A New Method of Evaluation of Chemical Geothermometers for Calculating Reservoir Temperatures from Thermal Springs in Nevada

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1 GRC Transactions, Vol. 35, 211 A New Method of Evaluation of Chemical Geothermometers for Calculating Reservoir Temperatures from Thermal Springs in Nevada Lisa Shevenell 1 and Mark Coolbaugh 2 1 Nevada Bureau of Mines and Geology,University of Nevada, Reno NV 2 Renaissance Gold Inc., Reno NV, USA lisaas@unr.edu sereno@dim.com Keywords Geothermometry, resource assessment, Nevada, geochemistry, exploration ABSTRACT Early work by Edmiston and Benoit (1984) found that the Na-K-Ca geothermometer tended to overestimate reservoir temperatures of geothermal systems in the Basin and Range. The purpose of this paper is to determine if a new method based on theoretical mixing calculations can better predict reservoir temperatures for Nevada/Great Basin geothermal systems than other traditional geothermometer calculations. The geothermometers that are compared in this work are the Quartz, no steam loss (Fournier 1977; Fournier, 1981) and the Na-K-Ca, Mg-corrected (Fournier and Potter, 1979). Several examples suggest that this new mixing method can predict realistic reservoir temperatures under suitable conditions. Preliminary analysis suggests that the method tends to work better when the Na-K-Ca geothermometer is greater than the SiO 2 geothermometer for an area. It also appears to work better when the temperature difference between the two thermal waters being mixed is >25 C and when the two geothermometers for the mixed fluids differ by >1 C for either the Na-K-Ca or SiO 2 when compared between the two fluids (e.g., SiO2 geothermometer of fluid 1 is 1 C greater than SiO2 geothermometer of fluid 2). Introduction Recent work at the University of Nevada, Reno has included compilation of various data for inclusion on web pages and evaluation of these data to assess the geothermal potential of areas from regional to local scales. Numerous geochemical databases have been placed on public web sites for use by others in assessing and evaluating geothermal resources in the Great Basin ( nbmg.unr.edu/geothermal/index.html). A suite of geothermometers was computed using this data, and results were previously evaluated using geochemical data from production wells in Nevada (Shevenell and DeRocher, 5). With various limitations of traditional geothermometer calculations (e.g., mixing, gas loss, precipitation, re-equilibration), additional methods of geothermometer computation have been attempted (i.e., Reed and Spycher, 1984; Shevenell and DeRocher, 5) to help evaluate the range of geothermometry methods available to estimate reservoir temperatures. However, the method proposed by Reed and Spycher (1984), and tested on Nevada producing reservoirs by Shevenell and DeRocher (5) prove to be very time consuming and offer only modest improvements in accuracy of reservoir temperature estimation. The purpose of this paper is to determine if a new method based on theoretical mixing calculations can better predict reservoir temperatures for Nevada/Great Basin geothermal systems with a far less time consuming method. Background Early work by Edmiston and Benoit (1984) found that the Na-K-Ca geothermometer tended to overestimate reservoir temperatures of geothermal systems in the Basin and Range. The silica geothermometer calculated in samples from deep wells overestimated measured temperatures by 18ºC, where as that of the Na-K-Ca overestimated temperatures by 29ºC (Edmiston and Benoit, 1984). Similarly, Mariner et al. (1983) found that geothermometers overestimated temperatures in deep geothermal wells in the northern Basin and Range by 14ºC. These authors determined that the most favorable indications for a high temperature reservoir were obtained when silica temperatures of >21ºC were indicated in areas of significant geothermal gradient. This earlier work focused on high temperature systems, and many systems in Nevada are lower temperature systems suitable to binary power technology. This earlier work also used single analyses of varying quality from surface samples and exploration and discovery wells, without the benefit of water samples from production wells or other types of wells that are now in place in the areas discussed in this paper. Current analysis of calculated geothermometer temperatures also commonly show that the silica and cation geothermometers yield disparate temperatures, with one or the other being closer to the actual reservoir temperature, but not in any 657

2 consistent manner (Shevenell and DeRocher, 5) This paper presents an alternative approach to assessing disparate geothermometer temperatures calculated by the Na-K-Ca, Mg-corrected and silica geothermometers using a theoretical mixing model. Methodology A mixing model was constructed using as input two different, water samples of differing geochemistry and differing temperatures located in close proximity to one other. The mixing model was used to estimate geochemical compositions and thermal temperatures of two different end-member source fluids that are assumed to have mixed in different proportions to produce the differences in chemistry observed in the sampled waters. The geothermometers that are compared are the Quartz, no steam loss (Fournier 1977; Fournier, 1981) and the Na-K-Ca, Mg-corrected (Fournier and Potter, 1979). Two scenarios are tested. Scenario A is mixing between two separate well or spring waters. Scenario B is mixing of the same water that has different temperature and composition at different sampling times. The mixing calculations are valid under the following assumptions. 1. The hot end member and cold end member waters are the same composition for the two water samples evaluated. 2. The proportion of hot and cold end member waters may vary when evaluating a time series in a particular well or spring that may experience greater and lesser mixing of thermal and non-thermal water over time (Scenario B). The composition of the end members is assumed constant, but the mixing proportions vary over time. 3. There is no precipitation when the waters mix, and exothermic/endothermic reactions during mixing are minimal. 4. This can be applied over a limited temperature range where enthalpy can be assumed linearly proportional to temperature. It is also assumed that heat loss between the zone of mixing and the point of sampling is minimal. 5. No boiling or effervescence occurs. 6. The SiO 2 and Na-K-Ca, Mg corrected geothermometers converge at the actual geothermal reservoir temperature. 7. The temperature of the cooler of the two end-member fluids can be estimated with relative certainty, and is assumed in the examples provided below to be 17 C. (Comment: In the case of Bonham Ranch noted below, the coolest artesian well has a temperature of ~ 2 C, thus we can guess that the cooler end-member water has temperature near that of ambient shallow groundwater. A sensitivity analysis based on changing the assumed temperature of the cool end-member did not change the results very much, (at least in this case)). In this paper, we calculate a series of end-member water chemistries under different assumed mixing scenarios using mass balance considerations. The water chemistry of theoretical endmember thermal waters is calculated for a variety of end member temperatures and using calculated flow rate to conserve thermal mass. These recalculated water chemistries are used to calculate geothermometers that cover the span of possible mixing ratios. For example, if we have measured water chemistries of two waters of different temperatures from the same area, we can recalculate the geochemistry of a theoretical sample at a different temperature by calculating the percentage of theoretical hot and cold water end members solving the following equations simultaneously. First the thermal mass (temperature balance) of the sampled waters was calculated using the flow rate equations solved simultaneously. F T1 T 1 = f 1H T H + f 1C T C and F T1 = f 1H + f 1C F T2 T 2 = f 2H T H + f 2C T C and F T2 = f 2H + f 2C where, F T1 = total flow of well 1 (known or assumed) F T2 = total flow of well 2 (known or assumed) T 1 = flowing temperature of well 1 (known) T 2 = flowing temperature of well 2 (known) f 1H = flow of hot aquifer into well 1 f 2H = flow of hot aquifer into well 2 f 1C = flow of cold aquifer into well 1 f 2C = flow of cold aquifer into well 2 T H = temperature of hot aquifer (assumed) T C = temperature of cold aquifer (assumed) Rearranging and solving for f 1H and f 2H f 1H = (F T1 T 1 F T1 T C )/(T H T C ) and f 2H = (F T2 T 2 F T2 T C )/(T H T C ) Concentrations for the modeled waters mixed in different assumed mixing proportions are calculated from the concentration balance: FT1 C T1 = f 1H C H + f 1c C C and F T1 = f 1H + f 1C F T2 C T2 = f 2H C H + f 2c C C and F T2 = f 2H + f 2C where, C T1 = concentration of solute C in well 1 C T2 = concentration of solute C in well 2 C H = concentration of solute C in hot aquifer C C = concentration of solute C in cold aquifer and other terms retain the same definition. Rearranging of terms and solving for C H fc2 F T 1 C T 1 F T 2 C T 2 fc1 C H = fc2 f H1 f H 2 fc1 These simple calculations were performed in a spreadsheet over a variety of theoretical hot end member temperatures to get the proportion of the hot and cold water end members needed for a given theoretical temperature. Once the elements of interest for calculating geothermometers were re-calculated, geothermometers of that assumed/modeled sampled temperature were calculated and the theoretical temperature was plotted against the geothermometer temperature. The hypothesis was that when the calculations were made using two samples from different temperatures in an area, the lines would cross at one of the theoretical (calculated) sample temperatures, and this sample temperature would correspond to the actual reservoir temperature plotted on the other axis. 658

3 Figure 1. Locations of the three geothermal areas discussed in this paper. The example of the calculation is presented for Bonham Ranch, and the method is validated using chemistry from waters at producing geothermal areas where the reservoir temperature is known from production records. The locations of the three geothermal areas discussed in this paper are shown in Figure 1. Table 1. Selected data from samples collected at the Bonham Ranch, Desert Peak and Bradys, Nevada (from Coolbaugh et al., 7). Temp ID East North ( C) HCO 3 F Cl SO 4 Li Bonham Ranch SCD SCD Desert Peak Well Well Bradys Hot Spring Hot Well Bonham Ranch Temp ( C) SiO 2 Ca Mg Na K SCD SCD Desert Peak Well Well Bradys Hot Spring Hot Well Results Example: Bonham Ranch Several closely spaced artesian wells of differing temperatures were sampled at Bonham Ranch in the southwestern Smoke Creek Desert, Washoe County, Nevada and chemically analyzed. The two highest and lowest temperature wells in the area were selected for the test of this method. On the first visit, the well temperatures were measured with a shock resistant thermocouple, whereas on the second visit, the temperatures were measured with a more precise, but also more delicate, platinum resistance temperature device (RTD). The chemical analysis is reported with the temperature measured with the thermocouple during sampling, whereas calculations discussed below utilize the more precise value. The difference in temperature for the cooler well was 1.6 C cooler using the platinum RTD, while the difference in temperature for the hotter well was.7 C hotter. Locations, temperatures and chemistry used in geothermometer calculations appear in Table 1. Figure 2 shows the results of the calculations from Bonham Ranch where two wells of temperatures of 22.1 and 37.3 C were used in the mixing calculation, thus providing an example of scenario A. These fluids had calculated Na-K-Ca geothermometers of 153 and 172 C and lower SiO 2 geothermometer temperatures of 118 and 14 C. Using these fluids as a starting composition (Table 1), and mixing theoretical end members, where the cold end member is a constant 17 C, and the hot end member temperature is allowed to vary (e.g., X-axis of Figure 2), then the calculated geothermometers of the different mixed fluids are plotted on the Y-axis of Figure 2. It is hypothesized that where the SiO 2 and Na-K-Ca geothermometers cross is the actual reservoir temperature. In this case, at the Bonham Ranch, it is hypothesized that the hot end member (reservoir) temperature is 165 C (Figure 2). The fact that this temperature is less than C is consistent with the lack of observed silica-cemented sands and gravels and presence of calcium carbonate tufa towers in the postulated geothermal upwelling zone located approximately 2 km to the west (Coolbaugh et al., 7). An example of scenario B comes from Desert Peak where a well was sampled on two different dates and had two different temperatures (27 and 4 C). Figure 3 shows the results of this Desert Peak example in which the standard geothermometers were quite close to each other (SiO 2 = C, Na-K-Ca = C), and near the cross over point of 229 C. Measured temperatures in the reservoir from production wells is 218 C at 1676 m, demonstrating there is indeed a high temperature resource.

4 Drilled Temp =? (undrilled) Cross-over Temp = 165⁰C Mix_ Figure 4 shows a mixing scenario between a 58 C spring and an 89.5 C well at Brady s Hot Springs. In this case, the higher temperature fluid has a SiO 2 geothermometer temperature higher than the Na-K-Ca temperature, yet both slightly overestimate (22 and 19 C, respectively) the drilled temperature at Bradys (181 C). The lower temperature fluid has a higher Na-K-Ca geothermometer temperature than the SiO 2 (149 and 143 C, respectively) that slightly underestimates the measured temperature at Brady s Hot Springs. The mixed result (165 C) also underestimates the measure temperature at Bradys. Geothermometers of all types clearly can be difficult to interpret, and this method requires significant further evaluation to determine under what particular set of circumstances it can be expected to provide useful results Temperature (C) Figure 2. Mixing plot for the warmest and coolest of the warm wells at Bonham Ranch that likely had different proportions of thermal fluid mixing. Drilled Temp = 218⁰C Cross-over Temp = 229⁰C Temperature (⁰C) Mix_ Figure 3. Mixing plot for the well at Desert Peak on two different dates that likely had different proportions of thermal fluid mixing Drilled Temp = 181⁰C Cross-over Temp = 165⁰C Mix_ Temperature (⁰C) Figure 4. Mixing plot for a 58 C spring and 89.5 C well at Bradys (pair 4-5) that likely had different proportions of thermal fluid mixing. The mixing model suggests a reservoir temperature of 165 C, whereas the drilled temperature is 181 C. Discussion Preliminary analysis suggests that the method tends to work better when the Na-K-Ca geothermometer is greater than the SiO 2 geothermometer for an area. It also appears to work better when the temperature difference between the two thermal waters being mixed is >25 C and when the two geothermometers for the mixed fluids differ by >1 C for either the Na-K-Ca or SiO 2 when compared between the two fluids (e.g., Si 2 geothermometer of fluid 1 is >1 C greater than SiO 2 geothermometer of fluid 2). Typical mixing scenarios would show that higher temperature fluids with higher B and Cl mixing with lower temperature fluids with lower B and Cl can mix to form intermediate temperature, B and Cl fluid. Many mixing pairs selected in this preliminary work were selected based on this assumption. But in several cases, B and Cl did not increase in different springs or wells in a particular area with increasing temperature. Attempting the mixing model presented here resulted in positive results with cross over points of the SiO 2 and Na-K-Ca geothermometer mixing models at a relatively high temperature indicative of a possible higher temperature resource at depth. Preliminary evaluation shows the following when evaluating the correlation in the success of this proposed mixing model to estimate reservoir temperatures to trends in B, Cl and Temperature. There is no correlation in its success when the higher temperature fluid also has the higher B and Cl concentration. However, when a cross over in mixing models does occur, the higher temperature fluid is more apt to also have higher B and Cl concentrations. Many different mixing scenarios need to be tested and evaluated to determine the exact conditions under which this type of mixing model can be expected to yield reliable results. For instance, we consider another example where the estimated temperature is close to the measured reservoir temperature at a producing power plant. We plan to conduct statistical analyses (correspondence analyses as one test) to determine under what conditions the current, preliminary model can be expected to perform with some degree of reliability. We will use the mixing model under various scenarios and in different locations, including those outside the Great Basin. The statistical analysis will include evaluation of correlation of the following factors with degree 66

5 to which the model produces reliable results: distance between fluids used in calculations, temperature difference between them, difference in temperature estimated between the Na-K-Ca and SiO 2 geothermometers, whether the Na-K-Ca geothermometer has a higher estimated temperature than the SiO 2, whether B, F, Li and Cl are higher in the higher temperature fluid than the lower temperature fluid or not, a weighting of these against whether there is a modeled cross-over temperature or not (whether there is any trend calculated, or not as some that have been tested thus far show no trend), and other factors that emerge as other systems are modeled and evaluated. Conclusions A new method using mixing models has been presented here that shows promise in the estimation of subsurface reservoir temperatures in certain circumstances. These circumstances include A: closely spaced springs and wells with different temperatures that may represent mixing in varying proportions of two different source fluids, and B: one spring or well whose temperature and fluid composition varies over time, indicating time-varying mixing ratios of two different source fluids. Many more scenarios need to be tested and evaluated. We plan to evaluate the method both inside and outside the Great Basin and analyze the results statistically to help determine exactly under what circumstances the method will and will not provide reliable subsurface temperature estimates. However, preliminary analysis indicates it may be useful in cases where the Na-K-Ca geothermometer overestimates the subsurface temperature relative to the SiO 2 geothermometer, which is a common, although not consistent, situation in Nevada geothermal systems. Acknowledgements This material is based in part upon work supported by the U.S. Department of Energy under instrument number DE-FG7-2ID References Coolbaugh, M. F., J. E. Faulds, C. Kratt, G. L. Oppliger, L. Shevenell, W. M. Calvin, W. J. Ehni, and R. E.Zehner, 7, Geothermal potential of the Pyramid Lake Paiute Reservation, Nevada, USA: Evidence of previously unrecognized moderate-temperature (15-17 C) geothermal systems: Geothermal Resources Council Geothermal Bulletin, v. 36, n. 3, p Edmiston, R.C., and W.R. Benoit, Characteristics of Basin and Range geothermal systems with fluid temperatures of 15ºC to ºC. Geothermal Resources Council Transactions v. 8, p Fournier, R.O., Chemical geothermometers and mixing models for geothermal systems. Geothermics 5, p Fournier, R.O., Application of Water Geochemistry to Geothermal Exploration and Reservoir Engineering. In: Rybach, L. and Muffler, L.J.P., Geothermal Systems: Principals and Case Histories. Wiley, Chichester, p Fournier, R.O., and R.W. Potter II, Magnesium correction to the Na-K-Ca chemical geothermometer. Geochim. Cosmochim. Acta 43, p Mariner, R.H., T.S. Presser, and W.C. Evans, 1983, Geochemistry of active geothermal systems in the northern Basin and Range Province. Geothermal Resources Council Special Report No. 13, p Shevenell, L., and T. DeRocher, 5. Evaluation of chemical geothermometers for calculating reservoir temperatures at Nevada geothermal power plants. Geothermal Resources Council Transactions 29, p