as the cooler of the latter (in the South) were partly confirmed, the results were accompanied with large uncertainties for the individual springs of up to 130 K. Temperature estimations with uncertainties of that level are unsatisfactory for reliable exploration.
Many factors interfering precise and consistent results have been identified and discussed in literature. For calculating reservoir conditions based on the solubility of only one mineral phase (e.g., SiO2 geothermometers), the amount of solvent has to remain constant from reservoir to the discharge. Therefore, dilution with superficial water and boiling due to pressure relief are often considered to have greatest impact. For cation ratio geothermometers, which are not affected by changes of the amount of solvent, other processes like immaturity (not yet attained water–rock equilibrium) of fluids, fast re-equilibration kinetics and precipitation during ascent prevent from obtaining true in situ temperatures. The role of the reservoir lithology, as a major interfering factor becomes obvious, when for example comparing studies from, e.g., Giggenbach (1988), Arnórsson (2000), Fournier (1979) and Fournier und Truesdell (1973), indicating rather large discrepancies of the Na/K ratios of fluids from equilibrated geothermal systems of different lithologies for a given system. The same applies to other cation ratios (Na/K/Ca, K/Mg, Na/Li, etc.), commonly used for geothermometry. Also the authors of this study have previously found strong indications for the significant effect of different reservoir lithologies on the hydrochemical composition of the fluids affecting the calculation of reservoir temperatures (Meller et al. 2016; Nitschke et al. 2015; Nitschke et al. 2016). In this work, laboratory experiments are conducted to investigate the site-specific impact of rock composition on the equilibrated fluids in detail and to deduce implications for classical solute geothermometer applications. Furthermore, the numerical multicomponent geothermometry method as proposed originally by Reed and Spycher (1984) is assessed, evaluating if its statistical nature can overcome dependence upon reservoir rock composition. In order to facilitate the application of multicomponent geothermometry on basis of a standard fluid analysis, we suggest an easy-to-use modification of the original method.
Methods and results
The detailed geological setting of the study area is documented in previous works of Held et al. (2016b) and Sánchez et al. (2013). They found a prominent change of lithology associated with the virtually E-W striking Mocha-Villarrica-Fault Zone. South of that fault plutonic rocks of the North Patagonian Batholith (NPB) prevail, while to the north mainly volcanic and volcano-clastic rocks of the Cura-Mallin (CM) formation outcrop. Depending upon this local lithology change, strontium isotope measurements (Held et al. 2015) reveal spatially differing geothermal fluids, with a plutonic signature south of the volcanic chain and a volcanic signature in the north of the study area. Accordingly, for the experimental approach, two reservoir rock analogues were selected, representing the two different geological units: a Mesozoic tonalite (NPB) and a Cenozoic porphyric andesite (CM) for long-term batch reaction experiments.
Usually, reservoir rocks and their compositions are poorly known during exploration of a geothermal system and effects of different mineralogical compositions on geothermometers are difficult to handle. By calculating the equilibration temperature of a large number of (reservoir) rock forming minerals, multicomponent geothermometry provides a more statistical approach of determining in situ temperatures. Therefore, this method is more unbiased from reservoir rock composition. To test this hypothesis, we apply the method on natural emerging geothermal fluids from the Villarrica area and on the fluids derived from laboratory experiments to compare the results to temperatures calculated with classical solute geothermometers.
Laboratory water–rock equilibration experiments
Volumetric mineral composition of reservoir rock analogues used for laboratory experiments
The chemical evolutions of the major constituents over time are depicted in Fig. 1 and in a tabular form in Appendix. Measured aqueous constituents are assumed to be present as a result of water–rock interaction. Due to the fact, that only low mass transfer occur for both experiments, the minerals being educts and products of fluid–solid reactions were not determined (resulting changes of solids were below the detection limit of XRD (<5 mass%) and SEM–EDX (very thin alteration products). Therefore, conclusions made in terms of geothermometric applications, are based on changes of water chemistry only. Comparing both experiments, significant differences in fluid compositions become obvious. Towards the end of the reaction time, the fluid in contact with tonalite has a TDS of about 700 mg/L, whereas the TDS of the fluid from the andesite experiment is about 500 mg/L. The tonalite fluid can be classified as a Na–SO4 fluid of near neutral pH (6.7), while the andesite fluid is a Na–Cl fluid with a higher pH of 8.5. Sodium concentrations are very similar (5–6 mmol/L) for both experiments at the end of the reaction time, with a nearly continuous, but diminishing increase over time. The tonalite fluid is found to have high concentrations of potassium and calcium at early stages, but decreasing over the duration of the experiment. The andesite fluid is showing relatively constant concentrations for both cations, but remaining on a significantly lower level compared to the tonalite fluid. Aqueous SiO2 concentrations of both fluids reach a steady state already in relatively early stages of the experiments (after 4 days for the tonalite fluid, after 45 days for the andesite fluid). However, they differ strongly from each other. Being hardly explainable, although, we observe that the andesite fluid saturates with respect to quartz, whereas the chalcedony saturation of the tonalite fluid, leads to significantly higher SiO2 concentrations.
The Mg/K geothermometer of Giggenbach (1988) estimates reaction temperatures for both experiments quite well. Especially for the tonalite fluids, the calculated temperature (137 °C) reflects the reaction conditions in nearly perfect agreement. For the andesite fluids calculated temperatures approach reaction temperature over the course of the experiments, but decrease to slightly underestimated temperatures towards the end (120 °C). Na/Li based temperature determination (Kharaka and Mariner 1989; Sanjuan et al. 2014; Verma and Santoyo 1997) is obviously rather less appropriate, giving a broad range of apparently erratic results depending upon experiment and applied formulation. The method leads to dramatic underestimated temperatures (Verma and Santoyo 1997) but also really well fitting results (Sanjuan et al. 2014) for the andesite experiment. Calculated temperatures for the tonalite fluids range from underestimations (Verma and Santoyo 1997) to high overestimations (Sanjuan et al. 2014). The Li/Mg geothermometer (Kharaka and Mariner 1989) underestimates the reaction temperature for both experiments to a great extent.
If the application of one geothermometer is successful, inaccurate or failing cannot be explained in every case (e.g., like for the Na/K geothermometer). As laboratory procedures are identical for both experiments (sample preparation for solids and fluids and the setup of experiments), we conclude that the differences of fluid compositions comparing both experimental series in this specific case can only be due to the differences in rock composition. These discrepancies lead to different steady states of fluid compositions, which is consequently resulting in differences of calculated temperatures. Even if one of the geothermometers would yield a correct estimation of the reservoir temperature, there is no indication for the selection of that appropriate one when exploring a geothermal site.
The determination of in situ temperatures by multicomponent geothermometry, is based on the calculation of the saturation indices (SI = log(Q/K)) for a suite of possible (reservoir) rock minerals in a conceivable temperature interval. Based on a complete fluid analysis, an equilibrium temperature (temperature for which SI = 0) for each considered mineral phase is obtained. In contrast to classical solute geothermometry, the results represent a temperature distribution in which the fluid has been equilibrated with the host rock minerals. This enables the calculation of a mean in situ temperature from the bandwidth of obtained equilibration temperatures and gives insight on the uncertainty of this estimation (maximum spread of temperatures). From that point of view, multicomponent geothermometry can be considered as a statistical approach to predict reservoir temperatures and therefore it might be more applicable for the evaluation of systems with unknown mineralogy, which is often the case especially in early stages of geothermal exploration campaigns.
This study applies an approach similar to the original method suggested by Reed and Spycher (1984) and revisited by Spycher et al. (2014), Peiffer et al. (2014) and Palmer et al. (2014). Equilibration temperatures are calculated for feldspars (K-feldspars and albite), SiO2 polymorphs (quartz or chalcedony), phyllosilicates (muscovite, paragonite, biotites, kaolinite), zeolites and epidotes based on concentrations of major constituents Na, K, Ca, Si, Al, Fe, Cl, alkalinity and sulfate. Magnesium phases are excluded intentionally, since dilution of geothermal fluids with superficial, Mg-rich waters will significantly bias reservoir temperature estimations, by overestimating equilibration temperatures for magnesium minerals. The determination of the critical parameters, such as in situ pH and aluminum concentration is done differently than in the above named studies. Contrasting the methods of Spycher et al. (2014) and Palmer et al. (2014), we determine in situ pH as a sum parameter via a sensitivity analysis (“In situ pH value” section), thus accounting for measurement errors as well as for degassing and speciation-driven processes, which potentially affect the pH. The same applies for aluminum concentrations (“Aluminum concentration” section). Differing from the FixAl method proposed by Pang and Reed (1998), the here presented approach determines the aluminum concentration by minimization of the equilibrium misfit for all considered alumino-phases not by forced equilibrium of one single mineral. Numerical calculations were conducted using PhreeqC version 3.1.4 (Parkhurst and Appelo 2013) and thermodynamic data of Delany and Lundeen (1991).
Figure 4 provides a comparison of temperatures derived from multicomponent geothermometry (preliminary temperatures without correction of dilution, pH and aluminum concentration) to results calculated by a suite (n = 23) of classical solute geothermometers (SiO2, Na/K, Na/K/Ca, K/Mg, Li/Mg and Na/Li geothermometers according to the equations given by Arnórsson (1983), Can (2002), Diaz-Gonzalez et al. (2008) Fouillac and Michard (1981), Fournier (1977, 1979), Fournier and Potter (1982), Fournier and Truesdell (1973), Giggenbach (1988), Kharaka and Mariner (1989), Michard (1990), Nieva and Nieva (1987), Tonani (1980), and Verma and Santoyo (1997). The results were depicted as boxplots, plotting the mean (median value) equilibration temperature, the lower and upper quartiles (comprising 50% of all temperatures) and the lower and upper extremes. The ranges of temperatures for the springs in the Villarrica area and for the fluids derived from the experiments calculated by multicomponent geothermometry are significantly smaller as compared to the very large spread obtained from classical solute geothermometers. Despite special attention paid to the applicability of each solute geothermometer, it is shown that classical geothermometers generally lead to a broad spread of temperatures of, in some cases, ≫100 K. The spread of temperatures derived from multicomponent geothermometry is much smaller.
At the same time, the calculated mean (median) temperatures are significantly lower. Although deviation of calculated temperatures for the experimental fluids is quite small (124 °C for the andesite experiment and 133 °C for the tonalite experiments), estimations for some springs lead to implausible low values, ranging below the discharge temperature (e.g., discharge temperature/calc. temperature for Car = 82/77 °C or Chi = 85/69 °C). At least in those cases temperatures are interfered by processes which were obviously not taken into account in this preliminary calculation. Generally, calculated temperatures appear to underestimate in situ temperatures, as in any case being significantly cooler compared to classical geothermometer temperatures. The identification and quantification of the critical parameters being most sensitive for the system and necessary corrections calculated realistic reservoir temperatures are presented in the following section.
For the systematical underestimation of calculated temperatures discerned in “Multicomponent geothermometry” section, a number of processes or parameters are worth considering. Anticipated processes are the dilution with superficial water during ascent of fluids, the deviation of measured pH from in situ pH (due to degassing and as a function of temperature), as well as the uncertainties of aluminum concentrations (due to precipitations, sampling, sample storage and measurement errors). To quantify the impact of each parameter and to obtain realistic in situ conditions is a major task. Therefore, we conducted a sensitivity analysis on each of the mentioned parameters. In terms of the pH and the aluminum concentration, the best-fit results of this analysis (minimization of total temperature spread and densification of clustering of the majority of temperatures) are assumed to represent the most likely in situ conditions, which are then basis for the final temperature estimation.
Dilution with superficial water
In situ pH value
Variation of calculated equilibration temperatures as a function of pH can also be documented for the spring fluids (Fig. 7). Applying the measured pH, the obtained temperatures appear to be too low (partly below discharge temperature, e.g., Car and Chi). Especially for samples with high measured pH (e.g., Car and Liq), which potentially reflects extensive degassing, a large temperature spread is obtained. Applying lower pH values results in an increase of modeled temperatures and a decrease of temperature spread. The minimum of the equilibration temperature spread (and secondly the clustering of the majority of calculated temperatures) was taken to determine the most likely in situ pH, which then can be used to deduce the reservoir temperature. For samples with a measured slightly acidic pH (e.g., RinCo), modeled in situ pH will trend also towards neutral conditions resulting in a decrease of modeled mean temperature.
Aluminum concentrations of Villarrica springs measured by ICP–MS in comparison to results of previous studies
These issues are evident, when comparing aluminum concentrations of spring fluids in the study area measured in this study to results from previous works (Table 2). Results differ partly up to a factor of 20, which will increase the saturation indices by ~1.3. Thus, aluminum concentrations (input parameter) were varied within the bandwidth of reported measured aluminum concentrations in the study area (Table 2). The pH values were set according to the findings from pH sensitivity analysis.
Mean in situ temperatures for Villarrica springs and laboratory experiments calculated by a suite of classical solute geothermometers, multicomponent geothermometry and pH/aluminum-corrected multicomponent geothermometry
Classical solute geothermometers
Corrected multicomponent geothermometer
Mean T [°C]
Mean T [°C]
Mean T [°C]
In many cases, the application of different classical solute geothermometer equations leads to a wide range of calculated temperatures. An important factor interfering consistent calculation are differences in reservoir rock composition and their impact on fluid chemistry. Long-term batch equilibration experiments in this study clearly show that reservoir rock composition has a major impact on temperatures calculated by classical solute geothermometry, with variations of >200 K. In order to overcome the strong dependence upon rock composition, we assess the statistical multicomponent geothermometer approach. Since the original method demands high quality fluid sampling and analysis, we suggest a modification, which can be used also on the basis of standard fluid analysis. Compared to classical solute geothermometry, the resulting calculated equilibration temperatures have a significantly smaller scattering for fluids of plutonic and volcanic origin in the investigated area. It is shown that the pH value and the aluminum concentration are extremely sensitive parameters for the calculation of equilibration temperatures on the basis of multicomponent geothermometers. Thus, as measured values for both parameters can differ significantly from in situ conditions, we suggest applying a correction for the pH and the aluminum concentration prior to temperature determination. In doing so, multicomponent geothermometry leads to more realistic mean temperature estimation with significantly low variances of mostly ≪30 K for the natural samples as well as for the experimental fluids. The well-fitting calculations of reaction temperatures for both experiments, reveal a higher independence from reservoir rock composition as compared to classical solute geothermometers. This could make multicomponent geothermometry an ideal complementary approach to classical solute geothermometer methods evaluating subsurface temperatures particularly in unknown lithologies. The general applicability to a wide range of reservoir rocks has to be proven in the next step. In terms of classical solute geothermometry, we conclude that the impact of reservoir rock composition is of outstanding importance and has to be taken into account in future applications.
FN—conception and design of the study, experimental work, analysis, modelling, paper writing. SH—experimental work, analysis, paper writing. IV—experimental work. TN—analysis, paper revision. TK—interpretation, paper revision. All authors read and approved the final manuscript.
The study is part of a collaborative research project of Karlsruhe Institute of Technology (KIT) and the Andean Geothermal Center of Excellence (CEGA, Fondap-Conicyt 15090013). The authors appreciate the support of the BMBF-CONICYT International Scientific Collaborative Research Program (FKZ 01DN14033/PCCI130025). Additional support under the topic “Geothermal Energy Systems” of the Helmholtz portfolio project “Geoenergy” and by EnBW Energie Baden-Württemberg AG is gratefully acknowledged. Many thanks to two anonymous reviewers, who helped to significantly improve the manuscript.
The authors declare that they have no competing interests.
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