Hydrogeochemical characteristics and circulation model of deep geothermal resources in Tianjin
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摘要: 文章通过水化学和同位素分析，研究天津市深部热储地热流体水化学特征、水岩相互作用及其形成的水文地球化学过程，以揭示深部地热过程和循环机理，定量评价研究区热储温度、冷水混合比例以及地热流体最大循环深度等，建立天津市深部地热流体循环概念模型。结果表明：（1）天津市地热流体主要来自北部蓟县山区大气降水入渗补给，补给高程443.34~722.7 m；（2）大气降水经由入渗作用及周边深大断裂带，进入南部平原区封闭、半封闭的热储层，在径流过程中与围岩发生充分的溶滤、吸附、碳酸盐再沉淀、阳离子交换、脱碳酸等多重作用，同时地热流体发生冷水混入现象，地热流体初始温度为94.54~160.90 ℃，最大循环深度达
2 383.29 ~4 279.29 m，冷水混合比例介于0.01~0.77之间，混合后热储温度67.06~121.38 ℃，热循环深度为1 828.27 ~3 150.24 m，最终形成了现今高钠离子、高氯离子、高溶解性总固体（TDS）的地热资源特征。Abstract:Geothermal resources, as a pivotal renewable and environmentally benign energy source for advancing green development and establishing a clean energy system, hold immense potential for exploitation in Tianjin. Tianjin is situated in the northern region of the North China Plain, and its geothermal resources are predominantly distributed in the southern plain area, south of the Ninghe–Baodi Fault. These resources encompass porous thermal reservoirs within the Neogene Minghuazhen Formation and the Guantao Formation, as well as bedrock fracture-type thermal reservoirs in the Ordovician, Cambrian, and Mesoproterozoic Wumishan Formation (Jixian System). By integrating hydrochemical and isotope geochemical signatures, this study aims to quantitatively evaluate the mixing proportions of deep geothermal fluids and to systematically elucidate the circulation patterns of deep geothermal reservoirs, thereby providing a theoretical basis for the sustainable development of Tianjin’s geothermal resources. Sampling and analytical testing of geothermal fluids indicated a pH range of 7.08 to 8.43, suggesting a weakly alkaline nature. The TDS ranged from 762.1 to 6,040.4 mg·L−1, averaging at1,768.97 mg·L−1. Along the flow path, the anionic composition of the geothermal fluids exhibited significant shifts, transitioning from ${\rm{HCO}}_3^{-}$ dominance to Cl− and ${\rm{SO}}_4^{2-}$dominance. This transition was accompanied by an increase in TDS. Both porous geothermal reservoirs and bedrock fracture-type geothermal reservoirs displayed distinct spatial zonation in their hydrochemical characteristics. An in-depth analysis using Gibbs plots and ion ratio coefficients demonstrated that water-rock interactions are the key factors influencing the chemical composition of geothermal fluids. Specifically, Cl− and Na+ primarily originate from the dissolution of salt rocks. In contrast, Ca2+ and Mg2+ ions are mainly affected by the dissolution of carbonate minerals. Furthermore, cation exchange processes resulted in an increase in Na+ concentrations and a corresponding decrease in Ca2+ and Mg2+concentrations. Gypsum dissolution also served as a significant source of ${\rm{SO}}_4^{2-}$ in geothermal fluids. The dissolution of gysum induced a common ion effect that promoted the precipitation of CaCO3, further reducing the concentrations of Ca2+ and ${\rm{HCO}}_3^{-}$. Isotopic analysis of hydrogen and oxygen revealed that atmospheric precipitation is the primary source of recharge for geothermal fluids. However, the isotopic drift observed in most geothermal fluids indicated that they did not originate directly from local precipitation. Instead, these fluids underwent deep circulation, with lateral recharge serving as the main mode of replenishment. During circulation, these fluids exchanged oxygen isotopes with the surrounding rocks.Plotting the geothermal fluids on the Na-K-Mg ternary diagram showed that all samples fell within the partially equilibrated and immature fields, indicating that either (i) the fluid–rock system has not reached cationic equilibrium, or (ii) the ascending deep fluids have been diluted by shallow cold water. Consequently, cationic geothermometers are not recommended for estimating reservoir temperatures. Calculations by PHREEQC software showed quartz and chalcedony to be in supersaturation or near saturation, suggesting that SiO2 geothermometry can reliably estimate temperatures. Reservoir temperatures derived from the quartz geothermometer were generally higher than those from the chalcedony geothermometer and exceeded the measured wellhead temperatures. Therefore, we adopted the quartz geothermometer results as representative of the reservoir temperature. The estimated thermal storage temperature range in the study area was between 67.06 °C and 121.38°C. Using the silicon-enthalpy hybrid model, we analyzed deep circulation temperatures and cold water mixing in geothermal fluids. The cold water mixing ratios ranged from 0.01 to 0.77, resulting in estimated deep circulation temperatures of the geothermal fluids between 94.54 °C and 160.90°C. To ascertain the maximum circulation depth of the geothermal fluids, we integrated the reservoir temperatures derived from both the quartz geothermometer and the hybrid model, along with the average geothermal gradient. The quartz geothermometer results indicated that the thermal circulation depth of the middle reservoir ranged approximately from 1,828.27 m to 3,150.24 m. Conversely, the hybrid model calculations revealed a deeper maximum thermal circulation depth for the deep reservoir, ranging from 2,383.28 m to 4,279.28 m. Based on the aforementioned study, we have developed an initial conceptual model for geothermal fluid circulation. This model divides the area along the Ninghe–Baodi Fault, designating the recharge zone mainly in the bedrock-exposed region of Jixian county to the north. Atmospheric precipitation infiltrates through this and adjacent deep faults, entering enclosed and semi-enclosed thermal reservoirs in the southern plain. As the precipitation flows, it is progressively heated by underlying heat sources. Over extended geological periods, the dissolution of calcite and dolomite reaches equilibrium in the groundwater, maintaining a stable HCO3− concentration. Meanwhile, Ca2+ and Mg2+ undergo processes such as cation exchange and adsorption, leading to their gradual reduction. In contrast, highly soluble rock salt results in significant accumulation of Na+ and Cl− during prolonged migration. Consequently, the geothermal fluids exhibit high concentrations of Na+, Cl−, and TDS. Furthermore, the mixing of cold water with the geothermal fluids along their flow path has contributed to the current characteristics of geothermal resources in the study area. This study is of great significance for understanding the genetic mechanisms, occurrence modes, and geochemical evolution patterns of underground thermal water. -
图 1 天津市构造单元区划及采样点分布图
Figure 1. Division of structural units and distribution map of sampling points in Tianjin
图 2 明化镇组（a）、馆陶组（b）和雾迷山组（c）地热流体水化学类型空间分布图
Figure 2. Spatial distribution of hydrochemical types of geothermal fluids in Minghuazhen (a), Guantao (b) and Wumishan formations (c)
图 3 研究区地热流体温度与TDS关系图
Figure 3. Relationship between temperatures and TDS of geothermal fluids in the study area
图 5 明化镇组（a）和雾迷山组（b）典型地热井主要离子组分变化趋势图
注：多年水质数据参考自天津市地热资源开发利用动态监测报告。
Figure 5. Variation trend of major parameters in typical geothermal wells of Minghuazhen Formation (a) and the Wumishan Formation (B)
图 6 研究区不同水体的δD-δ18O关系图
Figure 6. Relationship of δD-δ18O of different water bodies in the study area
图 7 研究区地热流体Gibbs图（左图为阴离子图，右图为阳离子图）
Figure 7. Gibbs diagram of geothermal fluids in the study area (left:anion diagram; right:cation diagram)
图 8 研究区主要离子关系图：（a） Cl−/Na+；（b）（${\rm{HCO}}_3^{-}$+${\rm{SO}}_4^{2-}$）/（Ca2++Mg2+）；（c）${\rm{SO}}_4^{2-}$/Ca2+；（d）${\rm{HCO}}_3^{-}$/Ca2+；（e）${\rm{HCO}}_3^{-}$/${\rm{SO}}_4^{2-}$；（f）（Na+/Ca2+）/（Mg 2+ /Ca2+）
Figure 8. Relationship of major ions in the study area. （a） Cl−/Na+；（b）（${\rm{HCO}}_3^{-}$+${\rm{SO}}_4^{2-}$）/（Ca2++Mg2+）；（c）${\rm{SO}}_4^{2-}$/Ca2+；（d）${\rm{HCO}}_3^{-}$/Ca2+；（e）${\rm{HCO}}_3^{-}$/${\rm{SO}}_4^{2-}$；（f）（Na+/Ca2+）/（Mg 2+ /Ca2+）
图 9 研究区地下水氯碱指数统计图
Figure 9. Statistics of groundwater chlor-alkali index in the study area
图 10 研究区地热流体Na-K-Mg三角图
Figure 10. Na-K-Mg triangle diagram of geothermal fluids in the study area
图 11 研究区地热流体部分矿物饱和指数箱图
Figure 11. Box diagram of the partial mineral saturation index of geothermal fluids in the study area
图 12 研究区各储层典型地热井硅—焓模型
Figure 12. Silicon-enthalpy model of typical geothermal wells in the reserviors of the study area
图 13 硅—焓模型估算的热储循环温度和冷水混入比例统计图
Figure 13. Statistics of reservoir temperatures and cold water mixing ratios estimated by silicon enthalpy model
图 14 研究区地热流体循环概念模型图
Figure 14. Conceptual model of geothermal fluid circulation in the study area
表 1 研究区地热流体主要离子测试结果一览表
Table 1. List of main ions test results of geothermal fluids in the study area
样品 热储层 K+ Na+ Ca2+ Mg2+ Cl− ${\rm{SO}}_4^{2-}$ ${\rm{HCO}}_3^{-}$ SiO2 TDS D 18O mg·L−1 mg·L−1 mg·L−1 mg·L−1 mg·L−1 mg·L−1 mg·L−1 mg·L−1 mg·L−1 ‰ ‰ DB1 地表 30.3 552.0 62.9 68.6 657.0 353.0 408.0 9.7 1930.2 −32.9 −4.4 DB2 地表 31.0 560.0 64.4 69.9 654.0 352.0 408.0 7.5 1937.5 −27.8 −4.0 DS1 第四系 0.7 142.0 8.3 2.4 24.2 8.8 319.0 13.5 359.1 −70.4 −9.0 DS2 第四系 0.8 151.0 7.5 1.5 23.1 12.9 324.0 16.4 375.1 −71.2 −9.3 DS3 第四系 1.0 199.0 6.0 2.5 84.6 27.9 307.0 14.8 496.9 −72.4 −9.6 DR1 Nm 37.7 209.0 18.8 5.9 76.5 56.3 437.0 30.3 642.2 −69.8 −9.3 DR2 Nm 5.16 499.0 14.6 1.9 353.0 248.0 395.0 38.5 1338.9 −72.1 −8.6 DR3 Nm 77.4 416.0 29.2 11.6 385.0 268.0 377.0 68.5 1389.3 −66.7 −8.9 DR4 Nm 77.5 437.0 33.6 12.6 337.0 277.0 489.0 40.2 1429.8 −67.9 −9.0 DR5 Nm 75.8 408.0 33.7 10.8 350.0 303.0 373.0 69.5 1377.1 −67.5 −9.0 DR6 Nm 4.71 369.0 12.4 1.5 263.0 154.0 373.0 41.1 995.6 −68.5 −9.2 DR7 Nm 1.61 240.0 7.9 0.7 142.0 78.8 262.0 32.5 618.7 −71.8 −9.3 DR8 Nm 5.0 476.6 13.7 1.6 250.3 374.3 371.0 37.5 1344.5 / / DR9 Nm 9.1 792.9 55.7 11.0 633.1 798.5 227.0 31.6 2445.4 / / DR10 Nm 28.0 1003.5 294.9 61.3 1043.6 1717.3 165.4 22.0 4253.3 / / DR11 Nm 4.7 715.4 70.7 7.8 351.7 971.0 260.6 28.0 2279.6 / / DR12 Nm 4.0 466 14.2 1.1 329.7 237.4 390.5 31.0 1287.7 / / DR13 Nm 3.1 403.8 11.5 1.1 210.9 241.4 414.9 27.5 1118.8 / / DR14 Ng 1.0 313.0 2.5 0.3 117.0 0.9 549.2 27.4 763.7 −64.0 −8.9 DR15 Ng 1.3 243.6 3.0 0.3 46.1 57.8 457.6 30.6 629.5 −35.1 −6.3 DR16 Ng 11.0 496.3 16.3 2.7 356.3 236.3 509.5 35.2 1408.9 −70.5 −8.6 DR17 Ng 57.6 445.5 28.8 6.2 390.0 240.9 463.8 51.0 1451.9 −72.0 −9.1 DR18 Ng 41.8 454.7 38.0 6.5 390.0 225.3 488.2 44.5 1444.9 / / DR19 Ng 1.4 384.8 4.1 0.5 241.1 0.9 610.2 27.8 980.7 −70.0 −9.4 DR20 Ng 28.1 512.0 28.2 6.3 374.0 252.6 506.5 34.5 1501.0 / / DR21 Ng 4.1 607.9 10.9 0.9 528.2 201.9 482.1 41.5 1648.5 / / DR22 Ng 4.0 610.0 10.7 0.8 531.8 202.6 500.4 39.0 1661.1 / / DR23 Ng 2.4 268.9 3.9 0.3 74.4 82.8 463.8 34.6 705.2 / / DR24 Ng 19.7 498.5 30.9 6.1 372.2 239.7 524.8 30.5 1460.0 −68.0 −9.0 DR25 Ng 3.9 515.6 10.5 0.6 320.8 232.9 518.7 40.5 1402.2 −73.0 −9.2 DR26 Ng 3.8 479.1 9.1 1.0 351.0 220.2 482.1 38.5 1355.8 −72.0 −9.1 DR27 Ng 31.6 465.0 24.9 5.5 356.3 228.2 463.8 39.4 1406.8 / / DR28 Ng 1.5 324.6 4.9 0.3 108.1 124.2 485.1 32.4 844.6 −71.0 −9.4 DR29 Ng 3.6 565.4 12.2 1.0 379.3 272.8 463.8 35.0 1516.2 / / DR30 Ng 3.1 238.4 9.3 3.0 53.2 36.3 506.5 48.5 657.1 / / DR31 Ng 1.9 245.9 3.2 0.4 58.5 14.8 494.3 50.5 634.4 / / DR32 O 77.8 399.9 28.7 8.5 361.6 257.7 396.6 71.5 1404.0 −38.2 −6.7 DR33 O 46.2 810.3 479.4 99.6 828.5 1845.2 247.1 27.0 4259.8 / / DR34 O 42.5 821.5 530.3 92.8 822.8 1933.0 211.7 34.0 4382.8 −66.0 −9.1 DR35 O 51.9 892.2 569.6 114.5 1031.6 2231.4 180.1 0.0 5016.3 / / DR36 O 54.6 451.9 43.0 7.9 382.9 278.0 463.8 48.5 1498.7 −65.0 −12.9 DR37 O 7.2 406.3 14.4 2.3 319.0 89.4 494.3 29.5 1115.3 / / DR38 ∈ 76.0 419.0 33.1 10.4 379.3 268.2 408.8 67.5 1457.9 −72.0 −10.0 DR39 ∈ 61.8 507.8 26.6 9.3 437.1 311.6 370.4 61.0 1600.7 / / DR40 ∈ 56.2 1171.1 470.5 97.7 1397.1 1798.4 205.6 0.0 5124.6 / / DR41 Jxw 111.7 1650.1 367.9 82.8 2217.4 1375.1 195.9 0.0 5942.5 −61.6 −9.6 DR42 Jxw 76.4 424.2 30.3 9.0 375.8 270.2 408.8 68.5 1458.8 −56.4 −8.4 DR43 Jxw 65.4 410.5 35.3 9.1 414.8 286.1 311.2 67.0 1443.8 −71.9 −9.2 DR44 Jxw 73.9 426.4 28.0 10.1 397.0 269.7 369.2 66.5 1456.2 −71.9 −9.3 DR45 Jxw 79.4 397.0 31.9 8.2 358.0 256.6 390.5 71.0 1397.4 −67.2 −9.1 DR46 Jxw 78.9 396.1 41.9 9.0 354.5 258.8 427.1 73.0 1425.8 −60.6 −8.2 DR47 Jxw 69.1 505.9 30.2 11.2 432.8 368.1 360.0 68.0 1665.3 −69.0 −9.4 DR48 Jxw 59.8 594.9 40.4 12.3 522.2 403.5 374.1 51.0 1871.2 −68.0 −9.5 DR49 Jxw 72.0 516.7 30.8 11.3 450.2 355.7 357.0 66.0 1681.2 / / DR50 Jxw 72.2 600.9 39.3 14.5 577.8 355.7 350.9 0.0 1890.4 / / DR51 Jxw 64.3 617.0 43.3 15.9 610.5 392.1 349.6 55.0 1972.9 / / DR52 Jxw 74.2 772.0 90.3 16.8 762.2 607.2 312.4 74.5 2553.4 / / DR53 Jxw 65.8 454.1 31.0 10.9 439.9 262.3 409.4 59.5 1528.2 −65.0 −9.4 DR54 Jxw 61.3 547.7 38.5 11.5 509.8 377.5 379.5 57.0 1793.1 / / DR55 Jxw 65.7 447.8 28.0 11.1 429.3 247.4 422.3 62.5 1503.0 −74.0 −8.7 DR56 Jxw 45.5 508.9 30.3 5.7 428.9 244.9 494.3 63.5 1574.9 −66.0 −8.1 DR57 Jxw 76.7 436.6 24.6 10.9 425.4 281.8 332.6 68.0 1490.3 / / DR58 Jxw 76.8 410.1 28.0 9.1 365.1 263.8 384.4 62.5 1407.6 / / DR59 Jxw 78.5 404.4 28.8 9.1 368.7 271.5 378.3 67.5 1417.7 / / DR60 Jxw 74.5 414.9 28.5 9.0 375.8 266.9 357.0 69.0 1417.1 / / DR61 Jxw 71.1 457.6 33.6 10.6 411.2 288.8 402.7 35.5 1509.8 −68.0 −9.4 DR62 Jxw 69.8 477.2 32.7 12.2 439.6 306.2 399.7 60.5 1598.1 / / 注：“/”表示该指标未测试。 
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表 2 研究区热储温度估算
Table 2. Temperature estimation of heat storage in the study area
热储层 T石英/ ℃ T玉髓/ ℃ 最小值 最大值 平均值 最小值 最大值 平均值 明化镇组 67.06 117.80 87.92 35.13 89.18 57.15 馆陶组 75.71 102.74 88.70 44.17 72.88 57.91 奥陶系 75.11 119.27 91.63 43.55 90.78 61.12 寒武系 111.32 116.35 113.84 82.14 87.60 84.87 雾迷山组 86.49 121.38 112.41 55.54 93.09 83.35
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表 3 焓和SiO2含量与温度关系表
Table 3. Relationship between enthalpy, SiO2 content, and temperature
温度/ ℃ 焓/J·g−1 SiO2/mg·L−1 温度/ ℃ 焓/J·g−1 SiO2/mg·L−1 50 50.0 13.5 200 203.6 265.0 75 75.0 26.0 225 230.9 365.0 100 100.1 48.0 250 259.2 486.0 125 125.1 80.0 275 289.0 614.0 150 151.0 125.0 300 321.0 692.0 175 177.0 185.0
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表 4 硅—焓模型计算地热流体循环温度和冷水混合比例结果统计表
Table 4. Statistics of geothermal fluid circulation temperatures and cold water mixing ratios calculated by silicon enthalpy model
热储层 T循环/ ℃ 冷水混合比例 最小值 最大值 平均值 最小值 最大值 平均值 明化镇组 103.18 154.26 120.49 0.40 0.71 0.54 馆陶组 96.82 136.99 117.34 0.41 0.73 0.54 奥陶系 94.54 139.36 120.06 0.01 0.77 0.37 寒武系 126.57 143.52 135.04 0.31 0.43 0.37 雾迷山组 123.18 160.90 135.85 0.25 0.54 0.37
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表 5 地热流体不同方法计算温度及深度对比表
Table 5. Comparison of temperatures and depths calculated by different methods for geothermal fluids
样品 储层 T1/℃ T2/℃ T3 /℃ H1/m H2/m H3/m 样品 储层 T1/℃ T2/℃ T3/℃ H1/m H2/m H3/m DR3 Nm 79 117.12 154.26 1510 3028.50 4089.57 DR43 Jxw 91 115.98 139.07 2546 2995.82 3655.57 DR8 Nm 69 88.86 106.33 891 2220.87 2720.14 DR44 Jxw 97 115.60 131.58 2707 2985.08 3441.57 DR12 Nm 55 80.76 103.18 1290 1989.69 2630.14 DR45 Jxw 99 118.91 136.95 2328 3079.68 3595.00 DR14 Ng 49 75.71 99.08 1571 1845.21 2513.00 DR46 Jxw 98 120.34 140.68 2373 3120.31 3701.49 DR15 Ng 63 80.23 96.82 1916 1974.29 2448.43 DR47 Jxw 85 116.72 146.20 2442 3017.13 3859.29 DR16 Ng 63 86.12 107.15 1750 2142.83 2743.57 DR48 Jxw 79 102.74 123.18 2500 2617.48 3201.63 DR17 Ng 79 102.74 123.18 1325 2617.48 3201.57 DR49 Jxw 95 115.22 133.01 1623 2974.28 3482.43 DR18* Ng 71 96.45 120.37 2496 2437.94 3121.29 DR51 Jxw 78 106.31 132.69 1851 2719.58 3473.40 DR20 Ng 51 85.27 121.82 1393 2118.31 3162.71 DR52* Jxw 82 121.38 160.90 3801 3150.24 4279.29 DR24 Ng 48 80.09 114.71 1314 1970.42 2959.57 DR53* Jxw 83 110.10 135.41 3658 2827.99 3551.06 DR32 O 99 119.27 138.24 2760 3089.92 3631.86 DR54* Jxw 79 108.02 135.67 3282 2768.55 3558.43 DR33 O 56 75.11 94.54 1388 1828.27 2383.29 DR55 Jxw 91 112.52 131.13 1673 2896.91 3428.66 DR34 O 43 84.64 139.36 1516 2100.57 3663.86 DR56* Jxw 84 113.30 141.15 3102 2919.34 3714.89 DR36 O 100 100.40 101.59 1312 2550.59 2584.71 DR57 Jxw 93 116.72 138.52 2650 3017.13 3639.86 DR37 O 78.71 126.57 1822 1931.14 3298.43 DR58 Jxw 97 112.52 124.31 2538 2896.91 3233.86 DR38 ∈ 50 116.35 143.52 2200 3006.50 3782.71 DR59 Jxw 96 116.35 134.52 2876 3006.50 3525.57 DR39 ∈ 92 111.32 126.57 2010 2862.77 3298.43 DR60 Jxw 97 117.46 135.91 2176 3038.20 3565.29 DR41* Jxw 84 105.96 123.97 2778 2709.62 3224.14 DR62* Jxw 83 110.92 137.30 3249 2851.25 3605.00 注：T1为出水温度；T2为基于石英温标估算的热储温度；T3为基于硅—焓模型估算的热储温度；H1为地热井成井深度；H2为基于SiO2温标计算的地热流体循环深度；H3为基于硅—焓模型计算的地热流体最大循环深度。
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