Hydrothermal type geothermal high efficient mining irrigation intelligent operation maintenance system

Abstract

This application discloses an intelligent operation and maintenance system for efficient geothermal extraction and irrigation, comprising: a data processing module for performing precise digital mapping of the geothermal reservoir to the ground equipment in multiple dimensions and multiple physical fields, obtaining the dynamic changes of the geothermal reservoir and the ground equipment under different operating conditions; the data processing module includes a geothermal reservoir geological model, a THMC coupled simulation model, and a ground facility system model, wherein the geothermal reservoir geological model is used to characterize the three-dimensional spatial structure and initial physical property parameter distribution of the geothermal reservoir, the THMC coupled simulation model is used to simulate fluid flow, heat transfer, rock mechanics and chemical reaction processes based on the geological model, and the ground facility system model is used to simulate the working state of the ground equipment from the wellhead of the production well to the wellhead of the reinjection well; and an execution module for driving the variable frequency pump to perform stepless speed regulation to change the total flow and pressure of the system, and driving the regulating valve to adjust the opening to achieve flow distribution and pressure control, thereby forming an intelligent control loop.

Description

Technical Field

[0001] This application relates to an intelligent operation and maintenance system for efficient geothermal extraction and irrigation, belonging to the field of geothermal development technology. Background Technology

[0002] In the current development and utilization of hydrothermal geothermal energy, existing technologies face numerous severe challenges. The lack of a complete and accurate model system makes it difficult to achieve precise digital mapping of multi-dimensional, multi-physics fields from geothermal reservoirs to surface equipment. Existing models fail to fully consider the complex coupling relationships between fluid flow, heat transfer, rock mechanics, and chemical reactions, resulting in an inability to accurately simulate the dynamic changes of the system under different operating conditions. Furthermore, data exchange between models is severely hampered, and real-time data is not effectively used for dynamic calibration of model parameters, leading to significant deviations between digital mapping results and the actual system state. In terms of control, there is a lack of intelligent control strategies, relying primarily on manual experience. This makes it impossible to flexibly adjust operating parameters based on the real-time system status, hindering the construction of efficient and stable intelligent control loops. These problems significantly restrict the improvement of efficiency, the guarantee of operational stability, and the optimization of economic benefits in the development and utilization of hydrothermal geothermal energy. Summary of the Invention

[0003] According to one aspect of this application, a high-efficiency intelligent operation and maintenance system for hydrothermal geothermal extraction and irrigation is provided, which improves the efficiency of hydrothermal geothermal development and utilization.

[0004] A hydrothermal geothermal high-efficiency extraction and irrigation intelligent operation and maintenance system, characterized in that it includes: The data acquisition module is used to collect multi-source data that characterizes the geothermal reservoir and the operating status of ground equipment in real time; The data processing module is used to perform multi-dimensional and multi-physical field precise digital mapping from the geothermal reservoir to the ground equipment, and obtain the dynamic change process of the geothermal reservoir and the ground equipment under different operating conditions. The data processing module includes a geothermal reservoir geological model, a THMC coupled simulation model, and a surface facility system model. The geothermal reservoir geological model is used to characterize the three-dimensional spatial structure and initial physical property parameter distribution of the geothermal reservoir. The THMC coupled simulation model is used to simulate fluid flow, heat transfer, rock mechanics, and chemical reaction processes based on the geological model. The surface facility system model is used to simulate the working status of surface equipment from the wellhead of the production well to the wellhead of the reinjection well. The THMC coupled simulation model is bidirectionally coupled with the ground facility system model, and the real-time data of the data acquisition module is fused through a data assimilation algorithm to dynamically calibrate the model parameters, so that the digital mapping process is close to the real system state. The execution module includes a variable frequency pump, a regulating valve, and a control unit. The control unit receives the optimized control commands issued by the data processing module, converts the commands into control signals, drives the variable frequency pump to perform stepless speed regulation to change the total flow and pressure of the system, and simultaneously drives the regulating valve to adjust the opening to achieve flow distribution and pressure control, thereby forming an intelligent control loop.

[0005] Furthermore, it also includes: The early warning and optimization module is used to perform predictive simulations based on the calibrated data processing module, realize early warning of risks, solve for the optimal combination of operating parameters, and generate optimized control commands.

[0006] Furthermore, the construction of the geological model of the thermal reservoir includes: Acquire geological exploration data, well logging data, and core test data; The configuration is set to generate a three-dimensional spatial grid structure for the target thermal reservoir, and each grid cell is assigned initial physical property parameters, including the spatial distribution of porosity, permeability, initial temperature field, and initial pressure field. The thermal reservoir geological model provides the computational domain and initial conditions for the THMC coupled simulation model, and its physical property parameter field provides the main calibration object for the data assimilation algorithm.

[0007] Furthermore, the THMC coupled simulation model is configured to solve a set of partial differential equations involving thermo-hydraulic-mechanical-chemical multiphysics fields to simulate the flow of underground fluids, heat transfer, changes in rock stress, and the process of chemical reactions. The THMC coupled simulation model exchanges data bidirectionally with the surface facility system model: it receives wellhead flow or pressure commands from the surface facility system model as boundary conditions for its simulation, and feeds back the bottom hole pressure and temperature parameters obtained from the simulation calculation to the surface facility system model.

[0008] Furthermore, the ground facility system model is configured to simulate the working status of all ground equipment from the production wellhead, through the pipeline network and heat exchanger, to the reinjection wellhead; The surface facility system model includes a wellbore flow unit, a pipeline pressure drop and heat loss unit, a heat exchanger efficiency unit, and a pump energy consumption unit. The bottom hole parameters output by the THMC coupled simulation model are used as the input of the wellbore flow unit, while the wellhead flow rate and pressure parameters calculated according to the optimization instructions are used as the boundary conditions of the THMC coupled simulation model. The wellhead parameters output by the wellbore unit serve as the input to the pipeline pressure drop and heat loss unit, while the fluid parameters output by the pipeline pressure drop and heat loss unit serve as the input to the heat exchanger efficiency unit. The utilized fluid state parameters are then transmitted to the wellbore flow unit and the pipeline pressure drop and heat loss unit on the reinjection side. Through iterative calculations, the flow rate into each node is ensured to be equal to the outflow rate, and the pressure loss is closed, thereby solving the stable working state of the entire surface system under specific operating conditions.

[0009] Furthermore, the THMC coupled simulation model integrates early warning judgment logic, which is configured as follows: When the simulated and predicted temperature of the production well is lower than a preset threshold, a thermal breakthrough warning is triggered. When the simulated decrease in permeability or increase in pressure in the near-wellbore zone of the reinjection well exceeds the critical value, a reinjection blockage warning is triggered.

[0010] Furthermore, the ground facility system model integrates control logic, which is configured as follows: With the total energy consumption or unit heat cost of the system as the optimization target, the macroscopic irrigation and drainage requirements are transformed into a combination of executable control parameters, which includes the speed setting value of the variable frequency pump and the opening setting value of the regulating valve.

[0011] Furthermore, the execution of the control unit includes: Receives real-time measurement of actual pressure P from a pressure transmitter installed at the wellhead of the production well. actual ; Calculate the pressure deviation: e(t) = P set -P actual ; If P actual Below P set If the pressure is insufficient, the flow rate needs to be increased. In this case, the speed of the variable frequency pump should be increased and / or the regulating valve should be opened wider.

[0012] If P actual Higher than P set If the pressure is too high, the flow rate needs to be reduced. In this case, reduce the speed of the variable frequency pump and / or close the regulating valve.

[0013] Among them, the adjustment of the variable frequency pump is the first priority; The regulation of the control valve is the second priority.

[0014] The beneficial effects that this application can produce include: The hydrothermal geothermal high-efficiency extraction and irrigation intelligent operation and maintenance system provided in this application acquires multi-source data in real time through a data acquisition module, providing rich information for a comprehensive understanding of the system's operating status. The data processing module constructs a multi-dimensional model and performs bidirectional data coupling and real-time data fusion, enabling precise digital mapping between the geothermal reservoir and surface equipment. Dynamic calibration makes the model closer to the real system. The execution module, based on optimized control commands, implements an intelligent control loop through variable frequency pumps and regulating valves, allowing for flexible changes in system flow and pressure, precise allocation of flow and control pressure, effectively improving the efficiency of hydrothermal geothermal development and utilization, ensuring stable system operation, and reducing operation and maintenance costs. Attached Figure Description

[0015] Figure 1 This is a system block diagram of a hydrothermal geothermal high-efficiency intelligent operation and maintenance system for extraction and irrigation, according to one embodiment of this application. Detailed Implementation

[0016] The present application is described in detail below with reference to the embodiments, but the present application is not limited to these embodiments.

[0017] See Figure 1 A hydrothermal geothermal high-efficiency extraction and irrigation intelligent operation and maintenance system, characterized in that it includes: The data acquisition module is used to collect multi-source data that characterizes the geothermal reservoir and the operating status of ground equipment in real time. The multi-source data includes temperature, pressure, flow rate, vibration and electrical energy parameters. The data processing module is used to perform multi-dimensional and multi-physical field precise digital mapping from the geothermal reservoir to the ground equipment, and obtain the dynamic change process of the geothermal reservoir and the ground equipment under different operating conditions. The data processing module includes a geothermal reservoir geological model, a THMC coupled simulation model, and a surface facility system model. The geothermal reservoir geological model is used to characterize the three-dimensional spatial structure and initial physical property parameter distribution of the geothermal reservoir. The THMC coupled simulation model is used to simulate fluid flow, heat transfer, rock mechanics, and chemical reaction processes based on the geological model. The surface facility system model is used to simulate the working status of surface equipment from the wellhead of the production well to the wellhead of the reinjection well. The THMC coupled simulation model is bidirectionally coupled with the ground facility system model, and the real-time data of the data acquisition module is fused through a data assimilation algorithm to dynamically calibrate the model parameters, so that the digital mapping process is close to the real system state. The execution module includes a variable frequency pump, a regulating valve, and a control unit. The control unit receives the optimized control commands issued by the data processing module, converts the commands into control signals, drives the variable frequency pump to perform stepless speed regulation to change the total flow and pressure of the system, and simultaneously drives the regulating valve to adjust the opening to achieve flow distribution and pressure control, thereby forming an intelligent control loop.

[0018] Specifically, the data acquisition module is responsible for real-time monitoring of the geothermal reservoir and surface equipment operation status. The monitored data types are comprehensive, covering temperature (including temperatures at different depths of the reservoir, wellhead fluid temperature, and equipment operating temperature); pressure (including reservoir pressure, wellhead inlet and outlet pressure, and pipeline pressure); flow rate (including production well output, reinjection well reinjection volume, and pipeline fluid flow); vibration (pump vibration, pipeline vibration, vibration of key equipment components); and electrical parameters (including pump power consumption, inverter power, and total system energy consumption). This achieves comprehensive monitoring of key indicators throughout the entire geothermal extraction and injection process. High-precision sensors and industrial-grade data acquisition terminals are used, and the sampling frequency can be dynamically adjusted according to operating conditions to ensure data timeliness and provide real-time data support for subsequent model calibration and control decisions. The acquired data is stably uploaded to the system platform through multiple transmission methods such as industrial Ethernet, 4G / 5G wireless communication, or LoRa low-power wide area network. It also features data interruption resume and abnormal reconnection functions to avoid data loss due to network fluctuations. The data processing module is used to achieve accurate digital mapping between geothermal reservoirs and ground equipment. The geothermal reservoir geological model serves as the foundation of the entire simulation system. This model is constructed based on geological exploration data, such as drilling core analysis, well logging data, and seismic exploration data. It can accurately characterize the three-dimensional spatial structure of geothermal reservoirs, including the spatial distribution of reservoir thickness, porosity, and permeability, as well as initial physical property parameters, such as rock thermal conductivity, specific heat capacity, fluid density, and viscosity. This provides realistic geological environment boundary conditions for subsequent multiphysics coupling simulations. The THMC (Thermal-Hydraulic-Mechanical-Chemical) coupled simulation model is the core of reservoir dynamic simulation. Based on the geological model of the geothermal reservoir, it can simultaneously simulate key processes within the reservoir during geothermal development. These processes include: 1) Fluid flow processes, simulating the seepage patterns of groundwater in the reservoir's porous media, including changes in flow velocity and direction with the pressure difference between production and irrigation; 2) Heat transfer processes, calculating the heat exchange between reservoir rocks and fluids, and the migration patterns of heat with fluid flow, predicting dynamic changes in the reservoir temperature field; 3) Rock mechanics processes, analyzing the rock stress distribution and deformation caused by changes in reservoir pressure during production and irrigation, and assessing reservoir stability; and 4) Chemical reaction processes, simulating the dissolution and precipitation reactions between fluids and rock minerals, predicting the long-term evolution trends of reservoir porosity and permeability, such as the decrease in permeability caused by scaling. The ground facility system model focuses on the dynamic simulation of ground irrigation and extraction equipment, covering the entire process from the production wellhead to the reinjection wellhead, including production pumps, reinjection pumps, heat exchangers, filters, pipelines, and valves. By establishing equipment characteristic curves, such as the pump flow-head curve, the valve flow-opening curve, and the system hydraulic loss model, the working status of ground equipment under different operating conditions can be accurately simulated, including equipment inlet and outlet parameters, energy consumption, and operating efficiency.

[0019] Furthermore, a deep two-way data interaction is achieved between the THMC coupled simulation model and the surface facility system model. The surface facility system model transmits actual operating parameters such as production well output and reinjection pressure to the THMC model as boundary input conditions for reservoir simulation. Simultaneously, the THMC model feeds back parameters such as reservoir outlet fluid temperature and pressure to the surface facility system model, correcting the inlet boundary conditions of the surface equipment and ensuring that the entire digital mapping process is consistent with the reservoir and surface collaborative operation laws of the real system. At the same time, the system introduces data assimilation algorithms, such as Kalman filtering and ensemble Kalman filtering, to dynamically fuse real-time monitoring data acquired by the data acquisition module, such as reservoir temperature, wellhead pressure, and flow rate, with the model simulation results. By calculating the deviation between the model's predicted values ​​and the actual monitored values, key model parameters, such as reservoir permeability and pump efficiency coefficient, are automatically adjusted, ensuring that the digital mapping process continuously approximates the real system state and solving the problem of simulation accuracy decreasing over time due to the static nature of traditional models.

[0020] Meanwhile, the execution module is responsible for translating the optimization decisions of the data processing module into actual operations. Its hardware includes variable frequency pumps (including production and reinjection pumps), regulating valves (including pipeline flow regulating valves and wellhead pressure regulating valves), and a control unit: a PLC controller. Hardware selection follows principles of high reliability and energy efficiency; for example, the variable frequency pump uses a permanent magnet synchronous motor. The control unit receives optimization control commands from the data processing module in real time, such as target flow, target pressure, pump speed, and valve opening, and converts these commands into control signals conforming to industrial standards. For the variable frequency pump, the control signal adjusts the output frequency of the frequency converter to achieve stepless speed regulation of the pump, thereby precisely changing the total system flow and operating pressure. For the regulating valve, the control signal drives the valve actuator to achieve continuous adjustment of the opening, thus completing the flow distribution and local pressure control of each pipeline branch. The control unit collects the actual operating data of the actuator in real time and feeds it back to the data processing module. If there is a deviation between the actual value and the target value, the data processing module will recalculate the optimization commands, and the control unit will execute adjustments to achieve adaptive adjustment, ensuring that the system always operates under optimal conditions.

[0021] Also includes: The early warning and optimization module is used to perform predictive simulations based on the calibrated data processing module, realize early warning of risks, solve for the optimal combination of operating parameters, and generate optimized control commands.

[0022] Specifically, the early warning and optimization module relies on a high-precision model dynamically calibrated by the data processing module to achieve early risk warning and generate optimal operating schemes. It receives simulation data from the data processing module and provides optimized control commands to the execution module. With the calibrated THMC coupled simulation model and the ground facility system model as the core, combined with historical operating data and industry risk databases, it predicts the risks that may occur in the entire geothermal extraction and injection process. Reservoir risks are predicted by simulating the long-term decline trend of reservoir pressure, abnormal changes in temperature field, and rock stress concentration areas, such as reservoir productivity decline, reservoir collapse, and thermal breakthrough (premature impact of reinjection cold water on the hot water temperature of production wells). Equipment risks are predicted by simulating equipment operating parameters based on the ground facility system model and combining real-time monitoring data such as vibration, temperature, and energy consumption, such as pump wear, valve jamming, pipeline blockage, and decreased heat exchanger efficiency. Based on the simulation results of reservoir and equipment, it predicts system flow mismatch, such as an imbalance between the water output of production wells and the reinjection volume of reinjection wells; pressure overpressure, such as pipeline or wellhead pressure exceeding the safety threshold; and abnormally high energy consumption, etc., which are system-level risks. Based on the probability and impact of risks, an early warning system is established, with different response strategies corresponding to different warning levels: Low risk: The system automatically records risk trends without manual intervention; Low to medium risk: Warning information is pushed to the operation and maintenance platform, prompting attention to changes in relevant parameters; Medium to high risk: An audible and visual alarm is triggered, and a detailed risk analysis report is pushed, including the cause of the risk, the expected time of occurrence, and the scope of impact, recommending on-site inspection by operation and maintenance personnel; High risk: While triggering an emergency alarm, temporary control instructions are automatically issued to the execution module, such as reducing pump speed or closing some branch pipelines to prevent the risk from escalating, and the emergency command platform is linked to notify personnel for emergency response.

[0023] The optimization objectives are highest efficiency, lowest energy consumption, and lowest risk. Combined with actual project needs (e.g., geothermal heating projects prioritize stable outlet temperatures, while geothermal power generation projects prioritize increasing power generation), global optimization is performed on key system operating parameters. These parameters include core process parameters and equipment operating parameters. Core process parameters include the flow ratio between production wells and reinjection wells, the reinjection fluid temperature regulation value (e.g., controlling the fluid temperature before reinjection via a heat exchanger), and the production wellhead pressure setpoint. Equipment operating parameters include variable frequency pump speed, regulating valve opening, and heat exchanger power. Based on changes in system operating conditions, such as seasonal load variations (increased demand for geothermal heating in winter and decreased demand in summer) and dynamic changes in reservoir parameters (e.g., a slow decrease in permeability), the optimization parameters are dynamically updated, and the optimization cycle can be flexibly set. After each optimization calculation, optimized control commands containing the optimal parameter combination are automatically generated, such as adjusting the variable frequency pump speed to 1450 rpm, adjusting the reinjection well regulating valve opening to 85%, and setting the target flow rate to 80 m³ / h. 3 / h, and send it to the execution module.

[0024] The construction of the geological model of the thermal reservoir includes: Acquire geological exploration data, well logging data, and core test data; The configuration is set to generate a three-dimensional spatial grid structure for the target thermal reservoir, and each grid cell is assigned initial physical property parameters, including the spatial distribution of porosity, permeability, initial temperature field, and initial pressure field. The thermal reservoir geological model provides the computational domain and initial conditions for the THMC coupled simulation model, and its physical property parameter field provides the main calibration object for the data assimilation algorithm.

[0025] Specifically, the geothermal reservoir geological model serves as the foundation of the entire simulation system. The core data sources for model construction include three key types of data to ensure the model's realism and accuracy: First, geological exploration data, encompassing regional geological survey reports; seismic exploration profile data, used to identify the burial depth of the reservoir's top and bottom surfaces, fault distribution, and stratigraphic lithological variations; and drilling geological logging data, recording stratigraphic lithology and interlayer distribution at different depths during drilling. Second, well logging data, including sonic logging to calculate rock porosity; resistivity logging to assist in determining reservoir fluid properties; neutron logging to verify porosity data; temperature logging to obtain the original temperature distribution of the reservoir; and pressure logging to determine the initial reservoir pressure. Third, core experimental data, obtained through laboratory experiments on drill core samples, determining fundamental physical properties such as porosity, permeability, thermal conductivity, and specific heat capacity of the rock, providing experimental basis for well logging data interpretation and model parameter assignment. Based on the acquired fundamental data, the target geothermal reservoir region is discretized into a three-dimensional spatial grid structure using the finite element method or finite difference method. The mesh generation follows the principle of refining the mesh in critical areas and simplifying it in non-critical areas. Fine meshes are used around production and reinjection wells, near faults, and in areas with drastic permeability changes. Mesh sizes can be set to 0.5m × 0.5m × 0.5m to ensure accurate simulation of critical areas. Coarse meshes are used in areas far from well clusters and with uniformly distributed physical properties. Mesh sizes can be set to 5m × 5m × 5m to 10m × 10m × 10m to reduce computational load while maintaining simulation accuracy. Each mesh cell serves as the basic unit for model calculation, recording its spatial coordinates (x, y, z) and corresponding formation lithology information. Based on the interpretation results of multi-source data, initial physical property parameters are assigned to each three-dimensional mesh cell to construct a complete reservoir parameter field. The parameter assignment adopts the method of experimental data calibration and well logging data interpolation. Porosity and permeability are calibrated into the well logging interpretation model through core experimental data, and then the well logging data is extended to the grid cells of the entire reservoir area using Kriging interpolation or inverse distance weighted interpolation. The initial temperature field and initial pressure field are generated by combining temperature logging data, pressure logging data and regional geothermal gradient model, and the initial temperature value and initial pressure value of each grid cell are generated by interpolation algorithm, which finally forms a spatially continuous physical property parameter field covering the entire reservoir area.

[0026] Furthermore, the thermal reservoir geological model serves as the foundation for the THMC coupled simulation model, providing it with a clear computational domain, namely the reservoir space covered by the three-dimensional grid; initial conditions, namely the initial temperature field, initial pressure field, and initial distribution of physical properties, ensuring that the THMC model's simulation calculations have clear physical boundaries and initial states; simultaneously, the porosity, permeability, thermal conductivity, and other physical property fields constructed by the model are the main calibration targets of the data assimilation algorithm. During the dynamic calibration of the model, the data assimilation algorithm adjusts the values ​​of these physical property parameters by comparing simulation results with real-time monitoring data, so that the model gradually approximates the actual reservoir state.

[0027] The THMC coupled simulation model is configured to solve a set of partial differential equations involving thermo-hydraulic-mechanical-chemical multiphysics fields to simulate the flow of underground fluids, heat transfer, changes in rock stress, and the process of chemical reactions. The THMC coupled simulation model exchanges data bidirectionally with the surface facility system model: it receives wellhead flow or pressure commands from the surface facility system model as boundary conditions for its simulation, and feeds back the bottom hole pressure and temperature parameters obtained from the simulation calculation to the surface facility system model.

[0028] Specifically, based on the three-dimensional grid and initial parameters provided by the geothermal reservoir geological model, a set of partial differential equations coupling the four major physical fields of heat, water, force, and chemistry is constructed and solved.

[0029] Water flow field equations: Based on Darcy's law, a continuity equation is established to describe the flow of underground fluids in porous media. The effects of porosity and fluid density changes on seepage are considered to obtain the pressure distribution and fluid flow state in the reservoir at different times.

[0030] Temperature field equations: Based on the theory of heat conduction and heat convection, an energy conservation equation describing the heat transfer in the reservoir is established. Considering the heat exchange between the rock skeleton and the fluid, and the convective heat transfer carried by the fluid flow, the dynamic evolution law of the reservoir temperature field is obtained.

[0031] Mechanical field equations: Based on the theory of elasticity, equilibrium equations describing the stress-strain relationship of rocks are established. The effects of changes in pore pressure and temperature on the stress state of rocks are considered. The Mohr-Coulomb criterion is used to determine whether the rocks have been damaged. The stress distribution and deformation state of the reservoir are obtained, and then the changes in porosity and permeability are inverted.

[0032] Chemical field equations: Based on chemical reaction kinetics and mass transport theory, equations are established to describe the reaction between fluids and rock minerals and the migration of solutes. Considering the convection and diffusion caused by fluid flow and the changes in porosity and permeability caused by mineral dissolution and precipitation, these equations can predict mineral scaling, dissolution processes and their long-term effects on reservoir properties.

[0033] The deep coupling of the four major fields is achieved through parameter correlation. For example, in the mechanical field, stress changes alter porosity, which in turn affects the seepage velocity of the water flow field; in the temperature field, temperature changes alter fluid density and viscosity, affecting the flow state of the water flow field, while also altering the thermal expansion coefficient of the rock, thus affecting the stress distribution in the mechanical field; and in the chemical field, mineral dissolution and precipitation directly change porosity and permeability, which in turn affect the water flow field and the temperature field, forming a complete multi-field coupling feedback loop.

[0034] Furthermore, it receives wellhead flow rate or pressure commands from the surface facility system model and uses them as boundary conditions for its own simulation calculations. Specifically, for production wells, the surface facility system model determines the target pumping volume or target wellhead pressure based on user load demand and equipment operating status, and transmits this information to the THMC model as the source and sink terms Q in the flow field equations. f Or the wellhead boundary pressure value; for reinjection wells, the surface facility system model transmits the target injection volume of the reinjection pump or the target pressure at the reinjection wellhead to the THMC model, which is also used as the source and sink term Q of the water flow field equations. f Alternatively, the wellhead boundary pressure value is used to ensure that the THMC model simulation closely matches the actual operational needs on the surface. By solving the multiphysics coupling equations, the real-time pressure and temperature parameters at the bottom of the production and reinjection wells are calculated and fed back to the surface facility system model. The bottom-hole pressure parameter provides a basis for the surface facility system model to calculate the pump head; for example, the lower the bottom-hole pressure of the production well, the higher the head required by the production pump to meet pumping demand. The bottom-hole temperature parameter provides a reference for the surface facility system model to optimize heat exchanger operating parameters; if the bottom-hole temperature is higher than expected, the heat exchanger power can be appropriately reduced to decrease energy consumption, achieving dynamic guidance of reservoir conditions for surface equipment operation.

[0035] The surface facility system model is configured to simulate the working status of all surface equipment from the production wellhead, through the pipeline network and heat exchangers, to the reinjection wellhead; The surface facility system model includes a wellbore flow unit, a pipeline pressure drop and heat loss unit, a heat exchanger efficiency unit, and a pump energy consumption unit. The bottom hole parameters output by the THMC coupled simulation model are used as the input of the wellbore flow unit, while the wellhead flow rate and pressure parameters calculated according to the optimization instructions are used as the boundary conditions of the THMC coupled simulation model. The wellhead parameters output by the wellbore unit serve as the input to the pipeline pressure drop and heat loss unit, while the fluid parameters output by the pipeline pressure drop and heat loss unit serve as the input to the heat exchanger efficiency unit. The utilized fluid state parameters are then transmitted to the wellbore flow unit and the pipeline pressure drop and heat loss unit on the reinjection side. Through iterative calculations, the flow rate into each node is ensured to be equal to the outflow rate, and the pressure loss is closed, thereby solving the stable working state of the entire surface system under specific operating conditions.

[0036] Specifically, for the wellbore sections of production and reinjection wells, a fluid flow and heat transfer model is established within the wellbore, considering frictional resistance along the wellbore and heat exchange between the fluid and the wellbore wall. For example, hot water in the production well dissipates heat to the surrounding formation, while cold water in the reinjection well absorbs heat from the surrounding formation. This unit uses the bottom-hole parameters output from the THMC coupled simulation model as input. By solving the wellbore flow and heat transfer equations, the fluid pressure and temperature parameters at the wellhead are calculated, providing inlet boundary conditions for subsequent pipeline network units. For the surface pipeline network system, including the production and reinjection side networks, a hydraulic and heat loss model is established. The hydraulic loss calculation considers the frictional resistance and local resistance along the pipeline, outputting the pressure distribution at each node of the network. The heat loss calculation considers the heat conduction of the pipeline insulation layer, convection, and radiation, and, combined with external parameters such as ambient temperature and wind speed, outputs the fluid temperature at the network outlet. This unit uses wellhead parameters (production-side pipeline) output from the wellbore flow unit or fluid parameters (reinjection-side pipeline) output from the heat exchanger efficiency unit as input to achieve dynamic simulation of the fluid state of the pipeline system. A heat exchanger heat transfer model is established for the core geothermal equipment, considering factors such as heat exchanger structural parameters, fluid velocity, and fouling thermal resistance, to calculate the actual heat transfer coefficient and heat transfer capacity of the heat exchanger. This unit uses high-temperature geothermal fluid parameters output from the production-side pipeline and user-side load requirements as input to output the temperature parameters of the geothermal fluid after heat exchange, while simultaneously guiding the flow rate adjustment of the production-side pipeline. For production pumps and reinjection pumps, a pump operation model is established based on the pump characteristic curves (flow-head curve, flow-efficiency curve). Combined with the total pipeline resistance loss calculated by the pipeline pressure drop and heat loss unit, the required head of the pump unit is determined, and the actual power consumption of the pump unit is calculated. This unit outputs pump energy consumption data in real time, providing basic data for energy consumption optimization in the early warning and optimization modules. The model receives bottom-hole parameters from the THMC coupled simulation model as input to the wellbore flow unit, ensuring a close correlation between the surface system simulation and the reservoir state. On the other hand, the model calculates wellhead flow and pressure parameters based on optimization control commands issued by the early warning and optimization module, which serve as boundary conditions for the THMC coupled simulation model, enabling collaborative simulation between the surface system and the reservoir model. Through iterative calculations involving multi-unit data transfer, the system ensures that the surface system as a whole is in a stable working state. During the iteration process, the system continuously verifies the consistency of data from each unit: if the inflow and outflow deviations at a certain node exceed 1%, or the calculated pressure loss of a certain pipeline deviates from the actual monitored value by more than 5%, the pipeline resistance coefficient, pump head, and other parameters are readjusted, and the calculation is repeated until the conditions of flow conservation (the inflow to each node equals the outflow) and pressure closure (the total pressure loss of the pipeline equals the head provided by the pump) are met, and finally, the stable working state of the entire surface system under specific operating conditions is solved.

[0037] The THMC coupled simulation model integrates early warning judgment logic, which is configured as follows: When the simulated and predicted production well temperature is lower than the preset threshold, a thermal breakthrough warning is triggered; When the simulated and calculated permeability drop value or pressure rise value in the near-well zone of the reinjection well exceeds the critical value, a reinjection blockage warning is triggered.

[0038] The surface facility system model is integrated with control logic, and the control logic is configured to: Taking the total system energy consumption or unit heat cost as the optimization objective, convert the macroscopic production and reinjection requirements into an executable control parameter combination, where the control parameter combination includes the rotational speed set value of the variable frequency pump and the opening set value of the regulating valve.

[0039] Specifically, taking the production well temperature evolution data solved by the temperature field equation set as the core, the temperature warning threshold is set in combination with the actual project requirements. When the model simulates and predicts that the bottom hole and wellbore temperature of the production well will show a continuous downward trend within the next 72 hours, and the final temperature is lower than the preset threshold, the system automatically triggers a thermal breakthrough warning. The warning information includes the temperature drop rate, the specific time when the threshold is expected to be reached, and the number of the affected production well. Meanwhile, combined with the simulation result of the water flow field, the cause of the thermal breakthrough is preliminarily determined, such as the too small spacing between the reinjection well and the production well, or the excessive reinjection volume leading to the rapid migration of cold water to the production well.

[0040] Based on the coupling simulation data of the chemical field and the water flow field, the change of physical property parameters in the near-well zone of the reinjection well is monitored with emphasis, and two-dimensional warning critical values are set: one is the critical value for permeability drop, and the other is the critical value for pressure rise. When the model calculates that the permeability drop amplitude in the near-well zone of the reinjection well exceeds the critical value, or the reinjection pressure rise value breaks through the critical value, a reinjection blockage warning is triggered immediately. The warning information will present in detail the specific amplitude of permeability drop, the value of pressure rise, and the three-dimensional spatial coordinates of the blockage area. At the same time, combined with the simulation result of mineral reaction in the chemical field, the blockage type is clarified, such as pore blockage caused by calcium carbonate scaling, seepage channel blockage caused by suspended matter deposition in the fluid, etc. The core optimization objective can be switched according to the difference of project operation scenarios: Minimization of total system energy consumption: applicable to projects with strict requirements on energy consumption indicators, such as geothermal systems supporting green buildings, taking the lowest total power consumption of core equipment such as production pumps and reinjection pumps as the objective, and giving priority to selecting the operation parameter combination with low energy consumption; Minimization of unit heat cost: for commercial operation projects, such as geothermal heating communities and commercial hot springs, comprehensively calculate the energy consumption cost of the pump unit, equipment maintenance cost, and geothermal resource utilization efficiency, and take the lowest comprehensive cost per kilowatt-hour of heat as the optimization direction.

[0041] The macro-level heating and irrigation demands on the user side, such as a daily heat demand of 500 MWh during the winter heating season and the reinjection volume needing to match more than 90% of the production well output, are transformed into specific control parameter combinations through multi-unit collaborative calculations: First, based on the heat exchanger efficiency unit calculations, the target flow rate of the production well is derived from the difference between the required heat and the geothermal fluid temperature (e.g., when the required heat is 500 MWh and the geothermal fluid temperature is 60℃, the target flow rate is approximately 80 m³ / h). 3 / h); Combined with the pipeline pressure drop and heat loss unit, calculate the total pipeline resistance loss and determine the required pump head (e.g., if the total pipeline resistance loss is 15m, plus a pressure difference of 5m between the wellhead and the bottom of the well, the target pump head is 20m); Finally, based on the pump characteristic curve, convert the target flow rate and head into the variable frequency pump speed setpoint. At the same time, according to the pipeline flow distribution requirements, calculate the opening setpoint of the regulating valve of each branch pipeline, forming a complete control parameter combination including the variable frequency pump speed and the regulating valve opening, which is directly used to drive the execution module.

[0042] The execution of the control unit includes: Receives real-time measurement of actual pressure P from a pressure transmitter installed at the wellhead of the production well. actual ; Calculate the pressure deviation: e(t) = P set -P actual ; If P actual Below P set If the pressure is insufficient, the flow rate needs to be increased. In this case, the speed of the variable frequency pump should be increased and / or the regulating valve should be opened wider.

[0043] If P actual Higher than P set If the pressure is too high, the flow rate needs to be reduced. In this case, reduce the speed of the variable frequency pump and / or close the regulating valve.

[0044] Among them, the adjustment of the variable frequency pump is the first priority; The regulation of the control valve is the second priority.

[0045] Specifically, the control unit will receive P actual The pressure setpoint P issued by the early warning and optimization module set The pressure setpoint P is calculated and compared in real time by the ground facility system model based on irrigation and drainage requirements. set Generated by the ground facility system model based on irrigation and drainage requirements, via e(t)=P set -P actual Calculate the pressure deviation value e(t), and determine the current pressure state based on the sign of e(t): when e(t) > 0, i.e., P actual <P set The pressure is determined to be insufficient, and the wellhead pressure needs to be increased by increasing the system flow rate; when e(t) < 0, i.e., P actual>P set If the pressure is too high, the wellhead pressure needs to be reduced by decreasing the system flow rate; if |e(t)|≤0.02MPa (which can be adjusted according to the accuracy requirements of the project), the pressure is considered stable, and the current equipment operating parameters should be maintained unchanged.

[0046] Furthermore, the control unit strictly adheres to the priority rule of prioritizing the adjustment of the variable frequency pump and then the auxiliary adjustment of the regulating valve. It executes corresponding adjustment operations based on the type of pressure deviation to ensure efficient and stable flow adjustment: when the pressure is insufficient, the variable frequency pump speed increases. The control unit first sends a speed increase command to the variable frequency pump inverter, dynamically adjusting the speed increment according to the pressure deviation amplitude. For example, when e(t) = 0.05 MPa, the speed increment is 50 rpm; when e(t) = 0.1 MPa, the speed increment is 100 rpm, with a maximum single increment not exceeding 200 rpm to avoid sudden increases in flow rate causing system fluctuations. After adjustment, P is continuously monitored. actual If P within 30 seconds actual Upgraded to P set Stop adjusting within the range of ±0.02MPa; if P actual Still below P set Furthermore, if the variable frequency pump speed has reached 95% of the rated speed (e.g., the rated speed is 1500 rpm and the current speed is 1425 rpm), then the second priority adjustment is triggered, increasing the opening of the regulating valve. The control unit sends an opening increase command to the production wellhead or main pipeline regulating valve, with the opening increment set in a 5%-10% gradient. For example, if the current opening is 60%, it is first increased to 65%. After each adjustment, monitoring is performed for 15 seconds until P... actual The target range has been reached. If the regulating valve opening has increased to 90%, to avoid losing the regulating margin after full opening, and the pressure requirement is still not met, the system pushes a pressure regulation limitation warning to the early warning module, suggesting checking the reservoir capacity or equipment status. When the pressure is too high, the variable frequency pump speed decreases: the control unit prioritizes issuing a speed reduction command to the variable frequency pump inverter. The speed reduction is set according to the deviation range, such as 50 rpm when e(t) = -0.05MPa; 100 rpm when e(t) = -0.1MPa. The minimum speed should not be lower than 30% of the rated speed to prevent the pump unit from running dry. After adjustment, monitor for 30 seconds. If P actual Once the value drops to the target range, stop adjusting; if P actual Still higher than P set Furthermore, the variable frequency pump speed has dropped to 30% of the rated speed, triggering the second priority adjustment. The control unit sends an opening reduction command to the control valve, with the opening reduction set in a 5%-10% gradient. For example, if the current opening is 80%, it will first be reduced to 75%. Each adjustment is monitored for 15 seconds until the pressure reaches the target. If the control valve opening has dropped to 20% to avoid complete closure and flow interruption, and pressure reduction is still not achieved, the system sends a high pressure risk warning and can simultaneously activate the pressure relief valve to assist in pressure reduction.

[0047] The above description is merely a few embodiments of this application and is not intended to limit this application in any way. Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any changes or modifications made by those skilled in the art without departing from the scope of the technical solution of this application using the disclosed technical content are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A hydrothermal geothermal high-efficiency extraction and irrigation intelligent operation and maintenance system, characterized in that, include: The data acquisition module is used to collect multi-source data that characterizes the geothermal reservoir and the operating status of ground equipment in real time; The data processing module is used to perform multi-dimensional and multi-physical field precise digital mapping from the geothermal reservoir to the ground equipment, and obtain the dynamic change process of the geothermal reservoir and the ground equipment under different operating conditions. The data processing module includes a geothermal reservoir geological model, a THMC coupled simulation model, and a surface facility system model. The geothermal reservoir geological model is used to characterize the three-dimensional spatial structure and initial physical property parameter distribution of the geothermal reservoir. The THMC coupled simulation model is built based on the geological model and is used to simulate fluid flow, heat transfer, rock mechanics, and chemical reaction processes. The surface facility system model is used to simulate the working status of surface equipment from the wellhead of the production well to the wellhead of the reinjection well. The THMC coupled simulation model is bidirectionally coupled with the ground facility system model, and the real-time data of the data acquisition module is fused through a data assimilation algorithm to dynamically calibrate the model parameters, so that the digital mapping process is close to the real system state. The execution module includes a variable frequency pump, a regulating valve, and a control unit. The control unit receives the optimized control commands issued by the data processing module, converts the commands into control signals, drives the variable frequency pump to perform stepless speed regulation to change the total flow and pressure of the system, and simultaneously drives the regulating valve to adjust the opening to achieve flow distribution and pressure control, thereby forming an intelligent control loop.

2. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 1, characterized in that, Also includes: The early warning and optimization module is used to perform predictive simulations based on the calibrated data processing module, realize early warning of risks, solve for the optimal combination of operating parameters, and generate optimized control commands.

3. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 1, characterized in that, The construction of the geological model of the thermal reservoir includes: Acquire geological exploration data, well logging data, and core test data; The configuration is set to generate a three-dimensional spatial grid structure for the target thermal reservoir, and each grid cell is assigned initial physical property parameters, including the spatial distribution of porosity, permeability, initial temperature field, and initial pressure field. The thermal reservoir geological model provides the computational domain and initial conditions for the THMC coupled simulation model, and its physical property parameter field provides the calibration object for the data assimilation algorithm.

4. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 3, characterized in that, The THMC coupled simulation model is configured to solve a set of partial differential equations involving thermo-hydraulic-mechanical-chemical multiphysics fields to simulate the flow of underground fluids, heat transfer, changes in rock stress, and the process of chemical reactions. The THMC coupled simulation model exchanges data bidirectionally with the surface facility system model: it receives wellhead flow or pressure commands from the surface facility system model as boundary conditions for its simulation, and feeds back the bottom hole pressure and temperature parameters obtained from the simulation calculation to the surface facility system model.

5. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 4, characterized in that, The surface facility system model is configured to simulate the working status of all surface equipment from the production wellhead, through the pipeline network and heat exchangers, to the reinjection wellhead; The surface facility system model includes a wellbore flow unit, a pipeline pressure drop and heat loss unit, a heat exchanger efficiency unit, and a pump energy consumption unit. The bottom hole parameters output by the THMC coupled simulation model are used as the input of the wellbore flow unit, while the wellhead flow rate and pressure parameters calculated according to the optimization instructions are used as the boundary conditions of the THMC coupled simulation model. The wellhead parameters output by the wellbore flow unit serve as the input to the pipeline pressure drop and heat loss unit, while the fluid parameters output by the pipeline pressure drop and heat loss unit serve as the input to the heat exchanger efficiency unit. The utilized fluid state parameters are then transmitted to the wellbore flow unit and the pipeline pressure drop and heat loss unit on the reinjection side. Through iterative calculations, it is ensured that the flow rate into each node equals the outflow rate, and the pressure loss is closed, thereby solving the stable working state of the entire surface system under specific operating conditions.

6. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 4, characterized in that, The THMC coupled simulation model integrates early warning judgment logic, which is configured as follows: When the simulated and predicted temperature of the production well is lower than a preset threshold, a thermal breakthrough warning is triggered. When the simulated decrease in permeability or increase in pressure in the near-wellbore zone of the reinjection well exceeds the critical value, a reinjection blockage warning is triggered.

7. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 5, characterized in that, The ground infrastructure system model integrates control logic, which is configured as follows: With the total energy consumption or unit heat cost of the system as the optimization target, the macroscopic irrigation and drainage requirements are transformed into a combination of executable control parameters, which includes the speed setting value of the variable frequency pump and the opening setting value of the regulating valve.

8. The intelligent operation and maintenance system for high-efficiency hydrothermal geothermal extraction and irrigation according to claim 1, characterized in that, The execution of the control unit includes: Receives real-time measurement of actual pressure P from a pressure transmitter installed at the wellhead of the production well. actual ; Calculate the pressure deviation: e(t) = P set -P actual P set Set the pressure value; If P actual Below P set This indicates insufficient pressure, requiring an increased flow rate. In this case, increase the speed of the variable frequency pump and / or open the regulating valve wider. If P actual Higher than P set This indicates that the pressure is too high and the flow rate needs to be reduced. In this case, reduce the speed of the variable frequency pump and / or close the regulating valve. Among them, the adjustment of the variable frequency pump is the first priority; The regulation of the control valve is the second priority.

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