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Article

Water–Rock Interactions, Genesis Mechanism, and Mineral Scaling of Geothermal Waters in Northwestern Sichuan, SW China

1
Yibin Research Institute, Southwest Jiaotong University, Yibin 644000, China
2
Engineering Research Center of Geothermal Resources Development Technology and Equipment, Ministry of Education, Jilin University, Changchun 130026, China
3
Sichuan Hua Di Building Engineering Co., Ltd., Chengdu 610081, China
4
Sichuan Province Engineering Technology Research Center of Geohazard Prevention, Chengdu 610081, China
5
College of Engineering, Tibet University, Lasa 850000, China
*
Authors to whom correspondence should be addressed.
Water 2023, 15(21), 3730; https://doi.org/10.3390/w15213730
Submission received: 24 September 2023 / Revised: 21 October 2023 / Accepted: 23 October 2023 / Published: 25 October 2023
(This article belongs to the Topic Groundwater Pollution Control and Groundwater Management)

Abstract

:
Geothermal resources are the vital renewable energy for resolving energy crisis and environmental deterioration. Understanding hydrogeochemical processes, genesis mechanisms and scaling trends is crucial for securing the sustainable utilization of geothermal resources. In this study, fourteen geothermal waters were collected for hydrochemical and δ2H–δ18O isotopic analyses in northwestern Sichuan, SW China to clarify hydrogeochemical processes, genesis mechanisms, and scaling trends. Geothermal waters were recharged via atmospheric precipitation. Three different types of geothermal waters were identified using a piper diagram. Class 1 geothermal water with HCO3–Na and HCO3–SO4–Na types formed in the contact zone with Yanshanian intrusions and heated by residual radioactive heat. The hydrochemical processes were sodium/potassium silicate dissolution and positive cation–exchange. Class 2 geothermal water with HCO3–Ca and HCO3–Ca–Mg type was carbonate–type and heated by geothermal gradient. The dissolution of carbonate minerals dominated the hydrochemical process. Class 3 geothermal water with the SO4–Ca–Mg type was determined within deep faults. The dissolution of carbonatite and gypsum minerals and the oxidation of sulfides played a vital role in the hydrochemical process. The reservoir temperatures of geothermal waters followed the orders of Class 1 (74.9–137.6 °C) > Class 3 (85.9–100 °C) > Class 2 (38.7–93.5 °C). Calcium carbonate scaling should be paid attention to in Class1 and Class 3 geothermal water, and calcium sulfate scaling merely occurs in Class 3 geothermal water. This study provides vital information for geothermal exploitation in western Sichuan and other similar areas.

1. Introduction

Because of energy shortage and environmental deterioration, the development and usage of clean energy have become a hot topic worldwide [1]. In the context of the “dual carbon” goal, geothermal energy, as a significant renewable energy, can effectively reduce carbon emissions and alleviate global warming [2,3,4]. Understanding the hydrogeochemical process and genesis mechanism of geothermal water is a prerequisite for the development and utilization of geothermal resources [5,6,7,8]. Meanwhile, the scaling of fluid components is a serious problem restricting the sustainable geothermal exploitation [9,10]. Therefore, the hydrogeochemical process, genesis mechanism, and scaling trends of geothermal waters play a vital role in geothermal study [11].
The hydrogeochemical properties in geothermal fluid provides insights into the ion source and reservoir temperature of geothermal water, which can reveal the genesis of geothermal systems [5,6,7,8]. Correlation analysis can explore the relationship between hydrochemical components of geothermal fluid [12,13]. The reservoir temperature of the geothermal system is mainly based on mineral thermodynamics, such as SiO2 geothermometer, silicon–enthalpy equations, cationic geothermometer, and the multi–mineral equilibrium [14]. δ2H–δ18O isotopes have emerged as a key technique for determining the recharge source of geothermal water [15,16]. Quantitative calculations have been widely used as a proven, inexpensive and effective method for identifying scaling trends of geothermal water [17].
Abundant geothermal resources had been investigated in the Ganzi and Aba areas of western Sichuan, SW China. However, significant imbalance exists in geothermal research between Ganzi and Aba areas. Great progress in geothermal exploitation has been achieved in Ganzi area of western Sichuan for decades, such as in hydrochemical processes, genesis mechanisms, and regional geological background of the geothermal resources in the Xianshuihe, Ganzi–Litang, and Jinshajiang fault zones of western Sichuan [18,19,20,21]. Little research has been carried out on geothermal resources in the Aba area compared to those in the Ganzi area. Knowledge of the hydrochemical processes and genesis mechanisms of geothermal waters have yet to be revealed in the Aba region. Additionally, the scaling of fluid components is a vital index in the exploitation of geothermal resources [9,10]. Therefore, 14 groups of geothermal water samples were collected in Aba area for hydrogeochemical and δ2H–δ18O isotopic analyses. The aims of this study were (1) identifying hydrochemical types and hydrochemical process of geothermal waters, (2) clarifying reservoir temperature, (3) analyzing recharge sources and elevation, and (4) estimating the scaling trend of geothermal water. These achievements would provide a significant reference for geothermal exploitation and utilization in western Sichuan and other similar areas.

2. Materials and Methods

2.1. Geological Setting

Western Sichuan is situated at the convergence of the Tibetan Plateau and the Sichuan Basin. Tectonically, it belongs to the southwest edge of the Songpan–Ganzi Indo–Chinese orogenic belt [7]. Because of the active neo–tectonic processes, amounts of geothermal resources were developed here [20,22]. The study area is situated in the north region of western Sichuan, with its longitude ranging between 100°30′ E and 104°30′ E and latitude between 30°35′ N and 34°20′ N. It is characterized by high mountain valleys with the highest elevation of 5588 m and the lowest elevation of 1640 m. The study area experiences a plateau monsoon climate, with an average annual temperature of 8.2 °C and an annual rainfall ranging from 500–830 mm [7,23]. The entire region is traversed by the Min River and its tributaries.
The Aba area experienced complex regional tectonics due to belonging to the Songpan–Ganzi fold belt [24]. The fold belt extends in a northeast–southwest direction, ranging from 40° to 50°. It is bounded by the Maqin–Lueyang deep fault zone in the north, the Minjiang fault zone in the east, and the Qinling trough fold system and the Yangzi platform to the east of the Maowen deep fault zone. Many faults were developed in the study area, including the NE–trending Maowen deep fault zone, the E–W–trending Maqin–Lueyang deep fault zone, the N–S–trending Minjiang–Huya fault zone, and other, smaller faults like the Maerkang fault and Miyaluo fault (Figure 1). The generation, storage, and circulation of geothermal fluid in the region are critically dependent on these faults. The fault’s tensile fracture zones offer ideal passageways and heat reservoirs, and the wide feather–jointed fissures create water–conducting channels that allow the hot springs to be exposed. Intrusive rocks, such as Triassic granite, phyllite, and other types, are scattered in the south of the Aba area. The sedimentary strata—including Sinian and Silurian dolomite; Quaternary and Triassic sandstone; Triassic calcisilicarenite, slate, pebbly sandstone, and sandstone; Quaternary and Cambrian conglomerate; and a few crystallized chert—are widely distributed in the north of the study area.
The geographical locations of geothermal water are mainly concentrated in Songpan county and Mao–Li–Wenchuan counties (Figure 1), and their exposed elevation range is 1703–3920 m [7]. The temperatures of the hot springs and geothermal wells ranges from 10.5 °C to 48 °C and from 38 °C to 65 °C, respectively. The Bipenggou geothermal well has the highest water temperature, reaching 65 °C (Figure 2a). The geothermal water flow rate varies between 2.4 L/s and 3.0 L/s. Sulfur odor smells are present in Jiyugou, Yuansanzi, Jiangzha, and Heta hot springs, and white calcified deposits are found at the mouth of the Yuansanzi hot spring (Figure 2b–e). Additionally, the Erdaohai hot spring is surrounded by a human–made hole to form a pool, with lumpy yellow sinter deposit at the bottom (Figure 2f). Similarly, the Guergou hot spring has been buried by a landslide, and it is now held downhill by a pipe and stored in a pool (Figure 2g,h). The Kejiu hot spring is artificially drilled water, the well is 46 m deep, and geothermal water which is acidic gushes out from the wellhead (Figure 2i).

2.2. Methods

2.2.1. Sampling and Analysis

The water samples were collected in 2019 and 2020. The initial determinations of temperature, acidity and alkalinity (pH), and total dissolved solids (TDS) were carried out in the field using a Multi3630IDS portable multiparameter water quality meter from Germany. Additionally, a Gran titration was conducted to determine the HCO3 content using HNO3. All water samples were initially filtered using a 0.45 μm filtration membrane. The 550 mL HDPE bottles were washed three times in the field before collecting the samples, which were then sealed with wax. The comprehensive analysis of the geothermal water samples was conducted by Sichuan Huadi New Energy Environmental Protection Technology Co. Ltd., while the δ2H–δ18O isotopic analysis was performed by the Institute of Hydrogeology and Environmental Geology, Chinese Academy of Geological Sciences. The concentrations of major cations (K+, Na+, Ca2+, and Mg2+) and major anions (Cl and SO42−) in the samples were determined using inductively coupled plasma emission spectrometry (ICP–OES, testing precision 0.3–2.0%) and ion chromatography (Diona ICS–1100, testing precision 0.2%). The charge balance error was maintained below ±5%. δ2H–δ18O isotopes were measured using high–temperature thermal conversion element–isotope ratio mass spectrometry (HTC–IRMS) and Gasbench II isotope ratio mass spectrometry (Gasbench II–IRMS), respectively. The results were compared to the Vienna Standard Mean Ocean Water (VSMOW) as a standard, and the accuracies of δ2H and δ18O measurements were 1.0‰ and 0.2‰, respectively.

2.2.2. Geothermometer

The most–used geothermometer, the SiO2 geothermometer, provides a reliable estimate of the geothermal reservoir temperature of geothermal water. The corresponding empirical equations of the quartz geothermometer are as follows [25]:
No   steam   loss :   T = 1309 / ( 5.19 l o g ( S i O 2 ) ) 273.15
Maximum   steam   loss :   T = 1522 / ( 5.75 l o g ( S i O 2 ) ) 273.15
where SiO2 represents SiO2 solubility in mg/L.
Geothermal water from the deep upward transport is frequently mixed to varying degrees with shallow cold water, so silica enthalpy equations and the silica enthalpy graphic methods are used to determine the initial temperature of geothermal water and the ratio of cold water mixing [7,8]. The involving equations are as follows [25]:
S C X 1 + S h 1 X 1 = S s
ρ C S i O 2 X 2 + ρ H S i O 2 1 X 2 = ρ S S i O 2
where Sc is the enthalpy of cold water (J/g); Ss is the final enthalpy of the hot spring (J/g, there is a certain relationship between the temperature and the enthalpy of geothermal water [25]); Sh is the initial enthalpy of the geothermal water (J/g); ρ C S i O 2 is the mass concentration of SiO2 in the cold water (mg/L); ρSSiO2 is the mass concentration of SiO2 in the spring water (mg/L); ρHSiO2 is the initial concentration of SiO2 of the geothermal water (mg/L); X is the proportion of the cold water mixing.

2.2.3. Saturation Index

Saturation index (SI) is useful in understanding the mineral equilibrium in geothermal water [8,26]. In this study, we used the PHREEQC to calculate mineral saturation indices based on the equation [26]:
S I = l o g ( I A P / K )
where K is the equilibrium constant of the mineral dissolution reaction; IAP is the activity product of the relevant ions in the mineral dissolution reaction. When SI > 0, the mineral is oversaturated in the aqueous solution, and there is a tendency to precipitate; SI < 0, means that the mineral is not saturated in the aqueous solution; and when SI = 0, this suggests that the aqueous solution is exactly in equilibrium with the mineral.

2.2.4. Scaling Trend

Quantitative calculations are commonly employed as a reliable, cost–effective, and efficient approach to identifying scaling trends [17,27,28,29]. Thus, in this study, we have chosen quantitative calculations for predicting structural trends and analyzing corrosivity. The equations used for these calculations were presented in Table 1 and involve Larson’s index, Ryzner’s index, relative saturation index of gypsum (CaSO4–2H2O) (R.Sgypsum), and relative saturation of amorphous SiO2 (R.SSiO2).

3. Results

3.1. Hydrochemcial Facies

Table 2 shows that the study area’s geothermal water samples are classified into three categories. The piper diagram in Figure 3 displays the scatter plots of cations (Ca2+, Mg2+, Na+ + K+) and anions (HCO3, Cl and SO42−) in water samples, allowing for the classification of hydrochemical properties [30].
(1)
Class 1 geothermal water
Class 1 geothermal waters are located in the southern Aba area. Most geothermal water samples of Class 1 were HCO3–Na, while ABS06 had HCO3–SO4–Na. Low amounts of SO42− and Cl were found in most samples. The temperature of geothermal waters ranged from 23 to 65 °C, with pH values ranging from 7.0 to 9.5. Except for ABS07 and ABS11, geothermal water TDS ranged from 68 mg/L to 511 m/L. ABS06, ABS08, ABS10, and ABW02 had significantly lower Ca2+ and Mg2+ concentrations (Figure 4). This geothermal water had a higher Li concentration than the other two, and other trace element (F, Sr, and B) contents were similar.
(2)
Class 2 geothermal water
Class 2 geothermal waters are scatted in the northern Aba area. Geothermal water samples can be divided into two groups according to anions: one with HCO3, and the other with HCO3 and SO42− (ABS03). All samples included mainly Ca2+ and Mg2+ or their combinations. Thus, geothermal waters from this hydrothermal field were HCO3–Ca type, HCO3–Ca–Mg type, and HCO3–SO4–Ca–Mg type. The Schoeller diagram (Figure 4) demonstrated that these geothermal waters had more Ca2+ and Mg2+ than the southern area. TDS in geothermal water ranged from 305 mg/L to 1280 m/L at all sites, excepting ABS02 (2450 mg/L). It is worth noting that these geothermal waters had relatively lower temperatures (10.5 °C to 38.4 °C) and pH (6.5 to 7.4). Northern Aba geothermal waters had more diversified and complicated hydrochemical types than southern samples.
(3)
Class 3 geothermal water
Class 3 geothermal water only had one sample (ABS05), located in the eastern of Aba area. Similarly to the northern geothermal field, Ca2+ and Mg2+ dominated. However, according to the Schoeller diagram (Figure 4), the ABS05 sample had a higher concentration of SO42− (1360 mg/L) than the other two geothermal water samples, resulting in the SO4–Ca–Mg type water. The geothermal water had a temperature of 31.9 °C and a TDS value of 2150 mg/L. This geothermal water sample contained 4.84 mg/L Sr, which was higher than the others. It is also worth noting that ABS05 sample altitude was 1703 m, significantly lower than the altitude of other sample locations.

3.2. Oxygen and Hydrogen Isotopes (δ18O and δ2H)

A total of nine sets of δ2H and δ18O isotopes data were collected. The δ2H and δ18O values for Class 1 range from −132.1 to −86.0‰ and −18.1 to −12.1‰, respectively. The δ2H and δ18O values for Class 2 ranged from −102.5 to −96.7‰ and −15.3 to −14.0‰, respectively. The δ2H and δ18O values for Class 3 (ABS05) were −86.7‰ and −13.6‰.

4. Discussion

4.1. Ion Source Analysis

4.1.1. Correlation Analysis of Hydrochemical Parameters

Linear correlation between ions or indicators is frequently demonstrated using the Pearson correlation coefficient matrix [12,13]. Figure 5 showed strong positive relations between TDS, Ca2+, Mg2+, Na+, K+, Cl, HCO3, and B, with coefficients above 0.6. This suggested a strong correlation between the concentration of TDS and Ca2+, Mg2+, Na+, K+, Cl, HCO3, and B concentrations. Ca2+ and Mg2+ had a 0.8 correlation coefficient, indicating that carbonate mineral (such as dolomite) dissolution likely provided these elements, notably in Class 1 and Class 2 geothermal waters. Na+, K+, Cl, and HCO3 showed significant correlations with B (coefficients of 0.9, 0.9, and 0.8, respectively), suggesting that the origins of Na+, K+, Cl, and HCO3 may be similar to those of B.

4.1.2. Ion Ratio Analysis

Cl is commonly utilized as a significant ion for tracking hydrogeochemical processes due to its minimal alteration through water–rock interactions during the rise of geothermal water and its resistance to adsorption by solid–phase mineral surfaces [31,32,33]. In Figure 6a–c, there were relatively obvious linear correlations between the concentration of Cl and the concentration of Na+, K+, and B compared to other ions, indicative of their similar source from deep fluids in Aba area’s geothermal water. Additionally, the TDS was to some extent related to the concentration of Cl (Figure 6d), which was consistent with the Pearson correlation analysis results.
The major ion ratio of geothermal water can be used to determine the hydrochemical process [8,14,34]: Figure 7a indicates that the dissolution of salt rock minerals in the study area was very low.
Class 1 geothermal water: The relationship between Na+, K+, and HCO3 (Figure 7e) suggested that the elevated concentrations of HCO3 and Na+ may be attributed to the reaction products of deep underground water, CO2 and sodium/potassium silicate minerals—as shown in Equations (13) and (14) [34]. Additionally, the positive cation exchange (Equation (15)) was an important factor influencing the concentration of certain ions in this type geothermal water, especially in ABS07 and ABS11 hot springs (Figure 7f,g) [35]. Mover, the geothermal water points were located near the 100 °C equilibrium line (solid line) for kaolinite with muscovite, K–feldspar, paragonite, and albite. They were also located near the 200 °C equilibrium line (dashed line) for kaolinite with muscovite, paragonite, and gibbsite (Figure 7h,i) [36]. This suggested that the hydrothermal alteration provided Na+ and K+ sources for the geothermal water [14].
2NaAlSi3O8 + 3H2O + CO2 → Al2(Si2O5)(OH)4 + 4SiO2 + 2Na+ + 2HCO3
2KAlSi3O8 + 3H2O + CO2 → Al2(Si2O5)(OH)4 + 4SiO2 + 2K+ + 2HCO3
Ca2+(Mg2+) + 2NaX(solids) → 2Na+ + CaX2(MgX2)(solids)
Class 2 geothermal water: The relatively high concentrations of HCO3, Ca2+, and Mg2+ were a result of carbonate minerals dissolving, and sulfate mineral dissolution makes a negligible impact (Figure 7b,c) [34]. On the other hand, the geothermal water samples were observed to be in regions close to CAI–I = 0 and CAI–II = 0, suggesting a low degree of cation exchange reactions.
Class 3 geothermal water: The HCO3/(Ca2+ + Mg2+) ratio was less than 0.5 and the (Ca2+ + Mg2+)/(HCO3 + SO42−) ratio was above 1 (Figure 7b,c), which suggested that the source of Ca2+ may also include sulfate minerals in addition to carbonates. Field investigation revealed that ABS05 hot spring outcrop was found alongside stone coals, indicating the presence of sulfide oxidation. This process results in the production of a significant amount of SO42−, which is further supported by the higher concentration of SO42− compared to Ca2+ in Class 3 geothermal water (Figure 7d).

4.2. Geothermal Reservoir Temperature

4.2.1. Water–Rock Equilibrium State

The Na–K–Mg ternary diagram illustrated that the geothermal water samples (excluding ABW02) were typical of immature water located in the lower–right corner of the triangular diagram [37] (Figure 8a). Furthermore, the Cl, SO42−, and HCO3 triangle diagram can be used to identify the mixing between hot and cold water [37,38]. In Figure 8b, it can be observed that the sample points were mainly distributed in the peripheral water region, indicative of the involvement of cold water or surface water. Hence, we can infer that geothermal water had not yet achieved a water–rock equilibrium state, and it was more suitable to utilize a SiO2 geothermometer to calculate the reservoir temperature [7,14].

4.2.2. SiO2 Geothermometer

The SiO2 geothermometer provides a reliable indication of the temperature based on the principle that the solubility of SiO2 in the subsurface is influenced by temperature and pressure [8,33]. Various silica minerals were found naturally, including quartz, chalcedony, α–cristobalite, β–cristobalite, and amorphous silica. The log(K2/Mg) vs. SiO2 diagram and saturation index (SI) were employed to determine an appropriate silica geothermometer [39]. Figure 8c illustrated the distribution of geothermal samples in the study area were found to be present in quartz, chalcedony, and α–cristobalite. However, we noted that only the quartz was saturated (Figure 8d). Consequently, the quartz geothermometer was selected to calculate the reservoir temperature using Equations (1) and (2).
Because geothermal wells are considered semi–closed systems with minimal or no steam loss, the hot springs were assessed using the quartz steam loss equation, whereas the reservoir temperature for the geothermal wells was computed using the quartz no steam loss equation, yielding the results in Table 2. Class 1 geothermal water exhibited the highest geothermal reservoir temperature, ranging from 74.9–117.7 °C. Class 2 geothermal water had the lowest thermal reservoir temperature, ranging from 38.7–86.2 °C. Class 3 geothermal water had a thermal reservoir temperature of 85.9 °C.

4.2.3. Silicon Enthalpy Mixing Model

Representative samples of each type of geothermal water were selected to estimate the initial temperature and mixing ratio of cold water using silicon enthalpy equations (Equations (3) and (4)) [25]. The temperature and SiO2 content of the cold water were obtained from ABD01, which recorded a temperature of 10.8 °C and a SiO2 content of 8.5 mg/L. By substituting the enthalpy values of the geothermal water at different temperatures and the SiO2 content of the spring water into the silicon enthalpy equations, the initial temperature was assumed to be between 50 °C and 300 °C. Different values of X1 (Equation (3)) and X2 (Equation (4)) were determined at various temperatures, and the resulting dot–line diagrams were used to establish the relationship between temperature and the cold water mixing ratio of the geothermal water (Figure 9a–c) [38].
Moreover, a silicon–enthalpy graphical method has been conducted to estimate the reservoir temperature of mixing water [38,40]. It determined the enthalpy and SiO2 content of cold water as point a using the ABD01 sample as the reference, and the enthalpy and SiO2 content of geothermal water samples were point b. By connecting points a and b and extending the line to intersect with the quartz solubilization curve at point c, the transverse coordinate of point c represented the initial temperature (Figure 9d–f). By combining the silicon–enthalpy equations and the silicon–enthalpy graphical method, the initial geothermal water temperatures range of ABW02, ABW01, and ABW01 were 137.5–137.6 °C, 93.1–93.5 °C, and 182.3–186.3 °C, respectively, while the mixing ratios of cold water were estimated to be 57.8%, 67.5%, and 87.7%, respectively.

4.2.4. Multi–Mineral Equilibrium Simulation

The equilibrium between multi–minerals and fluids plays a crucial role in studying hydrothermal–chemical processes and can also help in estimating thermal reservoir temperatures [34,41]. We used the SOLVEQ–XPT to calculate variations of the saturation indices of different minerals at a temperature step of 20 °C. The selection of minerals was based on thermal reservoir lithology [11,42]. In this study, we assumed that the concentration of Al is 0.05 mg/L [41]. Additionally, we took into account the degassing effect of CO2 during the calculation process [11,34]. When adding equal amounts of HCO3 and H+ of 0.01 mol/L, 0.05 mol/L and 0.1 mol/L, respectively, most of the selected minerals reached convergence. For CO2 corrections, the convergence of the ABW02 geothermal water interval (Figure 9g) was observed between 120 and 140 °C. This result aligned with the temperature calculated using the silica enthalpy mixing model. Similarly, the convergence intervals for ABW01 geothermal water (Figure 9h) and ABS05 geothermal water (Figure 9i) were found to be between 60 and 80 °C and between 80 and 100 °C, respectively, which were consistent with the results obtained from the SiO2 geothermometer.
Geographically (Figure 10), the geothermal waters in Li and Maerkang counties had higher outcrop temperatures (>40 °C), with the maximum recorded at the Bibenggou geothermal well (65 °C) (Figure 10a). In addition, most southern thermal reservoir temperatures are above 90 °C, unlike those in the north (Figure 10b). Magmatic intrusions are present near the Xianshuihe fault zone in the south of Aba area, which may explain this thermal reservoir temperature differential [16,43].

4.3. Recharge Sources Traced by δ2H and δ18O

Changes in δ2H and δ18O isotopes can provide insights into the cycling process in various groundwater environments [44]. Craig observed a linear correlation between δ2H and δ18O isotopes and provided the global meteoric water line equation: δ2H = 8δ18O + 10 [45]. The global meteoric water line and the meteoric water line of the southwestern part of China (δ2H = 8.41δ18O + 16.72) [46] were chosen to determine the source of geothermal water in this study. Figure 11 showed that geothermal samples were near meteoric water lines and far from mantle, magma, and metamorphic water sources. This indicated a tight link between Aba’s geothermal fluids and meteoric water, which is the main recharge source.
Because of the elevation effect of δ2H and δ18O isotopes in groundwater derived from meteoric water, they can be used to estimate the recharge elevation [47]. In geothermal circulation systems, water–rock interaction causes changes in δ18O values in geothermal water, while δ2H values are minimally affected by water–rock interaction and isotope exchange. Thus, the following equation was used to calculate the recharge elevation E [45]:
E = e + (δ2H − δ2H0)/ΔG
where the e was the reference point elevation (m) and δ2H was the δ2H value of geothermal water samples. δ2H0 was the δ2H value of the reference point. The δ2H0 value (−94.7‰) and e value (3544 m) were determined in the Heishui county of the study area. The ΔG was the δ2H elevation gradient of meteoric water in SW China (−2.6‰/100 m) [48]. Accordingly, the recharge elevations of three types of geothermal waters were calculated as 3209–4982 m, 3621–3824 m, and 3236 m (Table 2).

4.4. Genesis Model of Geothermal Water

Aba geothermal water genesis models can be divided into three different types. The intrusive zone contact type (Class 1 geothermal water) was dominated by magma residual heat and found in Li, Maerkang, and Rantang counties in southern Aba. The second type, carbonate type (Class 2 geothermal water), was controlled by deep and large carbonate fractures. Heishui and Ruoergai counties in northern Aba were its main locations. Third, the fracture type with high SO42− content (Class 3 geothermal water) was influenced by the Maowen deep fault in eastern Aba.

4.4.1. Contact–Type of Intrusion Zone

This geothermal water was stored in sandstone–granite contact. The reservoir was heated because of the geothermal gradient, active deep faults, and granite radioactivity. Regional folding and fault tectonics affect geothermal water distribution. Bibenggou geothermal well, Guergou hot spring, and Kejiu hot spring are examples. This study investigated the genesis model of this type of geothermal water from the Bibenggou well.
The 2400 m Bibenggou geothermal well was intentionally drilled. Sandstone dominated the strata, providing thermal reservoir cover and water insulation. The main recharge source was atmospheric precipitation, estimated at 4982 m (Table 2), indicating that snow water (about 4000 m snow line altitude) recharged underground geothermal water (Figure 12). Geothermal water originated when snow and meteoric water infiltrated fractures in granite–sandstone layers, heating to 99.5–137.6 °C due to geothermal gradient and residual heat from deep magma intrusive rocks. Geothermal water comprises abundant Na+, K+, and HCO3 due to the reaction between thermal water and surrounding sodium/potassium silicate minerals during circulation. By mixing geothermal water with deep increasing heat flow, CO2 and trace elements like B and F were enhanced. After that, geothermal water rose along the fissures in the core of the inverted anticline, causing cation exchange processes in the shallow section and increasing Na+ concentration. Ultimately, boreholes revealed HCO3–Na type geothermal water.

4.4.2. Carbonate–Type in Carbonate ROCK Areas

This geothermal water reservoir was mostly carbonate rocks. The heat came from geothermal gradients. It had a low thermal reservoir temperature and little water–rock interaction. This group includes the Chuanzhusi geothermal well and Erdaohai hot spring, among others. This study investigated the genesis model of this type of geothermal water from the Chuanzhusi well.
The 122.8 m Chuanzhusi geothermal well was a self–spraying borehole. Permian and Carboniferous limestone comprise the reservoir. About 100 m of Quaternary sediments cover a 1680 m thick relative water–insulating layer above the reservoir layer. The covering protects the geothermal water reservoir from Min River water infiltration and provides thermal insulation. The Chuanzhusi geothermal wells were situated in a high geothermal area with a temperature gradient of 30–40 °C/km. At around 4200 m east of the Min River, meteoric water infiltrated fault fractures (Figure 13). These fissures, solution cracks, and paleocarbonate channels led groundwater to depths of 1700–2000 m. It generated geothermal water when heated by the geothermal gradient, reaching temperatures between 61.6 °C to 93.5 °C. Over time, this water dissolved nearby rocks like calcite and dolomite, releasing Ca2+, Mg2+, and HCO3. Trace elements like Sr and B were relatively abundant in the geothermal water. The intersection of the N–S–trending Min River fault zone and the W–trending minor cracks was where geothermal water was concentrated. The final drill holes found HCO3–Ca–Mg geothermal water.

4.4.3. Fracture–Type Controlled by Deep and Large Faults

This geothermal water concentrated in deep fault fissures. High SO42− concentrations in these reservoirs came from deep H2S and coal seams undergoing sulfide dissolution. Deep large fractures increased reservoir water storage and thermal conductivity. The geothermal display featured Jiyugou hot spring.
The geology of Jiyugou hot spring was complex due to its location in phyllite, argillaceous limestone, and fine sandstone strata with stone coal. Jiyugou hot spring had 106 to 142.2 Bq/L of radioactive radon gas, indicating a second heat source from radioactive decay. Mechanical frictional heat from Longmenshan active fractures and earthquakes also heats Jiyugou hot spring [49]. As shown in Figure 14, meteoric water infiltrated granite–dolomite fractures at 3200 m and was heated by geothermal gradient heating, crustal heat flow from radioactive element decay in the upper crust, and mechanical frictional heat from active faults and earthquakes. Geothermal water forms when its temperature rose to 85.9–100 °C. Geothermal water leached Ca2+ and Mg2+ from carbonate rocks during migration. The geothermal water had significant SO42− concentrations due to paste salt, lenticular gypsum, and stone coal strata. Geothermal water followed fracture zones and fissures until it reached the Maowen fault zone and Jiyugou fracture, where it was discharged as SO4–Ca–Mg geothermal water at topographically and tectonically helpful areas [49].

4.5. Prediction of Scaling Trends

Three types of scaling usually occur—carbonate scaling like calcium carbonate [50,51]; sulphate and heavy metal sulphide scaling, like calcium and iron sulphide [52,53]; and silicon and other siliceous components, like amorphous silica—depending on reservoir lithology, temperature, brine production, and utilization processes [54]. Silicon and calcium scaling are most common. High–temperature geothermal systems above 180 °C experience silicon scaling, while medium– and low–temperature systems (<150 °C) commonly have calcium scaling [10,55].

4.5.1. Scaling Trend of Calcium Carbonate

Upon rising, geothermal fluid rich in Ca2+ and HCO3 generates Ca(HCO3)2, which decomposes into CaCO3. Decomposing calcium bicarbonate produces alkaline scaling, which forms bigger particles on the pipe wall by interacting and colliding with other components [56,57,58,59]. The chemical equations for CaCO3 scaling reactions are as follows [10,58,59]:
H2CO3 ↔ CO2(gas) + H2O
HCO3 + H2O ↔ H2CO3 + OH
Ca2+ + 2HCO3 ↔ CaCO3(solid) + CO2(gas) + H2O
Qualitatively evaluating each geothermal water type’s calcium carbonate scaling trend using the Larson Index (LI) and Ryzner Index (RI) is common [8,17,27,28,29]. When Cl ions are high (milligram equivalent percentage > 25%) in geothermal water, the Larson index approach is better for the calcium carbonate scaling trend (Equation (6)). When Cl ions are not high, the Ryzner index method is superior, as shown in Table 1 (Equations (7)–(10)). The pH2 is the measured pH value of geothermal water (Table 2). Kc is usually determined graphically [60], and Ke is a constant with a TDS range of 200–6000 mg/L. Ke is 1.8 for temperatures above 100 °C, 2.6 for temperatures below 50 °C, and 2.6 − (2.6 − 1.8)/(100 − 50) × (t − 50) for temperatures between 50 and 100 °C [17,28,29]. After judging the Larson index, LI > 0.5 indicates no scaling but corrosivity, while LI < 0.5 indicates likely scaling and non–corrosivity [17,27]. Scaling severity is determined using the Ryzner index: RI < 4.0 indicates very severe scaling; 4.0 < RI < 5.0 indicates severe scaling; 5.0 < RI < 6.0 indicates moderate scaling; 6.0 < RI < 7.0 indicates slight scaling; and RI > 7.0 indicates no scaling [17,29].
Results are shown in Table 3. Calcium carbonate scaling trends in ABS01, ABS02, ABS07, and ABW01 were very severe; ABS03, ABS05, and ABS11 were severe; and ABS04 (average RI = 5.75) was moderate. ABS09 showed slight scaling (RI = 6.44). Finally, ABS06, ABS08, ABS10, ABS12, and ABW02 will not carbonate scale (RI > 7). The thermal reservoirs of ABS01–ABS05, ABS11, and ABW01 contained limestones and/or dolomites, which leached Ca2+ and HCO3, causing Ca2+ and HCO3 supersaturation and precipitation in geothermal water. In ABS07, CO2 degassing produced excessive HCO3 that reacted with Ca2+ to precipitate CaCO3.

4.5.2. Scaling Trend of Calcium Sulfate

Gypsum scaling has a major effect on geothermal fluids, followed by azurite and barite. Gypsum (CaSO4–2H2O) precipitates primarily if the geothermal fluid’s temperature is below 100 °C, according to the precipitation equation [17,61]:
Ca2+ + 2SO42− + 2H2O → CaSO4·2H2O
Gypsum scaling can be qualitatively determined from relative saturation (R.Sgypsum). logKgypsum is the solubility product of gypsum, which can be calculated using TDS and temperature in Equation (11) in Table 1 [17]. When R.Sgypsum > 1, gypsum is saturated and scaling may occur. The estimated results were in Table 3. R.Sgypsum > 1 for ABS05, showing gypsum scaling compatible with high SO42− content from sulfide dissolution and sulfide oxidation in ABS05 geothermal water. Other geothermal waters had R.Sgypsum below 1, indicating no gypsum scaling.

4.5.3. Scaling Trend of Amorphous Silica

Using thermodynamics and kinetics, dissolved silica precipitates amorphously. Chemical sorption and polymerization precipitate silica. Chemical polymerization condenses silica monomers into nanoscale polymer particles, while chemisorption deposits them directly on the surface. Silicon scaling chemical reaction equations are as follows [10,55]:
SiO2 + 2H2O ↔ Si(OH)4
Si(OH)4 + OH ↔ (OH)3Si + H2O
Si(OH)3 + Si(OH)4 → (OH)3Si–O–Si(OH)3 + OH
2n(OH)3Si–O–Si(OH)3 → Cyclic/Colloidal silica → Polymeric silica (scale)
This study used the relative saturation of amorphous silica, R.SSiO2, as in Table 1 (Equation (12)), where Tk is geothermal water’s absolute temperature, to determine silica scaling. The scaling of amorphous silica is distinguished by R.SSiO2 > 1. The estimation results are shown in Table 3. Amorphous silica scaling was not present in Aba’s geothermal water because none of the samples have R.SSiO2 values greater than 1.
Figure 15 shows the study area’s geothermal water scaling trend and geographic distribution. Scaling was more common in geothermal water near Aba border. First, all Class 2 geothermal water had calcium carbonate scaling, which ranged from severe to slight. Second, Class 1 geothermal water will be affected by extremely severe calcium carbonate scaling in ABS07, moderate in ABS09, and severe in ABS11. In contrast, ABS06, ABS08, ABS11, ABS12, and ABW02 do not scale. Finally, ABS05 will endure significant calcium carbonate and calcium sulfate scaling. Descaling methods like controlling CO2 partial pressure, pH, or chemical additives are chosen based on scaling trends to choose effective preventive measures when developing and using regional geothermal water [10].

5. Conclusions

To study hydrogeochemical processes, genesis mechanisms, and scaling trends in geothermal systems in northeastern Sichuan, we divided Aba geothermal water into three types. The conclusions achieved from hydrogeochemical and isotopic studies were listed below.
(1)
Aba’s geothermal water was recharged by atmospheric precipitation. Three types of geothermal waters recharge at 3209–4982 m, 3621–3824 m, 3236 m, respectively. Class 1 geothermal water was found across Aba area’s southern region. Hydrochemistry types included HCO3–Na and HCO3–SO4–Na. High concentrations of HCO3 and Na+ were due to water, CO2, and sodium silicate mineral reactions and positive cation exchange. Class 2 geothermal water in northern Aba contained both HCO3–Ca and HCO3–Ca–Mg types, which generated significant amounts of HCO3, Ca2+, and Mg2+ through carbonate mineral dissolution. Class 3 geothermal water in eastern Aba had a high SO42− concentration due to oxidation of sulfides and gypsum mineral dissolution. It was SO4–Ca–Mg type water.
(2)
The geothermal reservoir temperature ranges for Class 1 geothermal water 74.9–137.6 °C, whereas Class 2 had lower temperature range at 38.7–93.5 °C. Geothermal water of Class 3 (ABS05) had a reservoir temperature of 85.9–100 °C and the initial temperature of up to 186.3 °C.
(3)
The Aba geothermal water genesis model comprised three primary types: (1) the contact type, which was magma residual heat in Li, Maerkang, and Rantang counties’ intrusive zones; (2) carbonate–type geothermal water controlled by deep and large fractures, which took geothermal gradient as the heat source and carbonates as the thermal reservoir; and (3) the fracture type with high SO42− concentration, which was controlled by a deep, large fault and was generally found in the upper plate of the Maowen fault.
(4)
ABS07, ABS09, and AB12 of Class 1 geothermal water will have slight to very serious calcium carbonate scaling, while ABS06, ABS08, ABS11, ABS12, and ABW02 will not. Class 2 geothermal water will have serious to very serious calcium carbonate scaling. Geothermal water in Class 3 will have severe calcium sulfate and calcium carbonate scaling.

Author Contributions

Writing—original draft preparation, investigation, methodology, G.L.; writing—review and editing, software, data curation, D.W., X.Y., M.S., Z.Y. and X.K.; review and editing, supervision, project administration, funding acquisition, Y.Z.; review and editing, resources, data curation, funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by National Natural Science Foundation of China grant number (42072313, 42102334), Sichuan Provincial Department of Science and Technology Projects grant number (2022NSFSC0413, 2023YFS0356), Sichuan Provincial Department of Natural Resources Research Project Funding grant number (KJ–2023–36), Open Fund of the Engineering Research Center of Geothermal Resources Development Technology and Equipment, Ministry of Education, Jilin University (22012).

Data Availability Statement

All the research data have been provided in the paper.

Acknowledgments

We would like to thank anonymous reviewers and editors for their constructive comments on this manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. (a) China map; (b) Sichuan Province map; (c) regional geological map in the study area (F1: Jiaxuxiang–a secondary fault of the Seda fault zone; F2: Maerkang; F3: Miyaluo; F4: Maowen; F5: Aba; F6: Minjiang–Huya; F7: Maqu–Heye; F8: Maqin–Lueyang).
Figure 1. (a) China map; (b) Sichuan Province map; (c) regional geological map in the study area (F1: Jiaxuxiang–a secondary fault of the Seda fault zone; F2: Maerkang; F3: Miyaluo; F4: Maowen; F5: Aba; F6: Minjiang–Huya; F7: Maqu–Heye; F8: Maqin–Lueyang).
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Figure 2. Photos of part of the geothermal water exposed locations: (a) ABW02, (b) ABS02, (c) ABS03, (d) ABS04, (e) ABS05, (f) ABS01, (g,h) ABS06, and (i) ABS07.
Figure 2. Photos of part of the geothermal water exposed locations: (a) ABW02, (b) ABS02, (c) ABS03, (d) ABS04, (e) ABS05, (f) ABS01, (g,h) ABS06, and (i) ABS07.
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Figure 3. Piper trilinear diagram of geothermal water.
Figure 3. Piper trilinear diagram of geothermal water.
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Figure 4. Schoeller diagram of major element components and trace element components of water samples.
Figure 4. Schoeller diagram of major element components and trace element components of water samples.
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Figure 5. Pearson coefficient test correlation of hydrochemical parameters of geothermal waters (all parameter values for all 14 samples).
Figure 5. Pearson coefficient test correlation of hydrochemical parameters of geothermal waters (all parameter values for all 14 samples).
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Figure 6. Relationship between Cl and some hydrochemical components: (a) Na; (b) K; (c) B; (d) TDS.
Figure 6. Relationship between Cl and some hydrochemical components: (a) Na; (b) K; (c) B; (d) TDS.
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Figure 7. The relationship between the major ions of geothermal water: (a) Cl vs. Na+ + K+; (b) HCO3 + SO42− vs. Ca2+ + Mg2+; (c) HCO3 vs. Ca2+ + Mg2+; (d) SO42− vs. Ca2+; (e) HCO3 vs. Na+ + K+; (f) (Ca2+ + Mg2+) − (HCO3 + SO42−) vs. Na+ + K+ − Cl; (g) CAI–II vs. CAI–I (CAI–I = (Cl − Na+ − K+)/Cl; CAI–II = (Cl − Na+ − K+)/(HCO3 + SO42− + CO32− + NO3)); (h) log(K+/H+) vs. log(SiO2); (i) log(Na+/H+) vs. log(SiO2).
Figure 7. The relationship between the major ions of geothermal water: (a) Cl vs. Na+ + K+; (b) HCO3 + SO42− vs. Ca2+ + Mg2+; (c) HCO3 vs. Ca2+ + Mg2+; (d) SO42− vs. Ca2+; (e) HCO3 vs. Na+ + K+; (f) (Ca2+ + Mg2+) − (HCO3 + SO42−) vs. Na+ + K+ − Cl; (g) CAI–II vs. CAI–I (CAI–I = (Cl − Na+ − K+)/Cl; CAI–II = (Cl − Na+ − K+)/(HCO3 + SO42− + CO32− + NO3)); (h) log(K+/H+) vs. log(SiO2); (i) log(Na+/H+) vs. log(SiO2).
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Figure 8. Identification of water–rock equilibrium and dissolution relationship of SiO2 minerals: (a) Na–K–Mg diagram; (b) Cl−SO4−HCO3 triangle diagram; (c) SiO2 vs. log(K2/Mg); (d) mineral saturation index diagram.
Figure 8. Identification of water–rock equilibrium and dissolution relationship of SiO2 minerals: (a) Na–K–Mg diagram; (b) Cl−SO4−HCO3 triangle diagram; (c) SiO2 vs. log(K2/Mg); (d) mineral saturation index diagram.
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Figure 9. (ac) Diagram of silicon–enthalpy equations (the left side of the is the initial reservoir temperature, the right side is the mixing ratio of cold water, and X1 and X2 are the proportion of the cold water mixing at different temperatures), (df) silicon–enthalpy graphical diagram and (gi) the log(Q/K)–temperature diagrams of the main aluminosilicate minerals of geothermal water.
Figure 9. (ac) Diagram of silicon–enthalpy equations (the left side of the is the initial reservoir temperature, the right side is the mixing ratio of cold water, and X1 and X2 are the proportion of the cold water mixing at different temperatures), (df) silicon–enthalpy graphical diagram and (gi) the log(Q/K)–temperature diagrams of the main aluminosilicate minerals of geothermal water.
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Figure 10. Spatial distribution of geothermal water in the Aba area: (a) outcrop temperature; (b) thermal reservoir temperature.
Figure 10. Spatial distribution of geothermal water in the Aba area: (a) outcrop temperature; (b) thermal reservoir temperature.
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Figure 11. δ2H–δ18O for the geothermal waters in the Aba area (GMWL: global meteoric water line, CMWL: Chinese southwestern meteoric water line).
Figure 11. δ2H–δ18O for the geothermal waters in the Aba area (GMWL: global meteoric water line, CMWL: Chinese southwestern meteoric water line).
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Figure 12. Genesis model of Bipenggou geothermal well.
Figure 12. Genesis model of Bipenggou geothermal well.
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Figure 13. Genesis model of Chuanzhusi geothermal well.
Figure 13. Genesis model of Chuanzhusi geothermal well.
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Figure 14. Genesis model of Jiyugou hot spring.
Figure 14. Genesis model of Jiyugou hot spring.
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Figure 15. Spatial characteristics of scaling of geothermal water in Aba area.
Figure 15. Spatial characteristics of scaling of geothermal water in Aba area.
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Table 1. Quantitative calculation equations for scaling trends.
Table 1. Quantitative calculation equations for scaling trends.
MethodEquationNo.Reference
Larson Index (LI)LI = ([Cl] + [SO42−])/[ALK](6)[17,27]
Ryzner Index (RI)RI = 2pH1 − pH2(7)[17,28,29]
pH1 = log[Ca2+] − log[ALK] + Kc(8)
pH2 = log[Ca2+] − log[ALK] + Ke(9)
T(°F) = 32 + 9/5 × T(10)
Relative saturation of gypsum (R.Sgypsum)R.Sgypsum = 10^(logCa2+ + logSO42− − logKgypsum)(11)[17]
Relative saturation of silica (R.SSiO2)R.SSiO2 = SiO2/(2.446 × 10,000 × e^(−1553/Tk))(12)
Table 2. Statistics of basic hydrochemical parameters, main ions, and isotopes of geothermal springs and wells in the Aba area.
Table 2. Statistics of basic hydrochemical parameters, main ions, and isotopes of geothermal springs and wells in the Aba area.
IDNameClassAltitude (m)T (°C)pHTDS (mg/L)δ2Hδ18ORecharge Elevation (m)No Steam Loss (°C)Maximum Steam Loss (°C)Reservoir Lithology
ABS06 aGuergou1258348.09.168−118.5−16.6445970.174.9Granite
ABS07 aKejiu1308326.07.02190−120.3−16.1452971.676.1Sandstone
ABS08 bXiadagai1236935.09.1229−86.0−12.13209111.3110.7Calcisilicarenite
ABS09 bBaoyan1264048.07.4511119.4117.7Slate/Phyllite
ABS10 bJiashikou1292544.09.3384117.0115.6Gravel–bearing sandstone
ABS11 bGuanyinmiao1261232.07.5294996.698.1Limestone/Dolomite
ABS12 dYouri1392023.09.5227.4−118.6−16.4446394.996.6Sandstone
ABW02 aBipenggou1306765.08.1258−132.1−18.1498299.5100.6Granite
ABS01 aErdaohai2343018.36.51280−99.4−14.0372529.838.7Limestone
ABS02 aYuanshanzi2308110.56.6245055.662.0Limestone/Dolomite
ABS03 aJiangzha2325338.46.6812−102.5−15.3384483.086.2Siliceous dolomite
ABS04 aHeta2336030.57.3305−96.7−14.3362156.462.6Conglomerate mixed with metamorphic limestone
ABW01 cChuanzhusi2301038.07.483461.667.4limestone
ABS05 aJiyugou3170331.97.22150−86.7−13.6323682.685.9Metamorphic dolomite
IDCa2+Mg2+Na+K+ClSO42−HCO3FLi+Sr2+B3+SiO2Hydrochemical type
ABS060.60.119.71.53.218.224.51.50.030.010.123.8HCO3–SO4–Na
ABS07193.045.2587.069.616.140.82339.02.56.71.813.824.7HCO3–Na
ABS081.00.455.21.06.023.796.18.40.10.010.160.9HCO3–Na
ABS0918.03.794.25.31.612.3297.06.30.80.10.171.7HCO3–Na
ABS100.50.497.91.414.714.0243.03.30.1136.00.168.3HCO3–Na
ABS1143.541.7615.062.449.99.02075.02.60.52.125.144.7HCO3–Na
ABS122.00.646.01.03.98.290.05.40.10.030.443.0HCO3–Na
ABW020.50.194.22.721.131.1176.59.30.10.010.247.6HCO3–Na
ABS01436.023.36.91.31.14.21514.00.40.030.40.37.4HCO3–Ca
ABS02707.0154.020.931.614.015.82863.01.70.30.76.116.2HCO3–Ca–Mg
ABS03163.044.639.06.74.0210.0606.81.00.20.40.832.7HCO3–SO4–Ca–Mg
ABS0466.012.418.91.11.844.8285.00.50.030.30.116.5HCO3–Ca
ABW01146.368.173.12.412.884.0854.30.60.014.62.519.1HCO3–Ca–Mg
ABS05343.0124.0110.015.919.71360.0301.63.00.24.80.732.4SO4–Ca–Mg
ABD0159.910.417.11.51.855.3221.90.10.10.30.18.5HCO3–Ca
Note(s): The units of ions and SiO2 in the table are mg/L; a: taken in 2020; b: taken in 2019; c: taken in 2009; d: cite from [7]; ABD01: surface water; “–” indicates that the data was not obtained.
Table 3. Calculation results of scaling trends of calcium carbonate, sulfate, and silicate in three types of geothermal waters (RI1 was calculated using Equations (7) and (8); RI2 was calculated using Equations (7) and (9)).
Table 3. Calculation results of scaling trends of calcium carbonate, sulfate, and silicate in three types of geothermal waters (RI1 was calculated using Equations (7) and (8); RI2 was calculated using Equations (7) and (9)).
IDClassCl ion Milligram
Equivalent Ratio
RI1RI2RI (Average)Scaling Trend of
Carbonate Minerals
R.SgypsumR.SSiO2
ABS06110.4%9.210.59.9No scaling0.00010.1
ABS0711.1%3.13.73.4Very severe0.01940.2
ABS0817.6%8.08.98.5No scaling0.00020.4
ABS0910.9%5.87.16.4Slight0.00140.4
ABS1018.8%7.38.57.9No scaling0.00010.4
ABS1114.0%3.84.64.2Severe0.00080.3
ABS1216.3%7.58.07.7No scaling0.00010.3
ABW02114.4%8.09.58.8No scaling0.00010.2
ABS0120.1%3.53.83.7Very severe0.00390.1
ABS0220.8%2.82.82.8Very severe0.04540.2
ABS0320.8%4.45.44.9Severe0.13600.2
ABS0420.9%5.46.15.8Moderate0.01860.1
ABW0122.2%3.44.43.9Very severe0.04980.1
ABS0531.6%3.94.74.3Severe1.14240.2
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Lv, G.; Zhang, X.; Wei, D.; Yu, Z.; Yuan, X.; Sun, M.; Kong, X.; Zhang, Y. Water–Rock Interactions, Genesis Mechanism, and Mineral Scaling of Geothermal Waters in Northwestern Sichuan, SW China. Water 2023, 15, 3730. https://doi.org/10.3390/w15213730

AMA Style

Lv G, Zhang X, Wei D, Yu Z, Yuan X, Sun M, Kong X, Zhang Y. Water–Rock Interactions, Genesis Mechanism, and Mineral Scaling of Geothermal Waters in Northwestern Sichuan, SW China. Water. 2023; 15(21):3730. https://doi.org/10.3390/w15213730

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Lv, Guosen, Xu Zhang, Denghui Wei, Zhongyou Yu, Xingcheng Yuan, Minglu Sun, Xiangxinyu Kong, and Yunhui Zhang. 2023. "Water–Rock Interactions, Genesis Mechanism, and Mineral Scaling of Geothermal Waters in Northwestern Sichuan, SW China" Water 15, no. 21: 3730. https://doi.org/10.3390/w15213730

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