Tracing Experiments and Flow Characteristic Analyses in Carbonate Geothermal Reservoirs: A Case Study of the Juancheng Geothermal Field, North China

Abstract

Carbonate geothermal reservoirs, characterized by widespread distribution, a high discharge capacity, and favorable reinjection conditions, have become a key target for geothermal resource development. However, the karst geothermal reservoir system in the Juancheng geothermal field exhibits significant heterogeneity, leading to substantial disparities in productivity among multiple geothermal wells and severely restricting efficient regional exploitation. This study systematically investigates the hydraulic characteristics and development potential of the karst geothermal reservoir in the Juancheng geothermal field using sodium fluorescein tracing experiment technology. The results reveal that the reservoir system contains multiple flow channels with distinct permeability differences. The dominant flow pathways, controlled by fault structures, exhibit an apparent velocity of up to 10.98 m/h, significantly higher than other regions in the study area. In contrast, low-permeability zones, influenced by the burial depth of the Ordovician strata, show poor connectivity due to limited karst development, with the lowest apparent velocity of only 1.03 m/h. By integrating pumping test data and tracer response characteristics, the dominant flow direction (northeast) demonstrates a stronger recharge capacity and water abundance, offering a higher development value. Conversely, the southeast low-permeability zone has weaker water production and constrained recharge conditions, resulting in a relatively limited development potential. Additionally, it is recommended that the direction of future geothermal well placement in the Juancheng geothermal field should avoid being parallel to the fault strike to prolong the thermal breakthrough arrival time. In regions with deeper Ordovician strata burial, denser well network deployment is suggested to enhance the reservoir utilization efficiency.

1. Introduction

Karst geothermal reservoirs belong to hydrothermal geothermal resources, characterized by widespread distribution, a large geothermal water discharge capacity, and favorable reinjection conditions. Geothermal water reinjection can maintain the pressure equilibrium in the reservoir to achieve the sustainable development of geothermal systems; however, reinjection operations may induce a temperature decline in production wells, shortening the effective utilization period of the system. Therefore, accurately evaluating the hydraulic connectivity between production and injection wells is a critical prerequisite for the scientific reinjection of geothermal effluent [1]. Karst geothermal reservoirs exhibit strong heterogeneity and anisotropy, complicating their hydraulic processes. Conventional techniques struggle to directly quantify the hydraulic connectivity between wells. Tracing experiments, which monitor the spatiotemporal dynamics of fluid migration, are the most direct and effective method to characterize flow paths, velocity distributions, and inter-well connectivity in karst geothermal systems [2,3].

Kumagai et al. [4] compared the recovery rates and first-detection times of potassium bromide and potassium iodide in the Sumikawa geothermal field, Japan, providing criteria for tracer selection. Kocabas et al. [5] combined thermal injection reflux tests with inter-well tracing experiments to determine flow and heat transfer parameters in reservoirs. Pang et al. [2] conducted sodium fluorescein tracing experiments in the Xiongxian area of the Niutuo Town geothermal field (North China), integrating fracture medium solute transport models to quantify parameters such as the dominant flow path length, seepage velocity, longitudinal dispersivity, and recovery rate, revealing inter-well connectivity in the test area. Yin et al. [3] used sodium 1,5-naphthalenesulfonate as a tracer in the Dongli Lake area of Tianjin, demonstrating poor hydraulic connectivity between production and injection wells and extremely low tracer recovery rates, providing critical data for reservoir heterogeneity studies. Xue et al. [6] employed ammonium thiocyanate as a tracer in the Hancheng area of the southeastern margin of the Ordos Basin, predicting temperature changes in production wells due to long-term reinjection using thermal breakthrough models. Ren et al. [7] systematically summarized tracer test results from 134 tracers in 14 enhanced geothermal systems (EGSs), emphasizing the core role of tracer technology in reservoir identification, tracer selection, and tracing experiment design.

2. Geologic Setting

The Juancheng geothermal field is located within the Heze Uplift tectonic unit of the Heze–Yanzhou Uplift in the Southwest Shandong Uplift area of the West Shandong Block (II) of the North China Craton (I) (Figure 1a,b) [8]. The region exhibits the limited development of fracture systems and lacks major deep faults, with only two sets of small-displacement northeast–southwest trending faults. The Juancheng geothermal field and surrounding areas are covered by Quaternary and Neogene strata. Based on existing drilling data, the stratigraphic sequence from oldest to youngest includes the Ordovician and Carboniferous of the Paleozoic and the Neogene and Quaternary of the Cenozoic.

Kang [9] divided Shandong Province into four geothermal zones from east to west based on geological structural conditions and reservoir characteristics, using the eastern branch of the Yimu Fault (Changyi–Dadian Fault), the western branch of the Yimu Fault (Yantou–Gegou Fault), the Qiguang Fault, and the Lanliao Fault as boundaries. These zones are as follows: East Shandong Uplift Geothermal Zone (I), Yishu Fault Zone Geothermal Zone (II), West Shandong Uplift Geothermal Zone (III), and Northwest Shandong Depression Geothermal Zone (IV). The Juancheng geothermal field falls under the West Shandong Uplift Geothermal Zone (III), where the primary reservoir is the karst geothermal reservoir of the Lower Paleozoic Cambrian–Ordovician carbonate rocks. The depth to the top of the reservoir ranges from 800 to 1400 m, with overlying sealing layers mainly composed of Cenozoic, Permian, and Carboniferous strata [10]. The measured data indicate a geothermal gradient of approximately 8.97 °C/100 m in the sealing layers (Figure 2), with geothermal water outlet temperatures of 40–60 °C and single-well discharge rates of 100–130 m³/h. The water chemistry is dominated by the SO₄-Ca·Na type.

The recharge source of the karst geothermal water primarily originates from atmospheric precipitation in the bedrock mountainous areas of Liangshan and Jiaxiang, which infiltrates through deep circulation to form groundwater recharge. This system is classified as a weakly open karst geothermal system [11]. Major deep faults, such as the Tianqiao, Juye, and Liaokao Faults, in the region connect deep heat sources, forming heat-conducting pathways. The dense distribution of secondary faults fractures the Ordovician carbonate strata, creating multi-level conductive networks that serve as primary water-conducting channels for the karst reservoir [12].

3. Tracing Experiment Procedure

3.1. Tracer Selection

The selection of tracers must ensure sufficient chemical and thermal stability, high solubility in geothermal fluids, non-adsorption by reservoir rocks, and no chemical reactions with reservoir fluids. Additionally, considering the heterogeneity of karst geothermal reservoirs, which can lead to extremely low concentration gradients of tracers (due to potential multiple flow pathways where individual pathway concentrations may fall below background values), the tracer must exhibit high detection sensitivity with a detection limit lower than or approaching background levels. Furthermore, the tracer must be non-toxic, environmentally compatible, and non-harmful to humans, flora, fauna, and surrounding water bodies, while also not impairing reservoir permeability. After a literature review and background value testing [2,13,14,15,16,17,18], sodium fluorescein was selected as the tracer. Preliminary tests were conducted using site-specific reinjection water to evaluate its compatibility, thermal stability, and adsorption behavior. The results demonstrated that sodium fluorescein exhibits excellent miscibility with water, remains stable without decomposition under high-temperature conditions, and does not react chemically with reservoir rock or adsorb onto formation surfaces. These findings confirm that sodium fluorescein meets the critical selection criteria for the tracing experiment.

3.2. Tracer Injection, Sampling, and Detection

The tracing experiment was conducted after the start of the heating season, which began on 15 November 2024. The tracer injection was initiated on 26 December 2024, following a 41-day continuous operation of the well system prior to the test, during which no impurities were present in the reinjection well. A total of 50 kg of sodium fluorescein was placed into a container, mixed with 3 tons of reinjection water, and stirred until fully dissolved (concentration of 16.67 g/L). The sodium fluorescein solution was then injected into the reinjection well using a constant-flow pump at a continuous and rapid rate. The injection time was 2 h, with an approximate injection rate of 1.5 m³/h.

Sampling and detection began immediately after the tracer injection. The initial sampling frequency was set to once every 12 h. After the first detection of the tracer, the frequency was increased to once every 6 h. When detected concentrations remained persistently low or below the detection limit, the frequency reverted to every 12 h. To ensure data accuracy and reliability, a two-tier quality assurance protocol was implemented during detection: (1) Temporal replicate sampling: three independent samples were collected at each monitoring point (with intervals of 1–2 min), and the arithmetic mean was recorded as the effective concentration value for that time point. (2) Container control: disposable sampling containers were used, with a “one-tube-per-sample” protocol to prevent cross-contamination.

A total of 477 sampling data points were obtained during the test. The detection was performed using the FluoroQuik handheld fluorometric tracer instrument from the National Key Laboratory of Petroleum Resources and Engineering, the China University of Petroleum (Beijing). The FluoroQuik instrument features high sensitivity, minimal susceptibility to contamination, low experimental costs, and ease of operation, with a detection limit of 0.001 μg/L (0.1 ppb).

3.3. Characteristics of Monitoring and Injection Wells

This tracing experiment involved three monitoring wells: LSGY, RBJ, and GJXC. During the tracing experiment, the pumping capacity of the monitoring wells ranged from 100 to 110 m³/h, with outlet temperatures of between 45 and 50 °C. The injection well is approximately 500 m from the LSGY and GJXC wells and about 1200 m from the RBJ well. The karst geothermal aquifer in the test area has a thickness of approximately 50 to 250 m (Figure 3).

4. Results

4.1. Characteristics of Concentration–Time Curves

The LSGY well first detected the tracer after 29 h (Figure 4), followed by peak concentrations at 115 h (1.04 μg/L), 235 h (1.63 μg/L), and 331 h (0.82 μg/L), forming a triple-peak “low-high-low” concentration curve. The multi-peak response indicates the presence of three distinct karst channels between LSGY and the reinjection well, with permeability and path length differences among the channels causing asymmetric distributions of peak concentrations and arrival times. The RBJ well detected the tracer after 5 h (Figure 5), forming a double-peak “low-high-low” curve with peaks at 91 h (0.45 μg/L), 168 h (1.38 μg/L), and 331 h (1.13 μg/L). This exhibits similar three-peak curve characteristics to the LSGY well, indicating the presence of three karst channels. The GJXC well first detected the tracer after 19 h (Figure 6), with peaks observed at 168 h (0.84 μg/L) and 389 h (0.30 μg/L). However, its peak concentrations were significantly lower than those of the other wells, with the first peak as low as 0.30 μg/L, indicating the presence of two karst channels with relatively low permeability between GJXC and the reinjection well.

4.2. Tracer Seepage Velocity

Based on tracing experiment principles, the first appearance time of the tracer corresponds to the maximum groundwater velocity, while the peak time corresponds to the apparent velocity [15,19]. According to the results, for the LSGY well, the apparent velocities at the three peaks were 4.35 m/h, 2.13 m/h, and 1.52 m/h, with a maximum velocity of 17.24 m/h. For the RBJ well, the apparent velocities at the three peaks were 10.98 m/h, 5.95 m/h, and 3.02 m/h, with a maximum velocity of 200 m/h, significantly higher than that of LSGY. For the GJXC well, the apparent velocities at the two peaks were 2.38 m/h and 1.03 m/h, with a maximum velocity of 21.05 m/h. The seepage velocity results indicate that the RBJ well has the highest hydraulic connectivity to the reinjection well, followed by LSGY, with GJXC showing the poorest connectivity, as reflected by its slowest flow velocities.

5. Discussion

5.1. Geometric Characteristics of Ordovician Karst Channels

The development of karst systems is synergistically controlled by fault-related lithology, structural patterns, and the intensity of groundwater circulation, with the karst development intensity decreasing with the increasing burial depth. Since the Ordovician sedimentation occurred, the Juancheng geothermal field has undergone two phases of epigenic karst development and multiple buried karst stages, forming a composite reservoir space dominated by karst cavities and tectonic fractures [20]. The multi-peak patterns (double- and triple-peak) in the concentration–time curves of the monitored wells indicate the presence of multiple heterogeneous flow channels in the karst reservoir (Figure 7). For the LSGY well’s three-channel system, the first channel (apparent velocity 4.35 m/h) had a velocity twice that of the second channel (2.13 m/h), suggesting a shorter pathway or superior connectivity. The third channel (1.52 m/h) exhibited a further-reduced velocity, implying it is a permeability-limited secondary channel. In the RBJ well’s three- channel system, the first channel (10.98 m/h) had a velocity far exceeding the second and third channel (5.95 m/h and 3.02 m/h), yet its concentration (0.45 μg/L) was significantly lower than the latter two (1.38 μg/L and 1.13 μg/L), suggesting its pathway may be short and narrow, while the second and third channel were likely longer and wider. Additionally, the prolonged high concentration during the tracer arrival phase in the second channel indicates the presence of favorable storage space. For the GJXC well’s two-channel system, the small differences in the apparent velocities (2.38 m/h and 1.03 m/h) reflect the comparable but low permeability in the karst channel relative to LSGY and RBJ. Similarly to the second channel in RBJ, the first channel in GJXC may host favorable water storage space, resulting in prolonged high tracer concentrations. The distinct tracer curve patterns among the wells demonstrate the multidirectionality and complexity of karst and channel development.

5.2. Structural Analysis of the Ordovician Karst Flow Channel System

Based on the tracing experiment results, we speculate on the karst channels between the production and reinjection wells in the Juancheng geothermal field and present a schematic diagram of the karst fracture channels between the production and injection wells (Figure 8). The analysis suggests that there are two to three primary geothermal water flow channels in the Juancheng geothermal field region. The main flow channels are identified as the second channels of the LSGY and RBJ wells and the first channel of the GJXC well, which may exhibit long and wide dimensions, spanning the LSGY, RBJ, and GCXJ well zones. These channels possess an excellent storage capacity and karst development, serving as the primary flow and recharge pathways of the reservoir system. Two secondary channels were identified: Secondary channel I exhibits short and narrow characteristics in the LSGY and RBJ well zones but terminates near the GJXC well, with a weak water production capacity, indicating a localized flow channel. Secondary channel II also spans the LSGY, RBJ, and GCXJ well zones, potentially exhibiting long and narrow characteristics. However, its karst development is limited, and it primarily serves a secondary seepage function.

5.3. Control Mechanism of Structural Faults and Burial Depth on Karst Thermal Reservoir Seepage Channels

The radial plot of flow velocity (Figure 9) reveals that under the current exploitation conditions, the maximum apparent flow velocity in the test area is 5.95 m/h, with dominant channel orientations concentrated in the northeast direction. According to the tectono-geological framework of the study area, two NE-SW trending faults exist, whose extension directions align closely with those of the dominant flow channels identified in the tracing experiment. However, the southeastern-oriented channel from the reinjection well to the GJXC monitoring well exhibits the lowest velocity (1.63 m/h), likely linked to the Ordovician burial depth distribution. In this direction, the Ordovician strata attain their maximum burial depth (Figure 1c), resulting in the weaker leaching of the Ordovician top layers and the insufficient development of later-stage burial karsting. Additionally, pre-existing fractures may have been filled, leading to reduced reservoir permeability and the formation of a low-velocity flow zone. This observation highlights the dual control mechanism of tectonic fractures and burial depth in the Juancheng geothermal field. The fracture network dictates the orientation of dominant flow paths through its spatial distribution, while deep burial conditions suppress karst development and fracture connectivity, thereby constraining the flow efficiency. Together, these factors govern the spatial heterogeneity and dynamic evolution of the karst geothermal reservoir system.

5.4. Geothermal Water Seepage and Productivity Development Potential

The curvature method is a method to identify reservoir recharge conditions by analyzing the morphological characteristics of Q-S (flow–drawdown) curves. Its core principle is to calculate the curvature value of the curve, that is, the degree of the curve deviation relationship. The linear curve (curvature ≈ 1) shows that the reservoir has a stable water supply source; the power curve (1 < curvature < 2) reflects that the recharge capacity of the reservoir is limited, but the reservoir space can still provide a certain amount of storage water; the parabolic curve (curve ≥ 2) shows that the reservoir permeability and recharge conditions are poor. In the Juancheng geothermal field, the curvature of the Q-S curve of the LSGY well is 1.03, showing linear characteristics, which proves that its NE-dominant seepage direction has good supply conditions (Figure 10). The curvature of the SCGJ2 well and the SCGJ1 well in the southeast direction of the low-permeability flow is 1.34 and 2.11, respectively, showing the characteristics of the power line and the parabola, implying that the recharge capacity in this direction is relatively poor, which is consistent with the performance characteristics of the tracer flow rate. Combined with the specific yield data of 10 geothermal wells in the Juancheng geothermal field (the specific yield is defined as the discharge rate when the water level in the well bore drops by one meter during a pumping test, i.e., specific yield = water yield/drawdown) (Figure 11), the northeast area with good recharge conditions and seepage channels has a relatively high specific yield (>1.5 L/(s·m)), while the low seepage velocity direction (southeast direction) corresponds to a lower specific yield (<1.0 L/(s·m)). This spatial differentiation further shows that the dominant seepage direction not only has better recharge conditions but also has a stronger water yield and a better exploitation potential. Therefore, from the perspective of resource development, it is suggested that reinjection wells should be preferentially deployed in the direction of northeast dominant seepage, which can effectively develop and utilize geothermal resources.

5.5. Well Deployment Optimization Strategy and Economic Exploitation of Geothermal Resources

The orientation and spacing of reinjection and production wells critically influence the economic exploitation of geothermal resources, directly determining the thermal breakthrough time and the productive lifespan of geothermal wells. Based on hydraulic conductivity derived from pumping tests (

Table 1. Pumping test information of each well.

Parameter		LGSY	SSC1	SSC2	SSC3	SGGJ1	SGGJ2	SCGJ3	YDC1	YDC2
High drawdown	Water yield/m3/d	109	120	121	127	100	89	120	115	123
	Drawdown/m	18	28	57	8	69	54	46	37	39
	Hydraulic conductivity/m/d	5.32	1.71	1.07	6.72	0.08	0.46	1.27	1.45	1.45
Medium drawdown	Water yield/m3/d	95	102	79	89	91	78	85	85	114
	Drawdown/m	16	22	35	5	57	44	33	28	33
	Hydraulic conductivity/m/d	5.19	1.83	1.07	7.60	0.08	0.49	1.20	1.36	1.56
Low drawdown	Water yield/m3/d	72	75	60	73	87	64	60	76	95
	Drawdown/m	12	14	19	3	52	35	18	21	25
	Hydraulic conductivity/m/d	5.14	2.00	1.41	8.56	0.09	0.49	1.45	1.58	1.68
Average hydraulic conductivity/m/d		5.1	2.0	1.4	8.6	0.1	0.5	1.5	1.6	1.7

and Figure 12), the radius of influence under different pumping drawdowns can be calculated, providing key parameters for optimizing well spacing. For well spacing, in Ordovician strata with shallow burial depths (<1200 m), where there is higher hydraulic conductivity (the average hydraulic conductivity ranges from 1.0 to 7.6 m/d.), the well spacing should exceed 400 m to delay the thermal breakthrough and prolong production cycles. In deeper Ordovician zones (>1200 m), where the hydraulic conductivity is relatively low (0–0.5 m/d) and flow rates are reduced, the well spacing can be reduced to 200–300 m to enhance the thermal energy extraction efficiency per unit area and achieve economically optimal exploitation. Guided by the flow direction revealed by the tracing experiment (Figure 8), reinjection and production wells should avoid being parallel to the fault strike to delay the thermal breakthrough time. Additionally, reinjection wells are prioritized for deployment in deeper Ordovician zones (>1200 m), leveraging the lower permeability in these regions to suppress lateral heat diffusion.

6. Conclusions

(1) Tracer concentration–time curves in the Juancheng geothermal field reveal multiple heterogeneous flow channels within the karst reservoir. The concentration curve of the LSGY well exhibits a triple-peak characteristic, indicating the presence of three karst fracture channels between the LSGY and the reinjection well. Similarly, three karst channels exist between the RBJ and the reinjection well, with the main channel demonstrating a superior storage capacity. GCXC shares similarities with RBJ but exhibits the poorest permeability among the karst channels.

(2) The karst reservoir flow system is dually controlled by the fracture orientation and the Ordovician burial depth. Faults dominate the selection of dominant flow paths, while the Ordovician burial depth influences seepage by inhibiting karstification development and fracture connectivity.

(3) Well deployment avoids parallel fault directions as much as possible, with the spacing adjusted according to the Ordovician burial depth. Based on the radius of influence derived from pumping tests, the well spacing in deeper Ordovician zones (>1200 m) should exceed 400 m to delay the thermal breakthrough. In shallower zones (<1200 m), the reduced permeability permits narrower spacing (200–300 m) to enhance the thermal energy extraction efficiency.

(4) This study investigates the seepage characteristics of the karst geothermal reservoir in the Juancheng geothermal field using tracer technology. However, the study still has certain limitations: ① The quantitative evaluation of the differences in thermal breakthrough times under different well placement strategies remains insufficient. ② The impact of long-term reinjection on the geothermal reservoir system has not been clarified. Therefore, it is recommended that future research focus on systematic investigations of the aforementioned issues, as their outcomes will provide a further scientific basis for optimizing geothermal development strategies in the Juancheng geothermal field.