Method and device for determining circulation injection-production process of geothermal multilateral well

Abstract

This invention relates to the field of underground space physical energy storage, and discloses a method and apparatus for determining the circulating injection and production process of a geothermal multi-branch well. The method includes: constructing a physical simulation experimental platform for circulating injection and production of a geothermal multi-branch well based on the actual conditions of the target geothermal well; constructing a digital twin model of the circulating injection and production process of the target geothermal well based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform; calibrating the digital twin model using the experimental results of the physical simulation experimental platform under different injection and production processes; and using the calibrated digital twin model to simulate the output results under different injection and production processes. This application integrates experimental methods and numerical calculation techniques to construct a multi-source data-driven digital twin, which can provide a deeper understanding of the digital twin of the multi-phase and multi-field coupled motion of rock strata. It enables optimization of wellbore process parameters and dynamic monitoring of the reservoir.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of underground space physical energy storage, and particularly to a method and apparatus for determining the geothermal multi-branch well circulating injection and production process. Background Technology

[0002] Aquifer reservoirs are one of the main targets for geothermal development, characterized by large reserves and small temperature fluctuations. The method involves injecting cold water into the aquifer using well reinjection. The cold water, due to its own pressure (hydraulic head difference), displaces the original groundwater, thus storing it in the aquifer surrounding the well. Simultaneously, the same volume of hot water is extracted from the reservoir through production wells, which, while maintaining formation pressure, is used for energy utilization such as power generation and heating.

[0003] However, in practical applications, due to geological conditions, the production capacity of injection and production wells differs to some extent. To ensure simultaneous reinjection and production within the same formation, branch well technology is one solution.

[0004] Branched well technology, by constructing multi-branched wellbores, can effectively increase well control volume and improve injection / production capacity. However, in practical engineering applications, the complex wellbore structure leads to intricate coupling relationships between the flow within the wellbore and formation seepage, resulting in pressure and flow response characteristics that are difficult to interpret. This poses significant challenges to well placement and thermal breakthrough risk assessment during the overall geothermal field development process. Summary of the Invention

[0005] The purpose of this invention is to provide at least one method and apparatus for determining the circulating injection and production process of geothermal multi-branch wells, which can at least solve the technical problem of difficult-to-understand pressure and flow response caused by the complex coupling relationship between pipe flow in the wellbore and formation seepage, and can at least achieve more efficient analysis of wellbore-reservoir flow and stress state, and realize the optimization of wellbore process parameters and dynamic monitoring of reservoir.

[0006] To address the aforementioned technical problems, at least one embodiment of this application provides a method for determining the circulating injection and production process of a geothermal multi-branch well, comprising:

[0007] Based on the geological data of the target geothermal well, a physical simulation experimental platform for the circulating injection and production of the target geothermal well's multi-branch well is constructed. The wellbore structure, branch layout, and geological strata of the physical simulation experimental platform correspond to the actual situation of the target geothermal well, so as to simulate the fluid behavior of the target geothermal well under different injection and production processes.

[0008] Based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform, a digital twin model of the circulating injection and production of the multi-branch well of the thermal reservoir of the target geothermal well is constructed. The initial state data of the fluid field includes at least one of inlet flow rate, temperature, pressure and flow velocity.

[0009] The experimental results of the physical simulation experimental platform under different injection and production processes are obtained. The initial parameters of the digital twin model are adjusted using the experimental results until the difference between the prediction results obtained by the physical simulation experimental platform and the digital twin model under the same injection and production process meets the preset error standard, thus obtaining the adjusted digital twin model of the geothermal multi-branch well cyclic injection and production.

[0010] Based on the adjusted geothermal multi-branch well circulating injection and production digital twin model, the outlet flow rate under different process parameters is simulated, and the target injection and production process is determined according to the outlet flow rate. The process parameters include at least one of the following: injection temperature, injection pressure, number of multi-branch wells, and structure of multi-branch wells.

[0011] At least one embodiment of this application also provides an apparatus for determining the geothermal multi-branch well circulation injection and production process, comprising:

[0012] The physical simulation experimental platform construction module is used to construct a physical simulation experimental platform for the circulating injection and production of the multi-branch well of the target geothermal well based on the geological data of the target geothermal well. The well structure, branch layout and geological strata of the physical simulation experimental platform correspond to the actual situation of the target geothermal well in order to simulate the fluid behavior of the target geothermal well under different injection and production processes.

[0013] The digital twin model construction module is used to construct a digital twin model of the thermal reservoir multi-branch well circulation injection and production of the target geothermal well based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform. The initial state data of the fluid field includes at least one of inlet flow rate, temperature, pressure and flow velocity.

[0014] The digital twin model adjustment module is used to obtain the experimental results of the physical simulation experimental platform under different injection and production processes, and to adjust the initial parameters of the digital twin model using the experimental results until the difference between the prediction results obtained by the physical simulation experimental platform and the digital twin model under the same injection and production process meets the preset error standard, thereby obtaining the adjusted digital twin model of the geothermal multi-branch well cyclic injection and production.

[0015] The injection and production process determination module is used to simulate the outlet flow rate under different process parameters based on the adjusted geothermal multi-branch well cyclic injection and production digital twin model, and determine the target injection and production process according to the outlet flow rate. The process parameters include at least one of the following: injection temperature, injection pressure, number of multi-branch wells, and structure of multi-branch wells.

[0016] At least one embodiment of this application also provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the above-described method for determining the geothermal multi-branch well cyclic injection and production process.

[0017] At least one embodiment of this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for determining the geothermal multi-branch well circulating injection and production process.

[0018] The method and apparatus for determining the geothermal multi-branch well circulation injection and production process provided in the embodiments of this application take the actual geological conditions of geothermal wells as a typical scenario, builds an experimental model of the geology based on field data, and explores the inherent laws of multi-phase and multi-field coupled motion and establishes a mechanism model through three-dimensional modeling and computational fluid dynamics. An Internet of Things (IoT) is built to dynamically sense information such as fluid transport, and a global spatiotemporal information database is established by inverting real-time monitoring data. A digital twin method combining experimental and simulation methods for multi-branch circulation injection and production of geothermal reservoirs is constructed. By integrating experimental methods and numerical calculation techniques to build a multi-source data-driven digital twin model, a deeper understanding of the digital twin of multi-phase and multi-field coupled motion of rock strata can be achieved. This method can cover the entire process of "well construction-intelligent production-operation-management" for multi-branch wells in geothermal reservoirs, achieving a comprehensive characterization of the impact on production behavior, more efficiently analyzing wellbore-reservoir flow and stress state, optimizing wellbore process parameters of branch wells, and dynamically monitoring reservoirs, effectively guiding the entire life cycle of production planning.

[0019] In some optional embodiments, the physical simulation experimental platform for constructing the multi-branch well circulation injection and production of the target geothermal well's reservoir based on the geological data of the target geothermal well includes:

[0020] Based on the actual working conditions of the target geothermal well, a main structure is constructed, which includes an injection well, a production well, a multi-branch well, a simulated reservoir, and a connecting pipeline system.

[0021] A liquid circulation system is constructed to simulate the high-temperature and high-pressure environment of a geothermal well. Sensors are installed at target locations on the main structure to monitor at least one of pressure, flow rate, and temperature. The target locations include at least one of the inlet of the injection well, the outlet of the production well, the interior of the simulated reservoir, and the connection point of the multi-branch wells.

[0022] In this embodiment, the main structure (including injection well, production well, multi-branch well, simulated reservoir, etc.) is built based on the actual operating conditions of the target geothermal well, which can realistically reproduce the injection and production process of the geothermal well. The physical simulation experimental platform can more accurately reflect the actual operating status of the geothermal well, providing a reliable foundation for subsequent experimental research and optimization.

[0023] In some optional embodiments, constructing a digital twin model of the target geothermal well's multi-branch well circulation injection and production based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform includes:

[0024] Based on the geological data of the target geothermal well, a three-dimensional geometric model corresponding to the actual medium and the target geothermal well is constructed.

[0025] The three-dimensional geometric model is discretized into a finite number of mesh elements;

[0026] Based on the initial state data of the fluid field and the geophysical characteristic data in the geological data of the target geothermal well, a fluid dynamics calculation model is built for the gridded three-dimensional geometric model to obtain a digital twin model of the multi-branch well cyclic injection and production of the target geothermal well. The fluid dynamics calculation model is used to map and simulate the injection and production process of the target geothermal well. The geophysical characteristic data includes at least one of porosity, permeability and hydrostatic pressure gradient.

[0027] In this embodiment, the gridded model can more accurately simulate the flow behavior of fluids in geothermal reservoirs. It can capture the impact of local details (such as fractures and pores) on the injection and production process. By numerically simulating the flow, heat transfer, and mass transfer processes of fluids, the operating status of geothermal wells can be accurately predicted. This provides a more accurate scientific basis for optimizing the injection and production process.

[0028] In some alternative embodiments, discretizing the three-dimensional geometric model into a finite number of mesh elements includes:

[0029] For the geometric features and physical properties of different components of the three-dimensional geometric model, local mesh sizes are defined accordingly;

[0030] The three-dimensional geometric model is meshed according to the preset global mesh size and the local mesh size.

[0031] In this embodiment, by defining local mesh sizes specifically for the geometric features and physical properties of different components of the 3D geometric model, it is possible to ensure that the mesh generation more closely matches the actual situation of the model. This refined mesh generation helps to capture the subtle features and physical behavior of the model, thereby improving the accuracy of simulation and analysis. It also helps to reduce unnecessary computation and improve computational efficiency.

[0032] In some alternative embodiments, the three-dimensional geometric model is discretized into a finite number of mesh elements, including:

[0033] Generate octree-style volume and surface meshes;

[0034] Delete the octree-form volume mesh, and retain the octree-form surface mesh;

[0035] Based on the octree-form surface mesh, the volume mesh is regenerated using the Deloitte triangulation method.

[0036] In this embodiment, generating octree-form volume and surface meshes enables efficient partitioning of the 3D space. Deleting the octree-form volume mesh while retaining the surface mesh allows for a more accurate representation of the surface features of the 3D geometric model. Based on the octree-form surface mesh, regenerating the volume mesh using the Delaunay triangulation method ensures that the generated volume mesh has more regular triangle shapes, reduces the number of distorted triangles, and improves mesh quality.

[0037] In some optional embodiments, the process of building a fluid dynamics calculation model for the meshed three-dimensional geometric model based on the initial state data of the fluid field and the geophysical characteristic data of the target geothermal well includes:

[0038] The geophysical property data and the initial state data of the fluid field are input into computational fluid dynamics software. Pressure inlet and pressure outlet are set, laminar or turbulent flow models are adopted, and the wall boundary conditions of the three-dimensional geometric model are used as numerical simulation boundary conditions to construct the fluid dynamics calculation model.

[0039] In this embodiment, based on experimental data obtained from a physical simulation experimental platform for the circulating injection and production of a multi-branch well in the geothermal reservoir of the target geothermal well, the initial state of the fluid field in the three-dimensional geometric model is set, including inlet flow rate, temperature, pressure, and velocity. This experimental data reflects the actual operating state of the geothermal well, making the constructed fluid dynamics calculation model more closely resemble reality and enhancing its practicality. The geophysical characteristic data and the initial state data of the fluid field in the three-dimensional geometric model are input into computational fluid dynamics software, utilizing the software's efficient computing capabilities for numerical simulation. Simultaneously, by setting pressure inlet and outlet, and employing laminar or turbulent flow models, the flow state of the fluid in the three-dimensional geometric model can be obtained more quickly, improving computational efficiency.

[0040] In some optional embodiments, the method further includes discretizing the fluid dynamics calculation model using a second-order upwind scheme.

[0041] In this embodiment, under complex flow conditions such as turbulence and vortices, the fluid motion often exhibits high nonlinearity and instability. The second-order upwind scheme can better adapt to these complex flow conditions and provide more accurate simulation results. Attached Figure Description

[0042] One or more embodiments are illustrated by way of example with reference to the accompanying drawings, and these illustrative descriptions do not constitute a limitation on the embodiments.

[0043] Figure 1 This is a flowchart of a method for determining the geothermal multi-branch well circulation injection and production process provided in one embodiment of this application. Figure 1 ;

[0044] Figure 2 This is a schematic diagram of the overall structure of a physical simulation experimental platform provided in one embodiment of this application;

[0045] Figure 3 This is a schematic diagram of different multi-branch geothermal well models provided in one embodiment of this application;

[0046] Figure 4 This is a schematic diagram of the result of multi-branch radial well mesh generation provided in one embodiment of this application;

[0047] Figure 5 This is a schematic diagram of setting boundary conditions provided in one embodiment of this application;

[0048] Figure 6 This is a schematic diagram illustrating the variation of injection pressure under different processes, provided in one embodiment of this application;

[0049] Figure 7This is a schematic diagram illustrating the effect of different numbers of branch wells on wellhead discharge rate provided in one embodiment of this application;

[0050] Figure 8 This is a schematic diagram illustrating the effect of branch well length variation on wellhead discharge rate provided in one embodiment of this application;

[0051] Figure 9 This is a schematic diagram comparing the injection and production effects of a single-well system and a multi-branch well system provided in one embodiment of this application;

[0052] Figure 10 This is a schematic diagram of the initial permeability velocity distribution provided in one embodiment of this application;

[0053] Figure 11 This is a schematic diagram of the initial permeability pressure distribution provided in one embodiment of this application;

[0054] Figure 12 This is a schematic diagram of the structure of a device for determining the geothermal multi-branch well circulation injection and production process provided in another embodiment of this application;

[0055] Figure 13 This is a schematic diagram of the construction process of a digital twin platform for geothermal well analysis provided in another embodiment of this application. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the various embodiments of this application will be described in detail below with reference to the accompanying drawings. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to help readers better understand this application. However, the technical solutions claimed in this application can be implemented even without these technical details and various changes and modifications based on the following embodiments. The division of the various embodiments below is for the convenience of description and should not constitute any limitation on the specific implementation of this application. The various embodiments can be combined with and referenced by each other without contradiction.

[0057] This invention proposes a method for determining the circulating injection and production process of geothermal multi-branch wells. The implementation details of the method for determining the circulating injection and production process of geothermal multi-branch wells in this embodiment are described below. The following content is only for the convenience of understanding and is not necessary for implementing this solution.

[0058] Example 1:

[0059] The method for determining the geothermal multi-branch well circulation injection and production process in this embodiment can be applied to electronic devices with communication, computing, and data storage capabilities. Its specific process can be as follows: Figure 1 As shown, it includes:

[0060] Step 110: Based on the geological data of the target geothermal well, construct a physical simulation experimental platform for the circulating injection and production of the multi-branch well of the geothermal reservoir of the target geothermal well. The well structure, branch layout and geological strata of the physical simulation experimental platform correspond to the actual situation of the target geothermal well in order to simulate the fluid behavior of the target geothermal well under different injection and production processes.

[0061] In this embodiment, a physical simulation experimental platform is used to simulate the fluid behavior of the target geothermal well under different injection and production processes. This provides an experimental environment that is as close as possible to reality, facilitating subsequent digital twin model calibration and verification.

[0062] Specifically, firstly, it is necessary to conduct in-depth analysis of the geological data of the target geothermal well, including key parameters such as geological structure, rock type, permeability, porosity, and temperature distribution. This information will directly affect the design and construction of the physical simulation experimental platform. Based on the geological data analysis, the overall structure and key components of the physical simulation experimental platform are designed. For example, a model capable of simulating the complex geological structure of geothermal reservoirs and a fluid circulation system capable of precisely controlling injection and production flow rates can be designed.

[0063] After the physical simulation experimental platform is structurally constructed, various sensors are installed on it to monitor key parameters such as fluid pressure, temperature, and flow rate in real time. Simultaneously, an efficient data acquisition system can be built to record and store experimental data in real time. Following the completion of the physical simulation experimental platform, comprehensive debugging and verification work can be carried out, including checking the functionality of each component and verifying whether the physical simulation experimental platform can accurately simulate the fluid behavior of the target geothermal well.

[0064] For example, the target geothermal well is located in a complex fracture zone with multiple branch wells. To simulate this situation, a three-dimensional physical simulation experimental platform can be designed, containing a geothermal reservoir model made of a transparent material. The model contains pipes simulating multiple branch wells, connected by tiny channels to simulate a real fracture network. During the experiment, different injection and production processes can be simulated by adjusting the pressure and flow rate of the injected fluid, and the fluid flow within the reservoir can be monitored in real time using sensors.

[0065] Step 120: Based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform, construct a digital twin model of the multi-branch well circulation injection and production of the target geothermal well, wherein the initial state data of the fluid field includes at least one of inlet flow rate, temperature, pressure and flow velocity.

[0066] In this embodiment, the initial state data of the fluid field, such as inlet flow rate, temperature, pressure, and velocity, can be obtained through a physical simulation experimental platform. These data are indispensable input parameters when constructing a digital twin model. A digital twin model is a virtual, highly realistic model used to accurately describe the fluid flow, heat transfer, and deformation behavior of the reservoir.

[0067] Specifically, based on geological data and results from physical simulation experimental platforms, the parameters of the digital twin model are initialized. These parameters include reservoir geometry, rock properties, fluid properties, and boundary conditions. After the digital twin model is constructed, comprehensive verification and debugging can be performed, including checking the model's stability, convergence, and accuracy, as well as verifying whether the model can accurately simulate the fluid behavior of the target geothermal well.

[0068] In practical modeling, the geological structure of the target geothermal well is quite complex, and fluid behavior is influenced by various factors. To construct a digital twin model, commercial software with powerful numerical computing capabilities (such as COMSOL Multiphysics or ANSYS Fluent) can be selected. Then, based on geological data and the results of the physical simulation experimental platform, a three-dimensional geometric model of the target geothermal well is constructed in the software, and corresponding rock properties, fluid properties, and boundary conditions are set. Finally, the fluid flow and temperature distribution in the reservoir are obtained through numerical solutions, and the results are compared and verified with those from the physical simulation experimental platform.

[0069] Step 130: Obtain the experimental results of the physical simulation experimental platform under different injection and production processes, and adjust the initial parameters of the digital twin model using the experimental results until the difference between the prediction results obtained by the physical simulation experimental platform and the digital twin model under the same injection and production process meets the preset error standard, thereby obtaining the adjusted geothermal multi-branch well cyclic injection and production digital twin model.

[0070] In this embodiment, a series of experiments under different injection and extraction processes were conducted on a physical simulation experimental platform, and the changes in key parameters such as fluid pressure, temperature, and flow rate were recorded during the experiments. These experimental results will serve as the basis for calibrating the digital twin model.

[0071] During calibration, sensitivity analysis can be performed on key parameters in the digital twin model to determine which parameters have the greatest impact on the model's prediction results, and these parameters should be adjusted first. Adjustment can be done manually or using optimization algorithms. After each parameter adjustment, the digital twin model needs to be rerun and the results compared with experimental results.

[0072] After each parameter adjustment, it is necessary to evaluate the error between the prediction results of the digital twin model and the experimental results of the physical simulation experimental platform. When the error meets the preset error standard, the digital twin model can be considered to have converged, that is, the difference between its prediction results and experimental results is within an acceptable range, and the digital twin model can be applied to the actual development and management of geothermal wells.

[0073] After verifying the experimental data and simulation results obtained by collecting pressure and flow rate through physical simulation experiments, a complete digital twin model of circulating injection and production in multi-branch wells of thermal reservoirs was established. This model mainly studies the influence of production parameters and structural parameters on injection capacity; the production experiment mainly studies the influence of structural parameters on the system's production capacity; the injection experiment collects the change of injection pressure over time, and the production experiment collects the outlet flow rate.

[0074] For example, five sets of experiments under different injection and production processes were conducted on a physical simulation experimental platform, and the changes in fluid pressure, temperature, and flow rate were recorded. Then, corresponding initial parameters were set in the digital twin model, and the model was run for prediction. By comparing and analyzing the experimental results and the predicted results, it was found that the model's prediction error was relatively large. To calibrate the model, sensitivity analysis was first performed on key parameters such as permeability, porosity, and fluid properties. The results showed that permeability had the greatest impact on the prediction results. Therefore, the permeability parameter was adjusted first, and the model was rerun for prediction. After several iterative adjustments, the model's prediction error finally met the preset error standard. In the verification phase, three more sets of experiments under different injection and production processes were selected for verification. The results showed that the prediction results of the digital twin model were highly consistent with the experimental results and could be used in actual geothermal well development and management.

[0075] Step 140: Simulate the outlet flow rate under different process parameters based on the adjusted geothermal multi-branch well circulating injection and production digital twin model, and determine the target injection and production process according to the outlet flow rate. The process parameters include at least one of the following: injection temperature, injection pressure, number of multi-branch wells, and structure of multi-branch wells.

[0076] In this embodiment, the digital twin platform can be used to analyze in real time the impact of branch well structural parameters (number and length of branch wells) on reducing injection pressure, increasing production output, and the number of branch wells, thereby enabling process parameter optimization and reservoir dynamic tracking and inversion.

[0077] In summary, the method for determining the geothermal multi-branch well circulation injection and production process provided in this embodiment takes the actual geological conditions of geothermal wells as a typical scenario. An experimental model of this geology was built based on field data. Through 3D modeling and computational fluid dynamics, the inherent laws of multi-phase and multi-field coupled motion were explored and a mechanism model was established. An Internet of Things (IoT) system was built for dynamic sensing of fluid transport and other information. Real-time monitoring data was inverted to establish a global spatiotemporal information database. A digital twin method combining experimental and simulation methods for multi-branch circulation injection and production of geothermal reservoirs was constructed. By integrating experimental methods and numerical calculation techniques to build a multi-source data-driven digital twin model, a deeper understanding of the digital twin of multi-phase and multi-field coupled motion of rock strata can be achieved. This method can cover the entire process of "well construction-intelligent production-operation-management" for multi-branch geothermal reservoirs, achieving a comprehensive characterization of the impact on production behavior. It can more efficiently analyze wellbore-reservoir flow and stress state, optimize wellbore process parameters, and dynamically monitor the reservoir, effectively guiding the entire life-cycle production planning.

[0078] In some optional embodiments, the physical simulation experimental platform for the circulating injection and production of the multi-branch well of the target geothermal well based on the geological data of the target geothermal well includes: constructing a main structure based on the actual operating conditions of the target geothermal well, the main structure including an injection well, a production well, multi-branch wells, a simulated reservoir, and a connecting pipeline system; constructing a liquid circulation system for simulating the high-temperature and high-pressure environment of the geothermal well; and installing sensors at target locations on the main structure, the sensors being used to monitor at least one of pressure, flow rate, and temperature, the target locations including at least one of the inlet of the injection well, the outlet of the production well, the interior of the simulated reservoir, and the connection point of the multi-branch wells.

[0079] In this embodiment, the main structure (including injection well, production well, multi-branch well, simulated reservoir, etc.) is built based on the actual operating conditions of the target geothermal well, which can realistically reproduce the injection and production process of the geothermal well. The physical simulation experimental platform can more accurately reflect the actual operating status of the geothermal well, providing a reliable foundation for subsequent experimental research and optimization.

[0080] Specifically, such as Figure 2 The diagram shows the overall structure of the physical simulation experimental platform. The platform is equipped with multiple sensors and a monitoring platform, including the main structure, high-temperature and high-pressure liquid and control modules, simulated wellbores (production wells, radial wells, and injection wells; radial wells are multi-branch wells), and measurement and acquisition modules for monitoring pressure and flow variables.

[0081] In some optional embodiments, the construction of a digital twin model of the geothermal reservoir multi-branch well cyclic injection and production based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform includes: building a fluid dynamics calculation model for the meshed three-dimensional geometric model based on the initial state data of the fluid field and the geophysical characteristic data in the geological data of the target geothermal well, thereby obtaining a digital twin model of the geothermal reservoir multi-branch well cyclic injection and production, wherein the fluid dynamics calculation model is used to map and simulate the injection and production process of the target geothermal well, and the geophysical characteristic data includes at least one of porosity, permeability, and hydrostatic pressure gradient.

[0082] In this embodiment, a three-dimensional geometric model is constructed based on the geological data of the target geothermal well, precisely corresponding to the actual medium and the structure of the target geothermal well. The construction of the three-dimensional geometric model includes, but is not limited to, key parameters such as stratigraphic structure, rock type, and fault distribution. For example, advanced Geographic Information Systems (GIS) and geological modeling software can be used to integrate this complex geological information into a unified three-dimensional model, thereby accurately reproducing the geometric morphology and physical properties of the geothermal reservoir.

[0083] like Figure 3 The diagram shows different multi-branch geothermal well models.

[0084] Meshling the three-dimensional geometric model allows for more accurate simulation of fluid flow behavior in geothermal reservoirs. It captures the impact of local details (such as fractures and pores) on the injection and production process. By numerically simulating fluid flow, heat transfer, and mass transfer processes, the operating status of geothermal wells can be accurately predicted. This provides a more accurate scientific basis for optimizing injection and production processes.

[0085] Based on the meshed 3D geometric model, a fluid dynamics computational model is further constructed. This includes, but is not limited to, the selection of fluid flow equations, the setting of boundary conditions, the determination of initial conditions, and the selection of solution methods. The core of the fluid dynamics computational model is to simulate the flow and heat transfer processes of geothermal fluids in the reservoir, so as to map and simulate the injection and production process of the target geothermal well. Through the digital twin model, the flow state, temperature distribution, and pressure changes of geothermal fluids under different injection and production strategies can be simulated, thereby providing a scientific basis for the optimized design and operation of geothermal wells.

[0086] In some optional embodiments, discretizing the three-dimensional geometric model into a finite number of mesh elements includes: defining local mesh sizes specifically for the geometric features and physical properties of different components of the three-dimensional geometric model; and dividing the three-dimensional geometric model into meshes according to a preset global mesh size and the local mesh sizes.

[0087] In this embodiment, various components (such as formations, faults, and wellbore) in the 3D geometric model are identified, along with their geometric features (such as shape, size, and boundary conditions) and physical properties (such as permeability, porosity, and thermal conductivity). Based on the analysis of different components, local mesh sizes can be defined specifically. The selection of local mesh sizes should consider the accuracy requirements of the simulation and the limitations of computational resources. For example, in areas with low permeability or complex fluid flow, a smaller mesh size may be needed to capture the details of fluid flow; while in areas with high permeability or relatively simple fluid flow, a larger mesh size can be used to improve computational efficiency. Furthermore, for critical components such as the wellbore, a finer mesh may be needed to accurately simulate the fluid flow state within the wellbore.

[0088] By defining local mesh sizes specifically for the geometric features and physical properties of different components of a 3D geometric model, it is possible to ensure that the mesh generation more closely matches the actual situation of the model. This refined mesh generation helps capture the subtle features and physical behaviors of the model, thereby improving the accuracy of simulation and analysis. It also helps reduce unnecessary computation and improve computational efficiency.

[0089] In some optional embodiments, the meshing of the three-dimensional geometric model includes: generating an octree-form volume mesh and a surface mesh; deleting the octree-form volume mesh and retaining the octree-form surface mesh; and regenerating the volume mesh based on the octree-form surface mesh using the Delaunay triangulation method.

[0090] In this embodiment, as Figure 4 The diagram shows the multi-branch radial well mesh generation. Generating octree-form volume and surface meshes allows for efficient 3D space partitioning. Deleting the octree-form volume mesh while retaining the surface mesh provides a more accurate representation of the surface features of the 3D geometric model. Based on the octree-form surface mesh, regenerating the volume mesh using the Delaunay triangulation method ensures more regular triangle shapes in the generated volume mesh, reduces the number of distorted triangles, and improves mesh quality.

[0091] In some optional embodiments, the step of building a fluid dynamics calculation model for the meshed three-dimensional geometric model based on the initial state data of the fluid field and the geophysical characteristic data in the geological data of the target geothermal well includes: inputting the geophysical characteristic data and the initial state data of the fluid field into computational fluid dynamics software, setting pressure inlet and pressure outlet, adopting a laminar or turbulent flow model, using the wall boundary conditions of the three-dimensional geometric model as numerical simulation boundary conditions, and constructing the fluid dynamics calculation model.

[0092] Specifically, Computational Fluid Dynamics (CFD) is the analysis of systems involving physical phenomena such as fluid flow and heat conduction through computer numerical calculations and graphical displays. The basic idea of ​​CFD can be summarized as follows: replacing the continuous physical field of physical quantities, such as velocity and pressure fields, in the time and spatial domains with a set of variable values ​​at a finite number of discrete points; establishing a system of algebraic equations relating the field variables at these discrete points using certain principles and methods; and then solving the system of algebraic equations to obtain approximate values ​​of the field variables.

[0093] CFD calculations all follow the basic conservation equations of fluid mechanics, including the mass conservation equation, momentum conservation equation, energy conservation equation, and composition conservation equation.

[0094] In this embodiment, the resistance characteristics in the porous medium model are treated according to the following formula:

[0095]

[0096] Where ΔP is the pressure difference; D is the thickness in the flow direction (i.e., the thickness of the porous medium region); v is the flow velocity; μ is the dynamic viscosity of the fluid; ρ is the density of the fluid; α is the permeability; and C2 is the inertial drag coefficient. Since the flow velocity is very small in all operating conditions of this experimental setup, the inertial drag can be ignored, i.e., C2 = 0.

[0097] The specific settings parameters are as follows:

[0098] Turbulence model and physical properties:

[0099] 1) Use the κ-ε turbulence model;

[0100] 2) Select the injection medium, dynamic viscosity, and density;

[0101] 3) The cement rock sample area in the simulated reservoir is set as a porous medium area, and the porosity and permeability are set.

[0102] Boundary conditions:

[0103] like Figure 5 The diagram shows the boundary condition settings. The reinjection well is set as the mass flow inlet, with the flow rate determined based on experimental results from the physical simulation platform. The side of the thermal storage area is set as the pressure outlet, with values ​​varying according to the z-coordinate: ρ × g × h (where ρ is the density of water, g is the gravitational acceleration, and g is the formation depth). The others are wall boundary conditions.

[0104] In this embodiment, based on experimental data obtained from a physical simulation experimental platform for the circulating injection and production of a multi-branch well in the geothermal reservoir of the target geothermal well, the initial state of the fluid field in the three-dimensional geometric model is set, including inlet flow rate, temperature, pressure, and velocity. This experimental data reflects the actual operating state of the geothermal well, making the constructed fluid dynamics calculation model more closely resemble reality and enhancing its practicality. The geophysical characteristic data and the initial state data of the fluid field in the three-dimensional geometric model are input into computational fluid dynamics software, utilizing the software's efficient computing capabilities for numerical simulation. Simultaneously, by setting pressure inlet and outlet, and employing laminar or turbulent flow models, the flow state of the fluid in the three-dimensional geometric model can be obtained more quickly, improving computational efficiency.

[0105] In some optional embodiments, the method further includes discretizing the fluid dynamics calculation model using a second-order upwind scheme. In this embodiment, under complex flow conditions, such as turbulence and vortices, the fluid's motion often exhibits high nonlinearity and instability. The second-order upwind scheme can better adapt to these complex flow conditions and provide more accurate simulation results.

[0106] Example 2:

[0107] Fluid transport patterns are a core scientific issue in geothermal development and a crucial link in coordinating design and extraction. Traditional monitoring methods cannot provide a comprehensive and intuitive view of the three-dimensional real-time movement of underground rock strata and fluids, necessitating a clear understanding of fluid transport during geothermal extraction to guide engineering practice. Based on the above embodiments, this embodiment provides a practical application scenario for determining a method for the circulation injection and production process in multi-branch geothermal wells.

[0108] This embodiment addresses the current status and problems of geothermal energy branch well development in my country. It integrates computational fluid dynamics, seepage mechanics, rock mechanics, experimental techniques, data monitoring, and big data to construct a digital twin platform for geothermal well analysis. Based on this digital twin platform, wellbore-reservoir flow and stress state analysis are performed, enabling functions such as wellbore process parameter optimization, reservoir dynamic monitoring, and inversion. The overall construction process is as follows: Figure 13 As shown, the specific process is as follows:

[0109] A method for constructing a digital twin platform for enhancing geothermal well injection efficiency includes:

[0110] Step 210: Design and build a physical simulation experimental platform for the circulation injection and production of multi-branch wells in thermal reservoirs. This platform can verify the accuracy of numerical simulation and construct digital twins. The experimental device is equipped with multiple platforms and sensor monitoring platforms, including the main structure, high-temperature and high-pressure liquid and control module, simulated wellbore, and measurement and acquisition module to monitor pressure and flow variables.

[0111] Step 220: Based on the geological data and other conditions of the actual geothermal well, establish a digital twin theoretical model of the geothermal well. The specific implementation details are as follows:

[0112] Step 221: A three-dimensional geometric model identical to the actual medium and geothermal well is created using 3D software such as PROE, and meshed for preliminary CFD calculations. The three-dimensional geometric model is as follows: Figure 3 As shown.

[0113] Step 222: Mesh the multi-branch radial wells in the 3D geometric model:

[0114] Specifically, before meshing, upper and lower limits for the mesh size must be set. The basic mesh size is set to 4mm, and the maximum volume mesh size is set to 20mm. Curvature-based adaptive meshing is activated, and the volume mesh growth rate is set to 1.1. Local dimensions for different components are defined. The mesh size for the wall surface of the Φ2mm hole attachment in the branch well is controlled at 0.4mm to analyze the flow phenomena of the small hole attachment. To generate a uniformly transitioned volume mesh, an octree-type volume mesh and surface mesh are first generated. Then, the octree-type volume mesh is deleted, and a uniformly transitioned mesh is regenerated based on the octree-type surface mesh using the Delaunay method (Delaunay triangulation method).

[0115] Step 223: Obtain geological data of the experimental area and store it in the database:

[0116] The basic data for the model are obtained by collecting geological data, porosity, permeability, hydrostatic pressure gradient and other parameters from the experimental area; based on the collected data, such as inlet flow rate, temperature, pressure and flow velocity, a digital twin experimental research platform for geothermal wells is constructed.

[0117] Step 224, Building the CFD calculation model for the geothermal well:

[0118] The data from step 223 is input into the CFD computational fluid dynamics software. The top of the injection well is set as the pressure or flow / velocity inlet, and the top of the cement rock sample area is set as the pressure outlet. A laminar / turbulent flow model is used, and the other boundary conditions are wall boundary conditions as numerical simulation boundary conditions to construct a simulation digital twin model.

[0119] To obtain more accurate numerical results, a second-order numerical format is adopted to reduce numerical errors. Initialization is selected from the air inlet or all regions, and the number of iteration steps is determined by the residual and the computation time.

[0120] CFD calculations all follow the basic conservation equations of fluid mechanics, including the mass conservation equation, momentum conservation equation, energy conservation equation, and composition conservation equation.

[0121] Mass conservation equation (continuity equation):

[0122]

[0123] Momentum conservation equation (Navier-Stokes equation):

[0124]

[0125] In the porous media model, the resistance characteristics are treated according to the following formula:

[0126]

[0127] Where ΔP is the pressure difference; D is the thickness in the flow direction (i.e., the thickness of the porous medium region); v is the flow velocity; μ is the dynamic viscosity of the fluid; ρ is the density of the fluid; α is the permeability; and C2 is the inertial drag coefficient. Since the flow velocity is very small in all operating conditions of this experimental setup, the inertial drag can be ignored, i.e., C2 = 0.

[0128] The specific settings parameters are as follows:

[0129] Turbulence model and physical properties:

[0130] 1) Use the κ-ε turbulence model;

[0131] 2) The injection medium is water at 25℃, with a dynamic viscosity of 8.8871E-4 Pa·s and a density of 997.561 kg / m³. 3 ;

[0132] 3) The cement rock sample region in the simulated reservoir was set as a porous medium region with a porosity of 0.2 and a permeability of 530 mD.

[0133] Boundary conditions:

[0134] like Figure 5 The diagram shows the boundary condition settings. The reinjection well is set as the mass flow inlet, with the flow rate determined based on experimental results from the physical simulation platform. The side of the thermal storage area is set as the pressure outlet, with values ​​varying according to the z-coordinate: ρ × g × h (where ρ is the density of water, g is the gravitational acceleration, and g is the formation depth). The others are wall boundary conditions.

[0135] Step S230: Through the verification of the geothermal multi-branch well circulation injection and production physical simulation experimental platform, analyze the experimental results of different process parameters of geothermal multi-branch well injection and production, and use this as a basis to verify the accuracy of the digital twin platform.

[0136] After verifying the experimental data and simulation results obtained by collecting pressure and flow rate through physical simulation experiments, a complete digital twin model of circulating injection and production in multi-branch wells of thermal reservoirs was established. This model mainly studies the influence of production parameters and structural parameters on injection capacity; the production experiment mainly studies the influence of structural parameters on the system's production capacity; the injection experiment collects the change of injection pressure over time, and the production experiment collects the outlet flow rate.

[0137] Specifically, the results that can be obtained through the digital twin platform are as follows:

[0138] 1. For example Figure 6 The diagram shows the variation of injection pressure under different processes. The injection pressure can be divided into three stages: decreasing, transition, and stabilizing. As time progresses, the system injection pressure decreases; as the injection temperature increases, the injection pressure increases: it is speculated that lower temperature injection induces greater thermal stress (tension), leading to decreased permeability; the injection pressure increases with the increase of injection flow rate.

[0139] 2. For example Figure 7 The diagram shows the effect of different numbers of branch wells on wellhead discharge. During injection, increasing the number of branch wells from 2 to 6 resulted in a 2.98 MPa decrease in injection pressure; in the production experiment, as the number of branch wells gradually increased, the system's wellhead discharge increased by 60%.

[0140] 3. For example Figure 8 The diagram shows the effect of branch well length variation on wellhead discharge rate. During injection, increasing branch well length resulted in a 2.4 MPa decrease in injection pressure; during production experiments, increasing branch well length resulted in a 28% increase in wellhead discharge rate.

[0141] 4. For example Figure 9 The diagram shows a comparison of the injection and production effects between a single-well system and a multi-branch well system. During injection, compared to a single-well open system, the water absorption index of the multi-branch well increased by 1.6 L / MPa (1.6 times); in the production experiment, the outlet discharge of the multi-branch well increased by 90%. Therefore, multi-branch wells can significantly improve the system's injection and production capacity.

[0142] 5. Through the digital twin platform, the structural parameters of branch wells (number and length of branch wells) can be analyzed in real time to reduce injection pressure, increase production output and the degree of influence of the number of branch wells, so as to realize the optimization of process parameters and dynamic tracking and inversion of reservoir.

[0143] like Figure 10 The diagram shown is a schematic representation of the initial permeability velocity distribution.

[0144] like Figure 11 The diagram shown is a schematic representation of the initial permeability pressure distribution.

[0145] In this embodiment, taking the actual geological conditions of a geothermal field as a typical scenario, an experimental model was built based on field data. Through 3D modeling and computational fluid dynamics, the inherent laws of multiphase and multi-field coupled motion were explored and a mechanistic model was established. An Internet of Things (IoT) system was built for dynamic sensing of fluid transport and other information. Real-time monitoring data was retrieved to establish a global spatiotemporal information database. A digital twin method combining multi-branch cycle injection and production experiments and simulations was developed for the geothermal reservoir. By integrating experimental methods and numerical calculation techniques, a multi-source data-driven digital twin was constructed, enabling a deeper understanding of the digital twin of multiphase and multi-field coupled motions of rock strata. The digital twin platform in this embodiment realizes a complete digital intelligent analysis and control process from indoor experiments to model calculations to field implementation. Through multiple interface designs, it seamlessly connects the coupled calculations of multiple phases and models, and uses information transmission technology to connect the workflow and data flow from scheme design to on-site implementation. It realizes real-time dynamic data transmission, real-time analysis and adjustment, and can cover the entire process of "well construction-intelligent mining-operation-management" of multi-branch wells in geothermal reservoirs. It can achieve a comprehensive characterization of the impact on mining behavior, effectively guide the whole life cycle mining planning, and safely and efficiently verify the whole process monitoring and analysis of geothermal extraction and irrigation under different geological conditions.

[0146] Example 3:

[0147] Another embodiment of this application relates to a device for determining the geothermal multi-branch well circulating injection and production process. The implementation details of this device are described below. The following details are for ease of understanding and are not essential for implementing this solution. A schematic diagram of the device for determining the geothermal multi-branch well circulating injection and production process in this embodiment can be seen as follows: Figure 12 As shown, it includes a physical simulation experimental platform construction module 1210, a digital twin model construction module 1220, a digital twin model adjustment module 1230, and an injection and extraction process determination module 1240.

[0148] The physical simulation experimental platform construction module 1210 is used to construct a physical simulation experimental platform for the circulating injection and production of the multi-branch well of the thermal reservoir of the target geothermal well based on the geological data of the target geothermal well. The well structure, branch layout and geological strata of the physical simulation experimental platform correspond to the actual situation of the target geothermal well in order to simulate the fluid behavior of the target geothermal well under different injection and production processes.

[0149] The digital twin model construction module 1220 is used to construct a digital twin model of the thermal reservoir multi-branch well circulation injection and production of the target geothermal well based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform. The initial state data of the fluid field includes at least one of inlet flow rate, temperature, pressure and flow velocity.

[0150] The digital twin model adjustment module 1230 is used to obtain the experimental results of the physical simulation experimental platform under different injection and production processes, and to adjust the initial parameters of the digital twin model using the experimental results until the difference between the prediction results obtained by the physical simulation experimental platform and the digital twin model under the same injection and production process meets the preset error standard, thereby obtaining the adjusted digital twin model of the geothermal multi-branch well cyclic injection and production.

[0151] The injection and production process determination module 1240 is used to simulate the outlet flow rate under different process parameters based on the adjusted geothermal multi-branch well cyclic injection and production digital twin model, and determine the target injection and production process according to the outlet flow rate. The process parameters include at least one of the following: injection temperature, injection pressure, number of multi-branch wells, and structure of multi-branch wells.

[0152] It is worth mentioning that all modules involved in this embodiment are logical modules. In practical applications, a logical unit can be a physical unit, a part of a physical unit, or a combination of multiple physical units. Furthermore, to highlight the innovative aspects of this application, this embodiment does not introduce units that are not closely related to solving the technical problems proposed in this application; however, this does not mean that other units are absent in this embodiment.

[0153] In some optional embodiments, the physical simulation experimental platform construction module includes:

[0154] The main structure building unit is used to build the main structure based on the actual working conditions of the target geothermal well. The main structure includes an injection well, a production well, a multi-branch well, a simulated reservoir, and a connecting pipeline system.

[0155] A liquid circulation system construction unit is used to build a liquid circulation system for simulating the high temperature and high pressure environment of a geothermal well. Sensors are installed at target locations on the main structure. The sensors are used to monitor at least one of pressure, flow rate, and temperature. The target locations include at least one of the inlet of the injection well, the outlet of the production well, the interior of the simulated reservoir, and the connection point of the multi-branch well.

[0156] In some optional embodiments, the digital twin model building module includes:

[0157] The three-dimensional model construction unit is used to construct a three-dimensional geometric model corresponding to the actual medium and the target geothermal well based on the geological data of the target geothermal well.

[0158] Mesh building units are used to discretize the three-dimensional geometric model into a finite number of mesh units;

[0159] The fluid dynamics calculation model construction unit is used to build a fluid dynamics calculation model for the gridded three-dimensional geometric model based on the initial state data of the fluid field and the geophysical characteristic data in the geological data of the target geothermal well, so as to obtain a digital twin model of the multi-branch well cyclic injection and production of the geothermal reservoir of the target geothermal well. The fluid dynamics calculation model is used to map and simulate the injection and production process of the target geothermal well, and the geophysical characteristic data includes at least one of porosity, permeability and hydrostatic pressure gradient.

[0160] In some optional embodiments, the mesh building unit includes:

[0161] Size definition sub-units are used to define local mesh sizes specifically for the geometric features and physical properties of different components of the three-dimensional geometric model;

[0162] The meshing sub-unit is used to mesh the three-dimensional geometric model according to the preset global mesh size and the local mesh size.

[0163] In some optional embodiments, the mesh building unit includes:

[0164] Mesh generation unit, used to generate octree-style volume meshes and surface meshes;

[0165] A mesh deletion unit is used to delete the octree-form volume mesh while retaining the octree-form surface mesh.

[0166] A mesh reconstruction unit is used to regenerate a volume mesh based on the surface mesh in the form of an octree using the Deloitte triangulation method.

[0167] In some optional embodiments, the fluid dynamics calculation model building unit includes:

[0168] The fluid dynamics calculation model simulation subunit is used to input the geophysical property data and the initial state data of the fluid field into the computational fluid dynamics software, set the pressure inlet and pressure outlet, adopt a laminar or turbulent flow model, and use the wall boundary conditions of the three-dimensional geometric model as numerical simulation boundary conditions to construct the fluid dynamics calculation model.

[0169] In some optional embodiments, the fluid dynamics calculation model building unit further includes:

[0170] The second-order upwind format subunit is used to discretize the fluid dynamics calculation model using a second-order upwind format.

[0171] Example 4:

[0172] Another embodiment of this application relates to an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for determining the geothermal multi-branch well cyclic injection and production process in the above embodiments.

[0173] The memory and processor are connected via a bus, which can include any number of interconnecting buses and bridges, connecting various circuits of one or more processors and memories. The bus can also connect various other circuits, such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and will not be described further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be a single element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices over a transmission medium. Data processed by the processor is transmitted over the wireless medium via an antenna, which further receives data and transmits it to the processor.

[0174] The processor manages the bus and general processing, and also provides various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory is used to store data used by the processor during operation.

[0175] Example 5:

[0176] Another embodiment of this application relates to a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the above-described embodiment of the method for determining the geothermal multi-branch well circulating injection and production process.

[0177] That is, those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0178] Those skilled in the art will understand that the above embodiments are specific embodiments for implementing this application, and in practical applications, various changes can be made to them in form and detail without departing from the spirit and scope of this application.

Claims

1. A method for determining the circulating injection and production process of a multi-branch geothermal well, characterized in that, include: Based on the geological data of the target geothermal well, a physical simulation experimental platform for the circulating injection and production of the target geothermal well's multi-branch well is constructed. The wellbore structure, branch layout, and geological strata of the physical simulation experimental platform correspond to the actual situation of the target geothermal well, so as to simulate the fluid behavior of the target geothermal well under different injection and production processes. Based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform, a digital twin model of the circulating injection and production of the multi-branch well of the thermal reservoir of the target geothermal well is constructed. The initial state data of the fluid field includes at least one of inlet flow rate, temperature, pressure and flow velocity. The experimental results of the physical simulation experimental platform under different injection and production processes are obtained. The initial parameters of the digital twin model are adjusted using the experimental results until the difference between the prediction results obtained by the physical simulation experimental platform and the digital twin model under the same injection and production process meets the preset error standard, thus obtaining the adjusted digital twin model of the geothermal multi-branch well cyclic injection and production. Based on the adjusted geothermal multi-branch well circulating injection and production digital twin model, the outlet flow rate under different process parameters is simulated, and the target injection and production process is determined according to the outlet flow rate. The process parameters include at least one of the following: injection temperature, injection pressure, number of multi-branch wells, and structure of multi-branch wells.

2. The method for determining the geothermal multi-branch well circulation injection and production process according to claim 1, characterized in that, The physical simulation experimental platform for the circulating injection and production of the target geothermal well's multi-branch well, constructed based on the geological data of the target geothermal well, includes: Based on the actual working conditions of the target geothermal well, a main structure is constructed, which includes an injection well, a production well, a multi-branch well, a simulated reservoir, and a connecting pipeline system. A liquid circulation system is constructed to simulate the high-temperature and high-pressure environment of a geothermal well. Sensors are installed at target locations on the main structure to monitor at least one of pressure, flow rate, and temperature. The target locations include at least one of the inlet of the injection well, the outlet of the production well, the interior of the simulated reservoir, and the connection point of the multi-branch wells.

3. The method for determining the geothermal multi-branch well circulation injection and production process according to claim 1, characterized in that, Based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform, a digital twin model of the multi-branch well circulation injection and production of the target geothermal well is constructed, including: Based on the geological data of the target geothermal well, a three-dimensional geometric model corresponding to the actual medium and the target geothermal well is constructed. The three-dimensional geometric model is discretized into a finite number of mesh elements; Based on the initial state data of the fluid field and the geophysical characteristic data in the geological data of the target geothermal well, a fluid dynamics calculation model is built for the gridded three-dimensional geometric model to obtain a digital twin model of the multi-branch well cyclic injection and production of the target geothermal well. The fluid dynamics calculation model is used to map and simulate the injection and production process of the target geothermal well. The geophysical characteristic data includes at least one of porosity, permeability and hydrostatic pressure gradient.

4. The method for determining the geothermal multi-branch well circulation injection and production process according to claim 3, characterized in that, Discretizing the three-dimensional geometric model into a finite number of mesh elements includes: For the geometric features and physical properties of different components of the three-dimensional geometric model, local mesh sizes are defined accordingly; The three-dimensional geometric model is meshed according to the preset global mesh size and the local mesh size.

5. The method for determining the geothermal multi-branch well circulation injection and production process according to claim 3, characterized in that, Discretizing the three-dimensional geometric model into a finite number of mesh elements includes: Generate octree-style volume and surface meshes; Delete the octree-form volume mesh, and retain the octree-form surface mesh; Based on the octree-form surface mesh, the volume mesh is regenerated using the Deloitte triangulation method.

6. The method for determining the geothermal multi-branch well circulation injection and production process according to claim 3, characterized in that, The initial state data of the fluid field and the geophysical characteristic data from the geological data of the target geothermal well are used to build a fluid dynamics calculation model for the meshed three-dimensional geometric model, including: The geophysical property data and the initial state data of the fluid field are input into computational fluid dynamics software. Pressure inlet and pressure outlet are set, laminar or turbulent flow models are adopted, and the wall boundary conditions of the three-dimensional geometric model are used as numerical simulation boundary conditions to construct the fluid dynamics calculation model.

7. The method for determining the geothermal multi-branch well circulation injection and production process according to claim 6, characterized in that, Also includes: The fluid dynamics calculation model is discretized using a second-order upwind scheme.

8. A device for determining the circulating injection and production process of a geothermal multi-branch well, characterized in that, include: The physical simulation experimental platform construction module is used to construct a physical simulation experimental platform for the circulating injection and production of the multi-branch well of the target geothermal well based on the geological data of the target geothermal well. The well structure, branch layout and geological strata of the physical simulation experimental platform correspond to the actual situation of the target geothermal well in order to simulate the fluid behavior of the target geothermal well under different injection and production processes. The digital twin model construction module is used to construct a digital twin model of the thermal reservoir multi-branch well circulation injection and production of the target geothermal well based on the geological data of the target geothermal well and the initial state data of the fluid field obtained from the physical simulation experimental platform. The initial state data of the fluid field includes at least one of inlet flow rate, temperature, pressure and flow velocity. The digital twin model adjustment module is used to obtain the experimental results of the physical simulation experimental platform under different injection and production processes, and to adjust the initial parameters of the digital twin model using the experimental results until the difference between the prediction results obtained by the physical simulation experimental platform and the digital twin model under the same injection and production process meets the preset error standard, thereby obtaining the adjusted digital twin model of the geothermal multi-branch well cyclic injection and production. The injection and production process determination module is used to simulate the outlet flow rate under different process parameters based on the adjusted geothermal multi-branch well cyclic injection and production digital twin model, and determine the target injection and production process according to the outlet flow rate. The process parameters include at least one of the following: injection temperature, injection pressure, number of multi-branch wells, and structure of multi-branch wells.

9. An electronic device, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method for determining the geothermal multi-branch well cyclic injection and production process as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for determining the geothermal multi-branch well circulation injection and production process as described in any one of claims 1 to 7.

Images