Measurement of Heat Loss Associated With Shallow Thermal Aquifers in Nevada, USA

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1 GRC Transactions, Vol. 37, 2013 Measurement of Heat Loss Associated With Shallow Thermal Aquifers in Nevada, USA Mark Coolbaugh 1 and Chris Sladek 2 1 Great Basin Center for Geothermal Energy, University of Nevada, Reno, NV, and Renaissance Gold, Inc., Reno, NV 2 Dept. of Geological Sciences & Engineering, University of Nevada, Reno, NV Keywords Heat loss, heat flux, heat, flux, loss, shallow, temperature, survey, aquifer ABSTRACT Measurement of temperatures at multiple depths in shallow, 2-meter deep probes can be used to calculate temperature gradients and heat loss associated with shallow thermal outflow aquifers of geothermal systems. In the Great Basin, heat loss at shallow depths varies significantly over the course of a year in response to temperature changes at the earth s surface; during summer months, heat flux in large portions of geothermal areas can be negative (i.e., directed downwards) due to ground heating from solar radiation. Conversely, heat loss during winter months is much greater. Multiple measurements of shallow temperatures over the course of a year were used in this study to calculate mean annual temperature gradients at a depth of 1.5 to 2.0 meters at the Desert Peak and Desert Queen geothermal areas in Churchill County, NV, USA, and these data were combined with thermal conductivity data to calculate seasonally adjusted annual heat loss associated with these shallow aquifers. Mean annual heat loss associated with the Desert Peak shallow aquifer is estimated at 9.5 MWt. If a nearby second aquifer is included, the total heat loss is estimated at 20 MWt. At the Desert Queen area, located 10 km northeast of Desert Peak, mean annual heat loss associated with another shallow thermal aquifer is estimated at 18 MWt, based on a correlation defined at Desert Peak between average 2-meter temperatures and average temperature gradients, and assuming that climatic conditions are similar at both areas. The shallow aquifer heat loss at Desert Peak of 9.5 MWt compares well with the initial electrical production capacity (name plate capacity of 12.5 MWt as of 1985) at the Desert Peak power plant. If the second shallow heat loss zone is included, the total heat loss of 20 MWt is similar to the expanded power plant capacity at Desert Peak of approximately 25 MWt. Of course, shallow thermal aquifers are not always present at geothermal systems, nor are they always detectable with shallow temperature surveys. Nevertheless, the similarity between the shallow heat loss and power plant production capacities suggests that shallow aquifer heat loss can be used to help assess the electricity generation potential of a geothermal system. As a subset of the total conductive heat loss of a geothermal system, heat loss associated with shallow thermal aquifers is of special significance because it is fed by convection of thermal fluids from depth. This in turn implies a degree of permeability connectivity of the type sought when drilling for geothermal reservoirs. The size and strength of shallow temperature anomalies at the Desert Peak and Desert Queen areas are similar to those found at other geothermal systems in Nevada, suggesting that heat losses of MWt may be fairly typical of shallow thermal outflow aquifers associated with geothermal systems in the Great Basin. These heat losses are much greater than those typically associated with hot springs, and they comprise a significant fraction of the total heat loss associated with geothermal systems. A number of geothermal systems with such shallow thermal aquifers have not been tested with deep drilling, and this data suggests that they may be capable of sustaining electrical energy production. Introduction Thermal waters commonly flow outwards and away from upwelling zones of geothermal systems to form shallow thermal aquifers of significant size, with horizontal extents in some cases in Nevada exceeding 20 km 2. In the arid Great Basin of the western United States, a large percentage of these shallow aquifers are blind, in the sense that hot springs are not present to provide surface evidence of the existence of these aquifers and their associated deeper geothermal reservoirs. Shallow temperature surveys at depths of 1-2 meters have been proven effective in detecting and mapping the location of these thermal aquifers (Coolbaugh et al., 2007; Sladek et al., 2007; Kratt et al., 2008, 2009, 2010). For example, at Desert Queen, the inferred thermal aquifer is 5.8 km long and 1.6 km wide, with a maximum observed anomaly to background temperature at 2 meters of approximately 22 C (Table 1). The actual thermal 249

2 aquifer lies at a depth of roughly 50 meters and approaches boiling temperatures in places, based on temperature gradient drilling (Benoit et al., 1982). The average size and strength of 2-meter temperature anomalies mapped at 12 geothermal areas in Nevada by the Great Basin Center for Geothermal Energy at the University of Nevada, Reno are 9.4 km 2 and 11 C, respectively (Table 1). Generation of anomalies of this size suggests a significant amount of total diffuse flow in these aquifers at significant temperatures. This in turn suggests that total convective heat dissipation is substantially greater than that associated with most hot springs, whose heat loss is typically insignificant compared to the total heat loss associated with most geothermal systems (Wisian et al., 2001). This should not be surprising, given that even for non-thermal, precipitation-derived water, groundwater flow volume predominates over surface flow volume. Thus, if heat losses associated with shallow thermal aquifers could be quantified, they could provide relevant information for assessing the total magnitude of near-surface convective geothermal flux, which in turn might provide information relevant towards the prediction of potential size and permeability of an underlying geothermal system. 2-meter Temperature ( C) Predicted Sine Curve Measured 1.5m Temps Date in Years Figure 1. Fitting of five temperature measurements to a sine curve for calculation of temperature as a function of time for one measurement site at a depth of 1.5 meters. The curve was fit to the data using an iterative least-squares calculation in Excel using the Solver function. Table 1. Size and strength of 2-meter temperature anomalies measured over a number of shallow thermal aquifers in Nevada. Most of these aquifers are blind. Data from Great Basin Center for Geothermal Energy at the University of Nevada, Reno and based in part on published data (Coolbaugh et al., 2007; Sladek et al., 2007; Kratt et al., 2008, 2009, 2010) Maximum Background Temp C Length Width Area AREA 2-m Temp Temp C Max - Min (km) (km) (km2) Astor Pass Bonham Ranch Desert Queen Tungsten Mountain Teels Marsh Rhodes Marsh Columbus Marsh Gabbs Valley Dead Horse Wells Hawthorne West Hawthorne East Emerson Pass Mean Values: This study uses temperature data from 2-meter temperature surveys to calculate the heat flux of shallow thermal aquifers in the Desert Peak and Desert Queen areas of Churchill County, Nevada. Previous papers discuss the field implementation details of these 2-meter surveys (Coolbaugh et al., 2007, 2010; Sladek et al., 2007, 2012). Methodology, Desert Peak Aquifers Shallow heat flux at any point in time can be calculated using a formula provided by Oke (1978), G = K ( T/ z) (1) where G = the soil heat flux, K = the thermal conductivity, and T/ z = the vertical soil temperature gradient. 250 At Desert Peak, the temperature gradient at a depth of 1.75 meters was calculated using simultaneous measurements of temperatures at depths of 1.5 and 2.0 meters in 2-meter probes inserted into the ground. These twozone temperature measurements were recorded at 56 station locations chosen to spatially represent the shallow temperature anomaly at Desert Peak defined by previous temperature gradient drilling. At a depth of 1.75 meters, the temperature gradient varies continuously over the course of a year due to the influence of seasonal temperature variations at the surface, whose affects penetrate to depths of up to 20 meters (Olmsted and Ingebritsen, 1986). In order to model seasonal temperature gradient variations and calculate the mean annual temperature gradient, temperatures at these 56 stations were measured five times (during field campaigns of September, 2010; January-February, 2011; May, 2011, July-August, 2011, and November, 2011). Best-fit sinusoidal curves, with a modeled zero net annual temperature drift, were then fit to the 1.5 and 2.0 meter data using Excel spreadsheets with the iterative Solver function; the degree of fit was generally excellent (Fig. 1). Using these smoothed temperature functions, the temperature gradient as a function of time could be calculated (Fig. 2). Large but consistent variations in the magnitude and sign of temperature gradients are observed over an annual cycle, and even in geothermally anomalous areas, temperature gradients can temporarily become negative (decreasing temperature with depth) during the hotter summer months (Fig. 2). From these best-fit curves and graphs, mean annual temperatures at 1.5 and 2.0 meter depths, and mean annual temperature gradients between 1.5 and 2.0 meters, were calculated. It is assumed that in the desert environment that typifies the Desert Peak and Desert Queen areas, precipitation and vegetationrelated effects (transpiration) have a negligible effect on the heat flux at a depth of 1.5 to 2.0 meters. Most precipitation events are relatively minor and result in insignificant contribution to soil

3 Temperature Gradient (degrees C/meter) /21/10 9/29/10 1/7/11 4/17/11 7/26/11 11/3/11 2/11/12 moisture at a depth of 1.5 to 2 meters. Extreme weather events at Desert Peak were found to impact temperatures at a depth of 2m by only 0.5 o C (Sladek et al., 2012), such effects not affect the calculation of overall heat flow. Thermal conductivities at each of the measurement points could have been assigned based on published values for sand, gravel, and unconsolidated rock types observed in the field, but instead it was decided to rely as much as possible on field measurements of thermal diffusivities in order to minimize uncertainties. Thus, thermal conductivities were estimated using calculated thermal diffusivity in combination with estimates of soil moisture content, using the following relationship, K = (α s ) c d (2) where α s = soil thermal diffusivity c = soil specific heat, and d = soil density. For stations with multiple temperature measurements, soil thermal diffusivities were calculated using the observed annual amplitudes of temperatures at two different depths (1.5 and 2.0 meters) according to the following equation (Jury et al., 1991): z α s = π 1 z 2 ln[δt(z 1 ) / ΔT(z 2 )] Time of Year Figure 2. Temperature gradient as a function of time at 1.75 meter depth for two stations in the Desert Peak area. Station 12E (upper red curve, diamonds) is within a stronger portion of the shallow temperature anomaly and has a calculated mean annual heat flux of 2,300 mw/m2, but still experiences negative temperature gradients over short durations of the year. Station 14L (lower blue curve, triangles) is from a weaker portion of the shallow temperature anomaly and has a calculated mean annual heat flux of 510 mw/m2. Temperature gradients at station 14L are negative for significant portions of the year, but positive gradients clearly outweigh negative gradients. The large annual range of temperature gradients underscores the importance of calculating heat loss with annual-normalized data. 2 / τ (3) where z = depth, τ = period of temperature cycle (1 year), and ΔT(z 1 ) and ΔT(z 2 ) = temperature amplitudes over 1 year at depths z 1 and z 2 respectively. Percent water saturation was calculated for the same samples by assuming that the range in observed thermal diffusivities was influenced primarily by water content (Sladek et al., 2012). Percent water saturation was then used to estimate the specific heat 14L 12E of the soils by interpolating between values for dry and saturated soil (0.8 and 1.48 j/g, respectively). Similarly, densities were interpolated using published values for dry and saturated sand and gravel (1.65 and g/cm 3, respectively). Equation (2) was then used to calculate thermal conductivities, which in turn were used to calculate mean annual heat flux using equation (1) with the mean annual temperature gradient. Seven of the temperature measurement stations were emplaced into bedrock (basalt and opal-cemented sands). For basalt, thermal conductivity, specific heat and densities were taken from published values for basalt, and for opal-cemented sands, published values for sandstone (two stations) were used. Physical and thermal properties were taken from multiple published sources (CRC, 2009; Robertson, 1988; Ochsner et al., 2001). In addition to the 56 stations at which temperatures were measured five times over the course of a year, and for which heat loss was calculated using the methods described above, temperatures were measured at 51 additional fill-in stations. At these fill-in stations, the temperature was measured only once. Heat flux was estimated at these fill-in stations by estimating the mean annual temperature gradient. This was accomplished by using a linear relationship between the mean annual temperature gradient calculated using the methods described above, and the mean annual temperature at a depth of 2 meters (Fig. 3). The mean annual 2-meter temperature at each of the fill-in stations was estimated by applying a seasonal correction factor to the single temperature measured at each of these stations. This linear correction factor was derived from the sine curve of annual temperature variations at the stations where multiple temperatures were measured. Average Gradient (degrees C/meter) y = x R 2 = Average Temperature (degrees C) Figure 3. Relationship between mean annual temperature gradient at 1.75 meters and the mean annual temperature at 2.0 meters for measurement points in the Desert Peak area. The best-fit line was calculated only from measurements in unconsolidated soils (light blue diamonds). Seven bedrock points were excluded and two points with abnormally high soil moisture contents were also excluded. Dark blue points denote fill-in stations for which temperature measurements over multiple dates were not made. Calculated average annual temperatures for these points were applied to the equation to calculate estimated mean temperature gradients. Thermal conductivities for fill-in stations (all of which were placed into unconsolidated materials) were based on values calculated from the multiple-temperature stations for similar 251

4 unconsolidated materials. The best spatial predictor of thermal conductivity appears to be the presence or absence of rocky soils near areas of bedrock. As such, soils in rocky areas have an average thermal conductivity of W/m C and non-rocky soils have a slightly lower average thermal conductivity of W/ m C. These values were assigned to fill-in stations depending on proximity to areas of rock outcrop. Mean heat losses for each of the 107 temperature stations were plotted on digital maps in ArcGIS. An interpolated map of heat flux was then created using inverse distance weighting to the third power using the five nearest neighbors. Total heat loss over the anomalous area of the map was then calculated by summing on a pixel by pixel basis the product of the heat flux times the associated area. The calculation was limited to areas of heat loss 400 mw/ cm 2 (with a peak value of 4,000 mw/cm 2 ). These areas correspond to areas of anomalous 2-meter temperatures which are believed to largely correspond to the location of shallow thermal aquifers. Methodology, Desert Queen Aquifer In the Desert Queen area, approximately 10 km northeast of Desert Peak, a shallow thermal aquifer approximately 5.8 x 1.6 km in aerial extent was first documented by temperature gradient drilling (Benoit et al., 1982) and then by a 2-meter shallow temperature survey (Coolbaugh et al., 2007; Sladek et al., 2007). Only six 2-meter stations have had their temperatures measured at multiple dates over the course of a year or more. For the remainder of the stations at which temperature was measured only once, an approximate estimate of heat loss was made by assuming that the relationship between 2-meter temperatures and 1.75 meter temperature gradients is the same at Desert Queen as it is at Desert Peak. This is considered likely since the soil composition is broadly similar in both areas and climatic conditions are also likely to be similar. The six multi-date measurement stations at Desert Queen were used to calculate the relationship between temperature measured at any given time of the year and average annual temperature at 2-meter depths. This relationship was used to determine a temperature correction which was applied to the remaining temperature stations so that their temperatures would be approximately equivalent to annual mean temperatures. Previous 2-meter temperature studies indicate that this seasonal correction is reasonably accurate. The relationship between average annual 2-meter temperature and mean annual temperature gradient defined at Desert Peak (Fig. 3) was then used to assign mean annual temperature gradients to the remainder of the stations at Desert Queen. The mean weighted average thermal conductivity for unconsolidated materials at Desert Peak (0.617 W/m 2 C) was then adopted at Desert Queen, where none of the stations used in the survey were located in bedrock. In a manner directly analogous to Desert Peak, mean annual heat losses for all points were entered on digital maps in ArcGIS and interpolated heat flux maps were created using inverse distance weighting with a power of 3 and the nearest 5 neighbors. The calculation was limited to areas of heat loss 400 mw/cm 2 (with a peak value of 5,000 mw/cm 2 ). These areas correspond to areas of anomalous 2-meter temperatures which are believed to largely correspond to the location of shallow thermal aquifers. Results Total heat losses from shallow thermal aquifers are estimated at 18 MW for the Desert Queen area (Fig. 4) and 9.5 MW for a broad area overlapping the Desert Peak producing geothermal field (eastern polygon on Fig. 5). If a second thermal anomaly west of Desert Peak is included in the calculations (Fig. 5), the Figure 4. Mean annual heat flux measured at a depth of 1.75 meters in the Desert Queen area. Interpolation method was inverse distance to the third power using the five nearest neighbors. Heat flux color coding for sample points (black squares) and interpolated surface: red = mw/ m 2, orange = mw/m 2, yellow = mw/m 2, green = mw/m 2, light blue = mw/m 2, dark blue = mw/m 2. The interpolation was limited to the black polygon defining the limits of heat flux at 400 mw/m 2, which coincides with the limits of the 2-meter temperature anomaly. Total estimated heat loss is 18 MW. Black squares define a 1 km x 1 km grid. North is up. Figure 5. Mean annual heat flux at a depth of 1.75 m in the Desert Peak area. Interpolation method was inverse distance to the third power using five nearest neighbors. See Fig. 4 for heat flux color coding. The interpolation was limited to the black polygons defining the limits of heat flux at 400 mw/m 2, which approximately coincide with the limits of the 2-meter temperature anomaly. Eastern polygon totals 9.5 MW, and the larger polygon totals 20 MW. Black squares define a 1 km x 1 km grid. North is up. 252

5 total heat loss from shallow aquifers at Desert Peak rises to 20 MW, and rises to 38 MW for all three areas combined. A lower heat flux threshold of 400 mw/m 2 was used to define the limits of the calculations in this study, because this boundary approximately coincides with the area of anomalous 2-meter temperatures which are believed to roughly define shallow thermal aquifers in the subsurface. At this threshold, the anomalies at both Desert Peak and Desert Queen are largely open-ended; in other words, the 400 mw/m 2 heat flux anomaly appears to extend well beyond the limits of the shallow temperature surveys. This in turn suggests that the shallow thermal aquifers are superimposed on a regionally more extensive heat loss anomaly. Presumably this larger heat loss anomaly is caused by conduction from deeper geothermal reservoir(s). Total heat loss from these reservoirs has been estimated at 140 MW (Wisian et al., 2001). It is likely that the heat loss anomalies mapped herein include a component of conduction from deeper geothermal reservoirs. This may be especially true of the Desert Peak area, where the shallow heat flux anomaly of Fig. 5 overlaps the producing geothermal field. However, the strongest heat flux anomalies at Desert Peak are focused southwest of the producing field in the vicinity of paleo-hot spring deposits (opalized sands), suggesting that majority of this thermal anomaly is associated with shallow thermal outflow in the subsurface. In the Desert Queen area, temperature gradient drilling indicates that most of the thermal anomaly is underlain by a shallow thermal aquifer marked by a temperature reversal at a depth of roughly 50 meters, supporting the hypothesis that the anomaly corresponds to shallow thermal aquifer outflow. Discussion The heat flux estimates for shallow thermal aquifers in the Desert Peak and Desert Queen areas are much greater than typical heat losses directly attributable to hot springs (Wisian et al., 2001). This confirms expectations that hot springs are merely the tip of the iceberg in terms of total shallow convective outflow in geothermal systems. This is especially true of the arid Great Basin in the western United States, where many of these shallow outflow aquifers have no associated hot springs. The shallow heat loss estimate for the immediate Desert Peak area of approximately 9.5 MW compares favorably with the initial geothermal power capacity of the power plant at Desert Peak of 12.5 MW. The expanded plant capacity at Desert Peak (~25 MW) compares well with the combined shallow aquifer heat losses calculated for the entire Desert Peak area of approximately 20 MW. It is not expected that heat loss from shallow outflow aquifers will always match so well the production capacity of the underlying reservoir; indeed, shallow thermal aquifers may not exist in some geothermal systems and in others, the shallow aquifers may not be detectable with surface surveys due to the presence of overlying cold water aquifers or for other reasons. Nevertheless, as a subset of total heat loss from geothermal systems, the heat loss associated with shallow aquifers may carry heightened significance because of its derivation from shallow convective flow, which is likely to correlate to some degree with permeability in the underlying reservoir, due to the presence of hydraulic connectivity from depth to the near-surface environment. This connectivity cannot usually be appraised as effectively with hot spring heat flow, because hot springs are typically a much smaller component of total heat flow. Because of the greater heat transport associated with shallow thermal aquifers, total heat loss associated with them has the potential to translate into a measure of implied economic potential. As demonstrated in Table 1, a number of blind, shallow thermal temperature anomalies in Nevada have sizes and anomaly intensity similar to the aquifers mapped at the Desert Peak and Desert Queen areas. This in turn suggests that heat losses are likely to be broadly similar as well, and that some of these systems, a number of which have not been tested with deep drilling, could support geothermal power plants. Acknowledgements We wish to acknowledge the support of the Great Basin Center for Geothermal Energy, beginning with Lisa Shevenell, past director of the center, and continuing with Wendy Calvin, current director. Field work at Desert Queen was funded largely through U.S. Department of Energy instrument number DE-FG07-02ID14311, and field work at Desert Peak was funded largely through a research grant from the Nevada Renewable Energy Center, as managed by the Desert Research Institute. Field access was kindly provided by Ormat Technologies Inc. This study has benefited from discussions with Scott Tyler at the University of Nevada, Reno. References Benoit, W.R., Hiner, J.E., and Forest, R.T., 1982, Discovery and Geology of the Desert Peak Geothermal Field: A Case History: Nevada Bureau of Mines and Geology Bulletin 97, 82 p. Coolbaugh, M.F., Sladek, C., Faulds, J.E., Zehner, R.E., and Oppliger, G.L., 2007, Use of rapid temperature measurements at a 2-meter depth to augment deeper temperature gradient drilling: Proceedings, 32 nd Workshop on Geothermal Reservoir Engineering, Stanford University, Stanford, CA, Jan , 2007, p Coolbaugh, M.F., Sladek, C., and Kratt, C., 2010, Compensation for seasonal and surface affects of shallow (two-meter) temperature measurements: Geothermal Resources Council Transactions, v. 34, p CRC, 2009, CRC Hand Book of Chemistry and Physics 90 th ed Jury,W.A., Gardner W.R., and Gardner, W.H., 1991, Soil Physics, 5th ed., Wiley and Son, New York, 328 p. Kratt, C., Coolbaugh, M., Sladek, C., Zehner, R., Penfield, R., and Delwiche, B., 2008, A new gold pan for the west: discovering blind geothermal systems with shallow temperature surveys: Geothermal Resources Council Transactions, v. 32, p Kratt, C., Coolbaugh, M., Peppin, B., and Sladek, C., 2009, Identification of a new, blind geothermal system with hyperspectral remote sensing and shallow temperature measurements at Columbus Salt Marsh, Esmeralda County, Nevada: Geothermal Resources Council Transactions, v. 33, p Kratt, C., C. Sladek, and M. Coolbaugh, 2010, Boom and bust with the latest two-meter temperature surveys: Dead Horse Wells, Hawthorne Army Depot, Terraced Hills, and other areas in Nevada: Geothermal Resources Council Transactions, v. 34, p Ochsner, T.E., Horton, R. and Ren, T., 2001, A New Perspective on Soil Thermal Properties: Soil Science, v. 65, p

6 Oke, T.R., 1978, Boundary Layer Climate, John Wiley and Sons, New York, 372 p. Olmsted, F.H. and Ingebritsen, S.E., 1986, Shallow subsurface temperature surveys in the Basin and Range Province II. Ground temperatures in the Upsal Hogback geothermal area, west-central Nevada, USA; Geothermics, v. 15, n. 3, p Robertson, E.C., 1988, Thermal Properties of Rocks: USGS Open File Report, Sladek, C., Coolbaugh, M.F., and Zehner, R.E., 2007, Development of 2-meter soil temperature probes and results of temperature survey conducted at Desert Peak, Nevada, USA: Geothermal Resources Council Transactions, v. 31, p Sladek, C., Coolbaugh, M.F., Penfield, R., Skord, J., and Williamson, L., 2012, The influences of thermal diffusivity and weather on shallow (2-meter) temperature measurements: Geothermal Resources Council Transactions, v. 36, p Wisian, K.W., Blackwell, D.D., and Richards, M., 2001, Correlation of surface heat loss and total energy production for geothermal systems: Geothermal Resources Council Transactions, v. 25, p