Southeastern Idaho exhibits numerous warm springs, warm water from shallow
wells, and hot water from oil and gas test wells that indicate a potential
for geothermal development in the area. We have estimated reservoir
temperatures from chemical composition of thermal waters in southeastern
Idaho using an inverse geochemical modeling technique (Reservoir Temperature
Estimator, RTEst) that calculates the temperature at which multiple minerals
are simultaneously at equilibrium while explicitly accounting for the
possible loss of volatile constituents (e.g., CO
The state of Idaho in the US has high potential of geothermal energy. The US
Geological Survey has estimated that there is up to 4900 MWe of
undiscovered geothermal resources and 92 000 MWe of enhanced geothermal
potential within the state (Williams et al., 2008). Southern Idaho has been
regarded to have high geothermal potential for conventional as well as for
enhanced geothermal system (EGS) development (Tester et al., 2006). Geologic
evidence such as the passage of the Yellowstone hotspot, Pleistocene
basaltic flows, young volcanic features, and warm to hot springs (Mitchell,
1976a, b; Ralston et al., 1981; Souder, 1985) in southern Idaho indicate
that the area may have economically viable geothermal resources. More direct
evidence of a high-temperature regime at depth in the area is provided by a
limited number of deep wells with high bottom-hole temperatures (BHTs) such
as the King 2-1 well (202
As a part of an effort to assess the geothermal potential of southern Idaho, we assembled chemical composition of waters measured from numerous springs and wells in the region and used them to estimate reservoir temperatures using an inverse geochemical modeling tool (Reservoir Temperature Estimator, RTEst; Mattson et al., 2015). In this paper, we present results of RTEst applied to southern Idaho thermal water measured at a number of wells and springs.
The study area is located in both the Basin and Range and Rocky Mountains provinces. Specifically, the western part of the area has geographic characteristics of the Basin and Range such as wide and sediment-filled basins separating fault-bound ranges, whereas the eastern part consists of several thrust-bound narrow sub-parallel ridges with thinly filed basins (Mabey and Oriel, 1970). Geologically, the fold–thrust belt (Fig. 1a) in the area is a part of Sevier fold–thrust zone, locally known as the Idaho–Wyoming fold–thrust belt (Armstrong and Oriel, 1965).
Geology of the area includes thick sequences Paleozoic and Mesozoic carbonate-rich sedimentary rocks deposited in a passive margin setting (Armstrong and Oriel, 1965). During the Jurassic–Cretaceous periods these sedimentary sequences were deformed by compressive stresses associated with the Sevier orogeny resulting in numerous west-dipping low-angled thrust faults (Armstrong and Oriel, 1965). Starting in the Eocene and continuing to the Recent, extensional activities resulted in Basin and Range type topography with normal faults bounding ranges and wide valleys (Armstrong and Oriel, 1965; Dixon, 1982). Quaternary volcanic activity in some areas in the region (McCurry et al., 2011) resulted in volcanic resources (McCurry et al., 2008; Pickett, 2004).
The presence of several hot springs and warm springs indicates potential geothermal resources in southeastern Idaho. The western part of study area represents the amagmatic Basin and Range type geothermal system where convective upwelling dominates the thermal discharge along the extensional faults. The discharges of thermal water from springs and seeps in eastern and northern parts of the study area are also controlled by deep normal faults (Dansart et al., 1994). However, some recent works (e.g., McCurry et al., 2011; Welhan et al., 2014) also suggest a deep magmatic geothermal resource in this area. The conceptual model of magmatic-sourced geothermal setting in the fold–thrust belt in southeastern Idaho considers a magmatic geothermal resource at a depth of 12–14 km in an area beneath 58 ka rhyolite domes at China Hat located within the Blackfoot Volcanic Field (BVF) (Welhan et al., 2014). According to this hypothesis, the deep-sourced magmatic hydrothermal fluid from this zone migrates eastwards along the thrust faults and permeable Paleozoic and Mesozoic layers into a shallower (3–5 km) reservoir. The high-temperature and high-salinity (sodium chloride) thermal fluids encountered at depth in some deep wildcat petroleum wells (such as, the King 2-1 well in Table 1) are possibly associated with these migrated magmatic fluids (Welhan et al., 2014).
Depth and corrected bottom-hole temperatures (BHTs) of several wildcat oil exploration wells in southeastern Idaho (Ralston et al., 1981; Souder, 1985; Blackwell et al., 1992; Welhan and Gwynn, 2014).
Chemical compositions of numerous water samples from southeastern Idaho were assembled to assess the potential geothermal reservoir temperatures in the region. Over the last several decades, water samples from springs and wells in southeastern Idaho have been analyzed by several US government agencies and researchers for water quality and management, environmental remediation, and geothermal energy exploration (e.g., Young and Mitchell, 1973; Mitchell, 1976a, b; Ralston et al., 1981; Souder, 1985; Avery, 1987; McLing et al., 2002). A database is compiled of publicly available data for southeastern Idaho springs/wells. From a larger database, 50 water compositions (Table 2, Fig. 1b) were selected for the assessment of deep geothermal temperatures in southeastern Idaho.
Geothermometry is a low-cost but useful geothermal exploration tool that uses
the chemical compositions of water from springs and wells to estimate
reservoir temperature. The application of geothermometry requires several
assumptions: (1) the reservoir minerals and fluid attain chemical
equilibrium, and (2) the water that moves from the reservoir to the sampling location retains its chemical signatures (Fournier et al., 1974). The
first assumption is generally valid (provided there is a sufficiently long
residence time); however, the second assumption is more likely to be
violated. As reservoir fluids move toward the surface, the pressure on the
fluid decreases resulting in boiling and subsequent loss of volatiles (e.g.,
CO
Geothermal temperature predictions using multicomponent equilibrium geothermometry (MEG) provide apparent improvement in reliability and predictability of temperature over traditional geothermometers. The basic concept of this method was developed in the 1980s (e.g., Michard and Roekens, 1983; Reed and Spycher, 1984), and some investigators (e.g., D'Amore et al., 1987; Hull et al., 1987; Tole et al., 1993) have used this technique for predicting geothermal temperature in various geothermal settings. Other researchers have used the basic principles of this method for reconstructing the composition of geothermal fluids and formation brines (Pang and Reed, 1998; Palandri and Reed, 2001). More recent efforts (e.g., Bethke, 2008; Spycher et al., 2011, 2014; Smith et al., 2012; Cooper et al., 2013; Neupane et al., 2013, 2014, 2015a, b; Peiffer et al., 2014; Palmer et al., 2014; Mattson et al., 2015) have been focused on improving temperature predictability of the MEG.
Water compositions of selected hot/warm springs and wells in
southeastern Idaho used for temperature estimation. Elemental/species
concentrations are given in mg L
An additional advantage of MEG over traditional geothermometers is that it considers a suite of chemical data obtained from water analyses for temperature estimation. Although MEG has advantages over the traditional geothermometers, it is also subject to the same physical and chemical processes that can violate the basic assumptions of geothermometry. However, MEG also provides a quantitative approach to account for subsurface composition-altering physical and chemical processes through inverse geochemical modeling. Therefore, it is important to reconstruct the composition of geothermal water for estimation of reservoir temperature with a greater certainty.
A newly developed geothermometry tool known as Reservoir Temperature Estimator (RTEst) (Palmer et al., 2014; Mattson et al., 2015) is used to estimate geothermal reservoir temperatures in southeastern Idaho. The RTEst is an inverse geochemical tool that implements MEG with an optimization capability to account for processes such as boiling, mixing, and gas loss. A more detailed description about RTEst can be found elsewhere (e.g., Palmer et al., 2014; Neupane et al., 2014; Mattson et al., 2015).
The MEG approach requires that measured water composition include all components present in the reservoir mineral assemblage (RMA). For aluminosilicate minerals, this requires measured values of Al that are often not available in historical composition database. For water compositions without measured Al, an Al-bearing mineral (e.g., K feldspar) was used as a proxy for Al during geochemical modeling as suggested by Pang and Reed (1998).
Based on the geology of southeastern Idaho and literature assessment of secondary minerals generally associated with the dominant rock and water types, we assumed reservoir mineral assemblages (RMAs) consisting of idealized clays, zeolites, carbonates, feldspars, and silica polymorphs (chalcedony) to estimate equilibrium temperatures using RTEst. Recently, Mattson et al. (2015) reported that the RTEst results in similar temperature estimates for the same water compositions when applied with slightly different RMAs. Selection of one or two unrepresentative minerals in the RMAs produced larger uncertainties in estimated temperatures than the estimated temperatures themselves because of poor convergence (Mattson et al., 2015). Therefore, while selecting the RMAs for RTEst, it is recommended to consider local geology, water chemistry (e.g., pH), and expected range of the reservoir temperatures. For more detailed information on selecting RMAs, see Palmer et al. (2014).
Using an appropriate RMA and measured water composition, RTEst estimates an
equilibrium reservoir temperature (as well as a fugacity of CO
The weighting factors ensure that each mineral that contributes to the equilibrium state is considered equally and the results are not skewed by reaction stoichiometry or differences in analytical uncertainty. There are three options for weighting factors in RTEst: inverse of variance, normalization, or unit weights. They are discussed in more detail by Palmer et al. (2014). In this paper, we used a normalization method for weighting, which assumes that the analytical errors for all thermodynamic components expressed as basis species are equal and that the thermodynamic activity of water is unity and is invariant. Examples of weighting factors (normalization factors) for several minerals are given in Palmer et al. (2014).
Reported chemistry of waters measured from several hot/warm springs and wells located in southeastern Idaho.
Compositions of waters from hot/warm springs and wells in southeastern Idaho
are presented in Table 2. The pH values of southeastern Idaho thermal waters are
circum-neutral, ranging from 6.2 to 8.1, with arithmetic mean, median, and
standard deviation of 6.87, 6.70, and 0.51, respectively; the field
temperatures range between 20 and 84
The dominant cations in the southeastern Idaho thermal waters are Na and Ca
with minor amounts of Mg (Fig. 2). The thermal waters include samples
dominated by Cl, HCO
The Na-Cl and Ca-SO
The Ca-HCO
Only one sample represents Ca-Cl (Group IV) type water, the Rockland W-2
well located in the westernmost part of the study area (Fig. 1). Although
this water has some similarity with the Ca-HCO
The remaining two types of waters are mixed waters – Na-HCO
Southeastern Idaho waters from hot springs and wells plotted on Giggenbach diagram (Giggenbach, 1988). All partially equilibrated waters are of Na-Cl (Group I) type waters.
When plotted on a Giggenbach diagram (Giggenbach, 1988), the majority of the
southeastern Idaho waters in this study are in the immature zone with some
waters in the zone of partial equilibration (Fig. 3). The partially equilibrated waters in
Fig. 3 are from hot springs and wells near Preston, Idaho (Battle Creek and
Squaw hot springs), and distribution of these waters on Giggenbach diagram
indicates that these waters could have interacted with rock at a temperature
range of 260–300
Temperature (
Temperature estimation for Battle Creek hot spring near Preston,
Idaho.
Estimates of reservoir temperatures for southeastern Idaho thermal waters shown in Table 2 were made using RTEst and several conventional geothermometers (Table 3). The RMAs that were used in RTEst consisted of representative minerals (Mg-bearing minerals – clinochlore, illite, saponite, disordered dolomite; Na-bearing minerals – paragonite, saponite; K-bearing minerals – K feldspar, mordenite K, illite; Ca-bearing minerals – calcite, disordered dolomite; and chalcedony). For thermal waters that do not have measured Al concentration, a value determined from assumed equilibrium with K feldspar was used in the calculations.
In MEG, the reservoir temperature is estimated by assuming a representative
RMA with which the fluid in the reservoir is believed to have equilibrated.
Next, the activities of the chemical species in solution are determined and
the saturation indices [SI
Figure 4a shows typical
Three common composition-altering processes are degassing, mixing, and
boiling. In particular, the loss of CO
Mean and standard deviation
To account for possible composition-altering processes, RTEst was used to
simultaneously estimate a reservoir temperature and optimize the amount of
H
The optimized temperatures and composition parameters for the other southeastern Idaho waters reported in Table 2 were estimated using RTEst in the same manner. The estimated reservoir temperatures and associated standard errors are summarized in Table 3.
In addition to RTEst, other traditional geothermometers were also compared (Table 3, Fig. 5). Because most of the waters from thermal springs and wells in southeastern Idaho are geochemically immature (Fig. 3), the use of traditional geothermometers to estimate their temperatures is unreliable. Temperatures obtained with silica polymorphs and Na-K-Ca geothermometers can be quite variable, compared with the RTEst temperatures. As shown in Table 4, group-wise mean chalcedony-based reservoir temperatures are consistently cooler than the mean RTEst-calculated reservoir temperature.
Chalcedony-based reservoir temperatures were calculated using the observed silica concentrations. On the other hand, RTEst reservoir temperatures were calculated with reconstructed solute concentrations (i.e., optimized for water gain/loss). For the majority of samples, the chalcedony-based temperatures are lower than the RTEst-estimated temperatures (Fig. 5a). In general, wherever RTEst indicates that the sample contains an appreciable fraction of additional water, the RTEst temperature is higher than the chalcedony-based temperature for that sample.
Mg-corrected Na-K-Ca temperatures are relatively similar to the RTEst temperatures; however, the trend between mean RTEst and Na-K-Ca temperature varies with groups. In general, Na-K-Ca geothermometry predicts in cooler temperatures in the lower temperature range and hotter temperatures in the upper temperature range compared to the RTEst temperatures (Fig. 5b). The main weakness of Na-K-Ca geothermometer is poor reliability in waters with a significant amount of Mg. Even the Mg-corrected Na-K-Ca temperature estimates have poor reliability if the Mg concentration in thermal waters is high and is controlled by non-chlorite minerals. In southeastern Idaho, the Mg concentration in thermal waters is likely to be controlled by carbonate minerals (limestone/dolomite) as these waters may have interacting with carbonate sequences in the reservoir or along the flow path. Compared to the RTEst temperatures, Na-K-Ca temperatures are lower for all but Group 1 waters. The overprediction of temperature for Group 1 waters is likely caused by the disproportionate (relative to Na and K) loss of Ca to calcite precipitation as suggested by Young and Lewis (1981).
RTEst temperatures versus chalcedony
As reported in Table 1, some of the wildcat petroleum wells in the fold–thrust
belt in southeastern Idaho have measured BHTs. In general, RTEst-calculated reservoir
temperatures appear positively correlated with nearby BHTs, supporting the argument
that MEG can be used to predict deep geothermal reservoir temperatures.
The North Eden Federal 21–11 well (2618 m) is located east of the Bear Lake,
near the border of Idaho, Utah, and Wyoming. This well has slightly lower BHT (84
The highest BHT was recorded for the
King 2-1 well (3927 m, 202
The geological setting coupled with the direct evidence of thermal expressions such as hot/warm springs in the area suggests that southeastern Idaho has good potential for geothermal resources. Our temperature estimates using RTEst with water compositions from southeastern Idaho thermal springs and wells indicate the presence of geothermal reservoirs at depth. Specifically, thermal waters of the Battle Creek hot springs and the Squaw Hot Springs suggest a promising geothermal prospect near Preston, Idaho. The US Department of Energy-sponsored new initiative in the Preston area with geological, geochemical, and geophysical approaches is expected to further assess the geothermal potential. In several other areas, oil and gas wildcat wells indicate presence of high temperature at depth; however, the moderate RTEst temperature estimates from nearby thermal springs and shallow wells might reflect mixing of local groundwater with deep thermal water and/or re-equilibration of high temperature thermal waters in a shallow low temperature zone.
Funding for this research was provided by the US Department of Energy, Office of Energy Efficiency & Renewable Energy, Geothermal Technologies Program. We appreciate the help from Will Smith and Cody Cannon for this study. Reviews by John Welhan and an anonymous reviewer greatly improved the quality of this paper. Edited by: H. Rüter Reviewed by: J. Welhan and one anonymous referee