Experimental Technique for Modeling Multi-Field Coupled Transport in Multi-Fracture Geothermal Reservoirs

Abstract

In the operation of enhanced geothermal systems (EGSs), complex physical and chemical coupling processes, which are crucial for the efficient exploitation of geothermal energy, are involved. In situ studies of multi-fracture hot dry rocks (HDRs) face significant challenges, leading to a shortage of experimental data for verifying numerical simulations and supporting experimental techniques. In this paper, a multi-field coupling experimental simulation technique was designed for a multi-fracture geothermal reservoir. This technique enables the experimental investigation of the effects of fracture and reservoir characteristics, working fluid parameters, and wellbore arrangement on the multi-field coupling transport mechanism inside geothermal reservoirs during EGS operation. In addition, the practicability and reliability of the experimental technique were proved via a two-dimensional multi-fracture model. The experimental technique addresses a research gap in studying multi-fracture geothermal reservoirs and holds potential to promote substantial progress in geothermal resource exploitation.

1. Introduction

EGSs involve circulating a working fluid through fracture networks induced by artificial fracturing technology in geothermal reservoirs and extracting heated working fluid (mainly water or carbon dioxide) from the production well(s) for power generation or heating [1]. The operation encompasses a range of physical and chemical processes, including heat conduction and convection in the reservoir matrix, hydrodynamic dispersion, molecular diffusion, and thermo-poroelastic evolution of the reservoir [2,3,4,5]. The comprehensive understanding of these processes is essential for ensuring the effective utilization of geothermal resources in the long term.

There are three methods used to study multiphysics coupling processes in reservoirs: numerical simulation, experimental analysis, and theoretical research. In light of the advantages of numerical simulation, researchers have dedicated considerable efforts in recent years to developing efficient simulators and codes for simulating the spatiotemporal behavior of geothermal reservoirs [2,6]. A multitude of thermal-hydro-mechanical-chemical (THMC) [3,7,8], thermal-hydro-mechanical (THM) [9,10,11,12,13,14], thermal-hydro (TH) [9,10,11,15,16,17], and thermal-hydro-chemical (THC) [18,19,20,21] coupling processes in the geothermal reservoir have been studied via numerical simulation [2]. Nevertheless, achieving a more comprehensive understanding of the performance of EGSs demands further practical and theoretical research [2]. Based on reasonable assumptions and applicable theories, theoretical research seeks to determine the governing equation of multiphysics coupling processes in geothermal reservoirs. Under appropriate boundary and initial conditions, the relevant parameters or state can be determined using the governing equation.

Experimental analysis serves as a fundamental method in scientific investigation. To ensure accuracy and reliability, experimental data must validate the results of numerical simulation and theoretical studies. In this context, two primary experimental approaches play crucial roles: in situ experimental research and laboratory-scale investigations. While in situ tests are often prohibitively expensive, their results provide more accurate guidance for optimizing operating parameters in pursuit of the sustainable development of geothermal resources [22]. Conversely, well-designed laboratory techniques can achieve significant research outcomes at substantially lower costs by effectively simulating the physical and chemical processes occurring in geothermal reservoirs. Studies have made notable advances in experimental simulation. However, most studies have focused on replicating the coupling process in a single fracture. There remains a notable scarcity of comprehensive physical simulation studies examining systems with multiple fractures [23,24,25,26,27].

This research presents an innovative experimental technique designed to accurately simulate multi-field coupling transport processes in multi-fracture geothermal reservoirs. The proposed technique enables a systematic adjustment of the system’s operation parameters, achieving a more faithful replication of coupled transport phenomena characteristic of geothermal reservoirs. This approach provides a valid theoretical basis for geothermal resource development. The experimental system’s capability to reproduce key reservoir dynamics was rigorously verified through parallel numerical simulations, establishing a robust theoretical foundation for geothermal resource development strategies.

2. Design of Experimental Technique System

The experimental system architecture comprises three integrated subsystems (Figure 1): a temperature control system, a simulation system, and a data system.

Given that multi-field coupling transport processes are influenced by geothermal reservoir temperature conditions, a temperature control system has been designed to meet high-temperature simulation requirements. The primary components of this system include a high-temperature-resistant elastic plate, electric heating plates, a heating plate fixing device, a temperature control system, and an insulation layer. The temperature within the experimental technique system is regulated by two electric heating plates. To ensure optimal thermal contact between the heating plate and the simulation system, a high-temperature-resistant elastic plate is positioned at the interface. This design minimizes experimental errors, facilitates data processing, and ensures uniform heating throughout the simulation system. Furthermore, an external insulation layer has been implemented to reduce energy loss during experiments, thereby significantly decreasing system temperature fluctuations.

The simulation system, comprising a desired rock mass for study and a circulation system for fluid flow, serves as a key part of replicating multi-field coupling transport processes during geothermal exploitation. The system mimics a fractured geothermal reservoir by assembling an experimental rock sample with an anti-seepage ring, secured via a fixing device. The circulation system includes a liquid tank, injection pump, connection pipeline, boreholes in samples, fractures, and an anti-seepage ring. The constant temperature of the liquid tank serves as the provider of injection fluid and maintains the injected fluid at a consistent temperature, enhancing simulation accuracy and facilitating data processing. The injection pump provides the power for circulating the experimental fluid in the simulation system. Connecting pipelines, sample boreholes, and fractures in the system create fluid migration channels, simulating the fluid transport process in a geothermal reservoir’s engineering system, including pipelines, wellbores, and fractures during heat extraction. The anti-seepage ring serves a dual purpose: preventing fluid leakage from the simulation system and adjusting the fracture aperture as the simulation system’s thickness increases. The ring’s structural design, illustrated in Figure 2., ensures high precision in adjusting the crack opening of the anti-seepage ring. The outlet liquid tank collects circulating fluid which flows through the whole simulation system, facilitating disposal.

The data system, which consists of flow meters, temperature sensors, and a computer system, is primarily used to monitor research parameters in the simulation system and to store data for post-test analysis and research. Each sensor’s range and location can be adjusted to meet the needs of the experiment.

The data system, comprising flow meters, temperature sensors, and a computer system, plays a primary role in monitoring research parameters within the simulation system and storing data for post-test analysis and research. The range and location of each sensor can be adjusted to meet the specific requirements of the experimental research.

3. Realization of Experimental Technique

3.1. Preparation of Experiment

To commence, rock samples are prepared based on the specific research requirements. Determination of the geometric dimensions (thickness, length, and height) and surface characteristics of the rock samples precede the investigation. Circular holes with a specific scale are then drilled into the rock samples to simulate injection/production wells. It is crucial to note that the drill positions on each rock sample are carefully maintained to prevent blockage of the channel after installation. For the simulating of injection and production wells, only one hole is drilled in the outermost two rock samples.

As depicted in Figure 1, the prepared rock samples are assembled with appropriate anti-seepage rings placed between samples. Subsequently, a fixation device is utilized to secure the insulation layer, rock samples, and anti-seepage rings. This ensures close contact between the anti-seepage ring and the rock sample, preventing fluid leakage during the experiment. High-temperature-resistant elastic plates and electric heating plates are then installed on the upper and lower sides of the experimental system through fixed devices, ensuring that all components are in close contact. Finally, the remaining components of the system are connected, and the sealing and safety of the experimental system are thoroughly inspected.

3.2. Experimental Process

Initially, electric heating plates were used to heat and maintain the simulation system for a specific duration, ensuring that the whole system reaches the required equilibrium state. Subsequently, experimental fluids from the constant-temperature liquid supply tank are injected into the system via the injection pump, simulating the multi-field coupling transport in geothermal reservoirs. Concurrently, relevant experimental data such as inlet/outlet fluid velocity and temperature, outlet fluid flow, sample temperature, and the physical-chemical properties of working with fluids are collected for subsequent analysis.

4. Application of Experiment Technique

During the extraction of geothermal resources, heat is transferred through three methods: conduction, convection, and radiation. Given that heat radiation plays a minor role in geothermal reservoirs and can be safely ignored, the focus in the research on heat transfer in geothermal systems is primarily on the thermal conduction of the reservoir rock skeleton and the heat convection between the reservoir matrix and working fluid, as well as within the fluid [28]. When the temperature of a rock sample is below 400 °C, the effect of the cold injection fluid on the rock structure is minimal [29]. Additionally, because of the experimental system’s outlet pressure matching with the atmospheric pressure, it is too low to significantly affect fracture characteristics, and injecting cold water into a fracture network in geothermal reservoirs does not substantially cause a noteworthy effect on the fracture characteristics and the coupled thermo-poroelastic process due to pressure changes [30]. The coupled thermo-poroelastic process’s impact can also be ignored. Moreover, the experimental system allows for the adjustment of the fracture aperture. Therefore, considering the conditions of the experiment and the actual site, the impact of the stress field on the multi-field coupling transport process is disregarded, and only the THC coupling transport process is considered. The experimental technique is designed to investigate the impact of various factors on EGS performance under the control of the THC coupling transport process. The acquisition of these experimental data can also verify the correctness of the theoretical model, thereby promoting the development of geothermal science.

4.1. Fracture Characteristics

The fracture network surfaces serve a pivotal role in the heat exchange between the circulating working fluid and the reservoir matrix [4]. The efficiency of energy exchange between the reservoir matrix and circulating fluid is determined by the various fracture characteristics and their distribution, including the number of fracture, the fracture surface roughness, the connectivity or permeability of the fracture zone, the aperture, etc. [31]. The production temperature is intricately linked to the total flow-accessible volume of the reservoir and the mean effective joint spacing [10]. Chandrasiri Ekneligoda et al. [32] investigated the optimal parameters for production temperature, revealing that the number/width/length of fractures all influence production temperature. Extremely well-developed hydraulic fractures provide a larger energy exchange area between the flowing working fluid and the reservoir matrix, along with a more conductive flow pathway. Studies indicate that heat extraction performance improves by increasing the number of fractures and decreasing fracture spacing in multi-fracture reservoirs [9].

Since the fractures in the simulation system proposed in this paper are formed by the gaps between the rock blocks, the size and characteristics of the fracture surface can be controlled during the preparation of the experimental samples. Moreover, the fracture surface features can be extracted by scanning the rock sample surface before the experiment, which provides a foundation for the subsequent study on the influence of fracture features on thermal extraction performance.

4.2. Reservoir Characteristics

The utilization and application of geothermal energy are significantly influenced by reservoir characteristics, including initial reservoir temperature, heat transfer characteristics, overall reservoir permeability, reservoir mean pressure, and others [1,10,19,22]. The natural geothermal reservoir has substantial lithology and energy heterogeneity, which is represented by uneven material distribution and a temperature gradient, influencing the heat transfer process in the geothermal reservoir by virtue of thermal conductivity and temperature difference [33,34]. The change in reservoir temperature caused by the exploitation process can induce a variation in the heat recovery efficiency, leading to the continual evolution in the production efficiency of EGSs [10]. Jing et al. [19] suggested that initial reservoir temperature has a significant impact on EGS long-term performance through numerical simulation. The thermal production efficiency is affected by changes in reservoir temperature, influencing the distribution characteristics of reservoir seepage fields. The reservoir permeability and the heat conduction of the rock matrix influence mass and energy exchange between the fracture and rock interface [2]. Saeid [28] suggested that reservoir porosity and permeability have an important effect on heat exploitation efficiency and system lifetime.

The designed temperature control system can accurately regulate the simulated temperature. The temperature control range relies on the resistant temperature of the impermeable material, typically not exceeding 350 °C. The simulation of other reservoir characteristics is achieved by taking different rock samples with different characteristics (e.g., porosity or thermal conductivity).

4.3. Working Fluid Parameters

The working fluid plays a crucial role in the exploitation of heat energy from geothermal reservoirs to the surface. The state of seepage and heat transfer in the reservoir is influenced by the EGS’s operation parameters (pressure/temperature/flow rate of working fluid, and water chemistry, as well as the outlet fluid pressure) and the characteristics of the working fluid (viscosity, density, heat transfer coefficient, and so on), thereby impacting the overall heat exploitation performance of the geothermal reservoir [35,36]. Ghassemi et al. [30] observed that the injection rate of working fluid has a significant effect on the outlet temperature evolution of the production well. Saeid et al. [28] evaluated the effect of viscosity and salinity of the reservoir fluid on the reservoir lifetime. Zeng et al. [22] conducted a numerical investigation to study the main factors affecting the performance and efficiency of the Yangbajing geothermal field, showing that the water production rate and injection temperature have a significant impact on EGS production and efficiency. McDermott et al. [37] looked into the effects of thermal-hydro-mechanical-chemical coupling on EGS performance and discovered that the electricity generation power is proportional to water properties such as temperature, pressure, and salinity. Guo et al. [38] investigated the evolution of temperature and pressure field distributions in the Songliao Basin geothermal field at various flow rates, as well as their impact on electricity generation.

4.4. Wellbore Arrangement

The layout of wellbores significantly influences the development of geothermal resources. An optimal wellbore arrangement is crucial for maximizing the production efficiency of geothermal resources. Too-small spacing may result in heat accumulation problems, while excessive spacing can cause problems such as insufficient energy extraction and increased fluid resistance [39]. Therefore, some studies have focused on the influence of wellbore layout on EGS thermal exploitation performance and optimal well layout design for efficient geothermal mining. Du et al. [39] established a three-dimensional coupling numerical model to simulate and optimize heat transfer schemes for buried-pipe heat pumps. Their results indicated that a lower space between heat holes could lead to heat accumulation problems, negatively affecting shallow geothermal energy utilization. However, these issues can be mitigated through the design of well-thought-out well spacing. Jing et al. [19], through numerical simulations, concluded that well spacing significantly impacts the long-term performance of geothermal reservoirs. Additionally, Zeng et al. [22] observed that horizontal wells exhibit higher water production rates and lower reservoir impedance compared to vertical wells in EGSs. In summary, a rational well spacing design is essential to avoid problems associated with heat accumulation and to optimize the long-term performance of geothermal reservoirs, especially in the context of EGSs with horizontal wells.

4.5. The Mechanism of Multi-Field Coupling Transport

The cold injection fluid can disrupt the equilibrium of the reservoir’s physical and chemical field. This disturbance enhances water–rock interactions, initiating dissolution and precipitation processes, and modifying the pore and permeability characteristics of the reservoir. Despite these observable changes, the precise understanding of how pore permeability characteristics evolve due to mineral dissolution and precipitation remains incomplete [2].

Geothermal systems are designed to operate for prolonged periods for considerable project income, often surpassing 20 years. In long-term EGS operation, fluid–rock interaction (WRCI) inevitably has a pivotal effect on the reservoir permeability in EGSs with high-temperature and high-pressure conditions [19]. Numerical simulation is the most effective tool for predicting the long-term effects of WRCI on reservoir thermal performance. Due to the lack of sufficient reaction rate data, accurate numerical simulation is still a challenge. Consequently, the chemical aspects of many geothermal reservoir models are underdeveloped because of persisting uncertainties, including the rate of ion exchange reactions and limitations in describing mineral precipitation and dissolution [19].

At present, research on THC coupling in geothermal reservoirs is predominantly centered on numerical simulation, with limited studies focusing on experimental simulations [18,19,20,21,40]. Bächler et al. [40] employed numerical simulation to investigate the effect of THC coupling on the production performance of the EGS reservoir. The results underscored the necessity of incorporating geochemical factors into integrated models of EGSs. Kiryukhin et al. [20] investigated the effects of the primary-secondary mineral solution and precipitation on the porosity of the geothermal reservoir in the context of THC coupling using data from 14 geothermal sites in Japan and Kamchatka (Russia). The findings highlighted a substantial influence on the thermodynamic and kinetic parameters of chemical interaction.

5. Evaluation of Experimental Techniques

A two-dimensional numerical model of seepage and heat transmission in a multi-fracture rock mass is developed based on the experimental approaches presented in this paper. This model showcases the applicability of the experimental technique for multi-field coupling studies in geothermal reservoirs.

5.1. Numerical Model

A 2D numerical model (Figure 3) representing seepage and heat transfer in a multi-fracture rock mass was established using the experimental technique outlined in this study. The model includes features such as injection and production wells, fractures, and a reservoir matrix. The model incorporates nine parallel fractures, each with a 3 mm aperture, characterized by a smooth surface. The fracture diameter of 3 mm was based on the measurement results of the Fenton Hill project [10]. Granite, a common lithology in EGSs, is selected as the rock sample. Each rock sample block has a thickness of 10 cm. Because the granite is extremely dense, the fluid flow channels in the system are almost entirely provided by fractures, permitting negligible fluid penetration in the granite. Both injection and production wells, with a diameter of 5 cm, are included in the system. Simultaneously, an injection well and a production well with a diameter of 5 cm are established in the model. The entire system has a width of 1 m and a height of 1.414 m, mirroring the size ratio of geothermal reservoir systems in engineering practice.

For simplicity, the fluid within the fractures is assumed to be a two-dimensional steady laminar flow, characterized as a constant physical property and an incompressible Newtonian fluid with no internal heat source. The model neglects heat dissipation from fluid viscous dissipation, and the fluid remains in the liquid phase throughout the system’s operation.

Based on the numerical model and the above assumptions, the governing equations in this work are as follows:

$${\displaystyle \frac{\partial T}{\partial t}}+u_x{\displaystyle \frac{\partial T}{\partial x}}+u_y{\displaystyle \frac{\partial T}{\partial y}}={\displaystyle \frac{\lambda }{\rho C_p}}\left({\displaystyle \frac{{\partial }^{2}T}{\partial x^2}}+{\displaystyle \frac{{\partial }^{2}T}{\partial y^2}}\right)$$

(1)

$${\displaystyle \frac{\partial u_x}{\partial t}}+u_x{\displaystyle \frac{\partial u_x}{\partial x}}+u_y{\displaystyle \frac{\partial u_x}{\partial y}}=F_x-{\displaystyle \frac{1}{\rho }}{\displaystyle \frac{\partial p}{\partial x}}+\mu \left({\displaystyle \frac{{\partial }^2{u}_x}{\partial x^2}}+{\displaystyle \frac{{\partial }^2{u}_x}{\partial y^2}}\right)$$

(2)

$${\displaystyle \frac{\partial u_y}{\partial t}}+u_x{\displaystyle \frac{\partial u_y}{\partial x}}+u_y{\displaystyle \frac{\partial u_y}{\partial y}}=F_y-{\displaystyle \frac{1}{\rho }}{\displaystyle \frac{\partial p}{\partial y}}+\mu \left({\displaystyle \frac{{\partial }^2{u}_y}{\partial x^2}}+{\displaystyle \frac{{\partial }^2{u}_y}{\partial y^2}}\right)$$

(3)

$${\displaystyle \frac{\partial u_x}{\partial x}}+{\displaystyle \frac{\partial u_y}{\partial y}}=0$$

(4)

where T is temperature, u_x and u_y are fluid velocities in the x and y directions, respectively, λ is rock thermal conductivity, ρ is the fluid density, p is pressure, C_p is rock specific heat, μ is fluid viscosity, and F_x and F_y are inertia forces in the x and y directions, respectively.

5.2. Boundary Conditions and Calculation Parameters

In this study, the entire system starts with an initial temperature of 473 K. The upper and lower limits of the rock mass are maintained at a constant temperature of 473 K, while the left and right boundaries are adiabatic. A cold fluid (water) with a temperature of 293 K enters the system at point A, flows through the well and fractures, and exits at point B after heat exchange. The fluid maintains a constant speed of 0.5 m/s. Other calculation parameters are chosen based on relevant geological exploration data [41,42], as summarized in

Table 1. Study parameters.

Parameter	Value
rock density	2650 kg/m3
rock thermal conductivity	3.49 W/m·K
rock specific heat capacity	920 J/kg K
fluid density	900 kg/m3
fluid thermal conductivity	0.6069 W/m·K
fluid specific heat capacity	4181.7 J/kg K
hydrodynamic viscosity	0.3 mPa·s

.

5.3. Model Verfication

Utilizing exact analytical models to verify numerical models is a straightforward and reliable method for model verification [41,42]. A numerical model shown in Figure 4 was established and calculated using COMSOL Multiphysics 6.0, and the simulation results were compared with the analytical solutions for model verification. The numerical model was a 2D rectangular rock zone (100 m × 100 m) with a single fracture. Water is injected through the single fracture at a constant temperature of Tinj and a constant flow rate of vinj into the system with an initial temperature of Ti to extract heat from the rock matrix. Barends derived the analytical solution to calculate the temperature in the fracture as Equation (9) based on fluid flow and heat transfer in a single fracture within a rock matrix that is infinite in two dimensions (infinite extending in the X and Z directions) [43]. The mean and value of variables in Equation (5) are shown in

Table 2. The mean and value of variables in the Equation (5) and for the verification case.

Variable	Description	Value
Tf	Temperature in the single fracture	-
Ti	Initial temperature of the rock matrix	353.15 K
Tinj	Injection temperature	303.15 K
λs	Thermal conductivity of rock matrix	2.337 W/(m·K)
ρf	Density of water	1000 kg/m3
Cp, f	Heat capacity of water	4200 J/(kg·K)
dfs	Aperture of the single fracture	0.005 m
vinj	Injection velocity of water	0.01 m/s
ρs	Density of rock matrix	2790 kg/m3
Cp, s	Heat capacity of rock matrix	767.38 J/(kg·K)

, where Erfc and U denote the complementary error function and the unit step function, respectively.

$$T_{\mathrm{f}}=T_{\mathrm{i}}+\left(T_{\mathrm{i}\mathrm{n}\mathrm{j}}-T_{\mathrm{i}}\right)\mathrm{e}\mathrm{r}\mathrm{f}\mathrm{c}\left({\displaystyle \frac{{\lambda }_{\mathrm{s}}x/\left({\rho }_{\mathrm{f}}{C}_{\mathrm{p},\mathrm{f}}{d}_{\mathrm{f}}\right)}{\sqrt{v_{\mathrm{i}\mathrm{n}\mathrm{j}}\left(v_{\mathrm{i}\mathrm{n}\mathrm{j}}t-x\right){\lambda }_{\mathrm{s}}/\left({\rho }_{\mathrm{s}}{C}_{\mathrm{p},\mathrm{s}}\right)}}}\right) \mathrm{U}\left(t-{\displaystyle \frac{x}{v_{\mathrm{i}\mathrm{n}\mathrm{j}}}}\right)$$

(5)

Figure 5 illustrates the comparison between the analytical solution and the numerical solution of the fracture temperature of the single-fracture model within 200 days. It depicts the temperature evolution at various fracture positions (x = 20 m, 40 m, 60 m, 80 m) over time. It can be seen that the numerical solution and the analytical solution have slight deviations in the initial stage, but the later stabilization stage is in good accordance. The initial deviation comes from two potential sources [44,45]: firstly, inconsistencies in the computational space between the analytical and numerical solutions, and secondly, errors induced by the discretization of the numerical solution. However, the maximum deviation of 0.5% falls within acceptable limits.

5.4. Evolution of Temperature Field of the Experimental System

Figure 6 illustrates the evolving temperature field of a multi-fracture rock mass over various times. It can be seen that the system’s temperature field begins to stabilize around 1000 min into operation. To analyze the temperature field’s evolution, the system was divided into three key areas: below the injection well, the middle fracture area, and above the production well.

Area beneath the injection well: Convective heat exchange occurs between them when cold fluid enters the injection well and contacts the system due to the temperature difference between the cold injected fluid and the fracture surface. By the time the fluid approaches the injection well’s exit, a dynamic equilibrium is established, leading to localized perturbations in the system’s temperature field. The disturbance zone expands toward the injection well outlet and diminishes as heat is transported away by the fluid.

Area of the fracture: To gain a deeper understanding of the temperature evolution within the fracture area, the temperature field distribution of multi-fracture rock mass at 180 s and 240 s are presented in Figure 7. At 180 s, the fluid has achieved dynamic temperature equilibrium with the rock mass before reaching the first fracture. As a result, the temperature field of a system behind the first fracture remains undisturbed before the 180 s mark. After 240 s, subsequently injected fluid, which has not yet attained thermal dynamic equilibrium with the rock mass, enters the first fracture. Heat exchange occurs on both sides of the fracture, disrupting the initial fracture temperature field. However, since the fluid has already established dynamic equilibrium with the rock mass before entering subsequent fractures, the temperature field of subsequent fractures remains unaffected. This process repeats until convective heat transfer equilibrium is established between all fracture regions and fluids. Simultaneously, as depicted in Figure 6 over time, the low-temperature area, defined as temperatures below 323 K in the fracture area, disperses near the 3rd and 4th fractures, rather than close to the water injection area. This dispersion pattern is attributed to the larger volume of rock mass near the first fracture, containing more heat, resulting in the slower temperature drop in the rock mass near the first fracture. Moreover, the temperature in the fracture area at the output side is not the lowest, as the fluid is already heated by the surrounding rock mass before reaching the rear fracture. As a result, the rock mass temperature in the rear fracture area is higher.

The area above the production well: Compared to the other two zones, the area above the production well exhibits straightforward distribution and evolution characteristics in the early stage. In the early stage, the injected fluid will achieve dynamic temperature equilibrium with the rock mass before it arrives at the production well area. There is no noticeable temperature differential between the fluid and the rock mass, resulting in a constant temperature field. After about 180 min, the fluid, which has not been sufficiently heated, flows into the production well and exchanges energy with rock mass in this area, initiating heat decrease with the upper rock mass. The isotherm of the upper rock mass becomes essentially parallel to the well wall of the production well. However, a dead temperature zone emerges in the top left corner, characterized by very slight temperature changes. This zone persists even when the temperature field of the entire system stabilizes. The presence of a dead temperature zone can hinder the complete utilization of heat in the rock mass. Therefore, minimizing or avoiding the occurrence of a dead temperature zone in hot dry rock geothermal engineering is essential to increase the rate of heat exploitation in the geothermal reservoir rock mass.

The above-mentioned distribution and evolution features of the system temperature field are essentially comparable with the evolution characteristics of the geothermal reservoir temperature field during the geothermal resource exploitation process. The presence of a constant temperature area demonstrates the experimental device’s dependability and practicability [46].

6. Conclusions

The exploration of multi-field coupling transport mechanisms in geothermal reservoirs is pivotal for the efficient development and utilization of geothermal resources. In this research, an experimental technique was designed for studying multi-field coupling transport in geothermal reservoirs. This technique enables the investigation of fracture characteristics, reservoir properties, working fluid parameters, and wellbore arrangements on EGS production performance, as well as the mechanism of multi-field coupling transport in a geothermal reservoir with thermo-hydro-chemical coupling.

A two-dimensional numerical model is constructed using the proposed experimental technique to showcase its practicability. The evolution of the temperature field during system operation is then examined. Simulation results indicate that the temperature field’s distribution and evolution characteristics closely resemble those observed in an actual geothermal reservoir during resource utilization. The existence of a constant temperature area underscores the dependability and practicality of the experiment.

It should be noted that the effects of pore-elastic stress and thermal stress were not taken into account in the design. However, it is still projected to overcome the current difficulties in carrying out in situ experiments and improve the research status of fewer data confirmed by numerical simulation, while also providing experimental technical assistance for relevant research.