Geothermal resource exploration method and system based on large model

Abstract

The invention relates to the field of resource exploration, and discloses a geothermal resource exploration method and system based on a large model, and the method comprises the steps: firstly carrying out the data collection of a target research region, and collecting the geothermal geological condition data and geological temperature data in a research range; establishing a geothermal geological condition data model through the collected geothermal geological condition data; establishing a geological temperature model according to the geological temperature data; integrating the geothermal geological condition data model and the geological temperature model to obtain a large geothermal resource exploration model; performing resource exploitation simulation in the geothermal resource exploration large model, recording an exploitation process condition, and establishing an exploitation risk grade gradient map according to the exploitation process condition; the problems that in the prior art, geothermal resource exploration is not systematic and incomplete, and geological conditions are not analyzed and monitored in real time in the mining process are solved.

Description

Technical Field

[0001] This invention relates to the field of resource exploration, and in particular to a method and system for geothermal resource exploration based on a large model. Background Technology

[0002] Geothermal resources refer to the thermal energy stored inside the Earth, which can be used to generate heat or electricity. Geothermal energy is a renewable energy source; the Earth's internal heat is constantly generated, providing a continuous supply of energy to meet energy needs.

[0003] Currently, geothermal resource exploration and monitoring treats geothermal resources as static. However, geothermal resources change to varying degrees over time. During extraction, alterations in geothermal fluids affect the geological structure of the extraction strata, including porosity, permeability, rock mechanical properties, and fluid physicochemical properties. These changes can not only impact geothermal extraction efficiency but also potentially trigger geological hazards such as land subsidence, microseismic events, well blowouts, and groundwater chemical pollution. Due to the high costs of geothermal resource exploration and development, utilizing existing exploration results and development examples for optimal exploration area selection in potential development zones is crucial. However, current technologies, relying solely on simple analysis of geothermal exploration data, often exhibit strong subjectivity and easily overlook certain geological information, resulting in poor accuracy in exploration area selection and thus carrying significant risks. Summary of the Invention

[0004] The present invention aims to provide a geothermal resource exploration method and system based on a large model, which solves the problems of unsystematic and incomplete geothermal resource exploration in the prior art, and the lack of real-time analysis and monitoring of geological conditions during the mining process.

[0005] To achieve the above objectives, the present invention provides the following method:

[0006] This invention provides a geothermal resource exploration method based on a large model:

[0007] S1: Collect data on the target study area, including geothermal geological conditions and geological temperature data within the study area;

[0008] S2: Establish a geothermal geological condition data model based on the collected geothermal geological condition data;

[0009] S3: Establish a geological temperature model based on the geological temperature data;

[0010] S4: Integrate the geothermal geological condition data model and the geological temperature model to obtain a large-scale geothermal resource exploration model;

[0011] S5: Simulate resource extraction in the large-scale geothermal resource exploration model, record the extraction process, and establish an extraction risk level gradient map based on the extraction process.

[0012] S6: Establish a geothermal resource extraction system scheme based on the extraction risk level gradient map, and complete the geothermal resource extraction process according to the geothermal resource extraction system scheme.

[0013] Preferably, the geothermal geological condition data includes geological depth, geological lithology combination, and geological structure map within the study area; the geological temperature data includes the average temperature of geological resource reservoirs and the overall temperature distribution from the surface to the geothermal resources within the study area over the past year.

[0014] Preferably, the step of establishing a geothermal geological condition data model using the collected geothermal geological condition data includes: establishing a three-dimensional geological model using the geological depth, geological lithology combination, and geological structure map; dividing the geological structure into layers with different geological lithology combinations due to different geological depths, and establishing a separate geological environment system for each layer; establishing a gradient map of the impact of mining on each geological environment system; and integrating the three-dimensional geological model, the geological environment system, and the gradient map of the impact of mining on the geological layer to obtain the geothermal geological condition data model.

[0015] Preferably, the step of establishing a three-dimensional geological model using the geological depth, geological lithology combination, and geological structure map, and stratifying and marking areas with different geological lithology combinations due to different geological depths, to establish a separate geological environment system for each layer, includes: establishing a three-dimensional rectangular coordinate system downwards from the surface center of the target study area; adding the geological depth and geological structure map to the three-dimensional rectangular coordinate system, and splitting the Z-axis of the three-dimensional rectangular coordinate system into multiple line axes according to the different geological lithology combinations to obtain a three-dimensional geological model; stratifying and marking areas with different geological lithology combinations according to the multiple line axes to obtain multiple geological environment layers; establishing a geological environment layer evaluation system based on the average temperature, mining difficulty, geological thickness, and mining impact reach of the geological environment layers; converting different types of data in the geological environment evaluation system into the same form and integrating the different types of data to establish a geological environment system.

[0016] Preferably, the step of establishing a gradient map of the impact of mining on each geological environment system includes: simulating the changes of different types of data in the geological environment system when geothermal resource mining is at different mining depths; recording the highest and lowest values ​​of each type of data based on the changes of different types of data in the geological environment system; calculating the average changes of different types of data, and recording the relationship between the average changes of different types of data and the highest and lowest values ​​of change in real time to obtain the gradient map of the impact of mining on the geological layer.

[0017] Preferably, the step of establishing a geological temperature model based on the geological temperature data includes: collecting the average temperature of geological resource reservoirs and the overall temperature distribution from the surface to geothermal resources within the study area over the past year using sensors; classifying and labeling the overall temperature distribution from the surface to geothermal resources within the study area according to temperature zones; calculating the temperature difference between the labeled temperature zones and the average temperature of geological resource reservoirs within the study area over the past year; and analyzing the influencing factors of temperature differences based on the temperature zone classification and labeling to obtain a geological temperature model.

[0018] Preferably, the steps of simulating resource extraction in the geothermal resource exploration model, recording the extraction process, and establishing an extraction risk level gradient map based on the extraction process include: simulating resource extraction in the geothermal resource exploration model, performing extraction simulations from different locations within the target study area, and monitoring the data changes of the geothermal resource exploration model below the surface at different extraction depths in real time; comparing the data changes of the corresponding geothermal resource exploration model obtained from different extraction locations with the extraction risk level and extraction impact level to obtain the extraction risk level gradient map; the higher the extraction risk level and the higher the extraction impact level, the higher the extraction risk level in the extraction risk level gradient map.

[0019] Preferably, the formula for calculating the mining risk level is:

[0020] D = d1 * 60% + d2 * 40%;

[0021] Where D represents the mining risk level, d1 represents the mining risk degree, and d2 represents the mining impact degree.

[0022] Preferably, after simulating resource extraction in the geothermal resource exploration model, recording the extraction process, and establishing an extraction risk level gradient map based on the extraction process, the method further includes: monitoring changes in geological temperature during the resource extraction simulation and performing geological temperature analysis; statistically analyzing the average temperature change within a unit time period; calculating the average of all the average temperature changes within a day to obtain the daily average temperature change value; determining the relationship between the average temperature change within a unit time period and the daily average temperature change value, and setting alarm shutdown conditions; if the average temperature change is greater than the daily average temperature change value, and the average temperature change within the two consecutive unit time periods preceding the average temperature change is greater than the daily average temperature change value, then an alarm shutdown is triggered.

[0023] This invention provides a geothermal resource exploration system based on a large model, characterized in that the system comprises:

[0024] Data acquisition module: Collects data on the target study area, including geothermal geological conditions and geological temperature data within the study area;

[0025] Geological Environment Module: Establishes a geothermal geological condition data model based on the collected geothermal geological condition data;

[0026] Geological temperature module: Establishes a geological temperature model based on the geological temperature data;

[0027] Model integration module: Integrates the geothermal geological condition data model and the geological temperature model to obtain a large-scale geothermal resource exploration model;

[0028] Mining Simulation Module: This module simulates resource mining within the large-scale geothermal resource exploration model, records the mining process, and establishes a mining risk level gradient map based on the mining process data.

[0029] Temperature Analysis Module: Monitors changes in geological temperature during resource extraction simulation and performs geological temperature analysis;

[0030] Scheme generation module: Establishes a geothermal resource extraction system scheme based on the extraction risk level gradient map, and completes the geothermal resource extraction process based on the geothermal resource extraction system scheme.

[0031] The beneficial effects of this invention are reflected in the following aspects: This invention establishes geothermal geological condition data models and geothermal temperature models by collecting geothermal geological condition data and geothermal temperature data. It fully considers various data information in the process of geothermal resource extraction, and divides the geological extraction environment into multiple segments through geological stratification and temperature zoning. This transforms the overall object information into multiple segments, making data analysis more accurate. After the segmentation, the data between each segment is correlated to achieve a holistic analysis from the parts. This analysis method enables data analysis to be both accurate and relevant to the object itself, making the exploration process more systematic. Finally, the extraction process is simulated, and an extraction risk level gradient map is established to achieve an optimal balance between extraction risk and extraction difficulty, maximizing benefits. Real-time temperature analysis is also incorporated to monitor changes in extraction risk in real time during the extraction process, maximizing safety and making extraction more intelligent. Attached Figure Description

[0032] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the accompanying drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0033] Figure 1 A flowchart illustrating a geothermal resource exploration method based on a large model, provided for an embodiment of the present invention;

[0034] Figure 2 This is a flowchart illustrating a geothermal resource exploration system based on a large model, provided as an embodiment of the present invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0036] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0037] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0038] Currently, geothermal resource exploration and monitoring treats geothermal resources as static. However, geothermal resources change to varying degrees over time, resulting in different exploration and monitoring results for each instance. Consequently, the calculated heat of the geothermal resources based on these results will differ, potentially leading to mining accidents or even landslides during extraction. Existing technologies lack systematic and novel geothermal resource surveys, considering only simple geological elements without taking into account geological changes during extraction or temperature variations. This neglect of certain conditions during geothermal resource extraction makes it easy for safety accidents to occur. Therefore, a method that can systematically analyze and explore geothermal resources, comprehensively consider all influencing factors, and analyze geological changes during extraction in real time is urgently needed in current technologies.

[0039] The present invention aims to provide a geothermal resource exploration method and system based on a large model, which solves the problems of unsystematic and incomplete geothermal resource exploration in the prior art, and the lack of real-time analysis and monitoring of geological conditions during the mining process.

[0040] like Figure 1 As shown in the figure, a specific embodiment of the present invention provides a geothermal resource exploration method based on a large model, comprising the following steps:

[0041] S1: Collect data on the target study area, including geothermal geological conditions and geological temperature data within the study area.

[0042] In this embodiment of the invention, the geothermal geological condition data includes the geological depth, geological lithology combination, and geological structure map within the study area, as well as hydrogeological conditions, reservoir temperature field characteristics, and geothermal fluid chemical characteristics; the geological temperature data includes the average temperature of the geological resource reservoir in the most recent year within the study area and the overall temperature distribution from the surface to the geothermal resources.

[0043] S2: Establish a geothermal geological condition data model based on the collected geothermal geological condition data.

[0044] In this embodiment of the invention, a three-dimensional geological model is established using geological depth, geological lithological combinations, and geological structure maps. Regions within the geological structure that exhibit different geological lithological combinations due to varying geological depths are layered and marked, with each layer forming a separate geological environment system. A three-dimensional rectangular coordinate system is established downwards from the surface center of the target study area. The geological depth and geological structure maps are added to this three-dimensional rectangular coordinate system, and the Z-axis is divided into multiple segments based on the different geological lithological combinations, thus establishing the three-dimensional geological model. Regions with different geological lithological combinations are layered and marked according to these segments, resulting in multiple geological environment layers. A geological environment layer assessment is established based on the average temperature, mining difficulty, geological thickness, and mining impact extent within each geological environment layer. The evaluation system transforms different types of data from the geological environment assessment system into a common form and integrates them to establish a geological environment system. A gradient map of the impact on geological layers is created based on the degree of impact of mining on each geological environment system. The system simulates the changes in different types of data within the geological environment system at different mining depths. The system records the highest and lowest values ​​of each type of data based on these changes. The average changes of different types of data are calculated, and the relationship between the average changes and the highest and lowest values ​​is recorded in real time to obtain a gradient map of the impact on geological layers. Finally, the three-dimensional geological model, the geological environment system, and the gradient map of the impact on geological layers are integrated to obtain a geothermal geological condition data model.

[0045] S3: Establish a geological temperature model based on geological temperature data.

[0046] In this embodiment of the invention, sensors are used to collect the average temperature of geological resource reservoirs and the overall temperature distribution from the surface to geothermal resources within the research area over the past year; the overall temperature distribution from the surface to geothermal resources within the research area is classified and labeled according to temperature zones; the temperature difference between the labeled temperature zones and the average temperature of geological resource reservoirs within the research area over the past year is calculated; and the factors affecting temperature differences are analyzed based on the temperature zone classification and labeling to obtain a geological temperature model.

[0047] S4: Integrate geothermal geological condition data models and geological temperature models to obtain a large-scale model for geothermal resource exploration.

[0048] In this embodiment of the invention, the geothermal resource exploration large-scale model is a holistic three-dimensional geological environment model, comprising two levels. The first level is a geothermal geological condition data model, displaying the specific composition and components of the geological environment. The second level is a geological temperature model, displaying the temperature at each point within the specific geological environment, temperature change predictions, and heat transfer around all heat sources in the geological environment. The performance of the geothermal resource exploration large-scale model is evaluated based on discriminant model performance testing indicators. In this embodiment, the discriminant model performance testing indicators are the model accuracy (ACC) value and the area under the ROC curve (AUC) value. If the ACC value is not lower than 80% and the AUC value is not lower than 0.8, the model performance is good and can be used for geothermal resource discrimination. If the ACC value is less than 80% or the AUC value is less than 0.8, it indicates poor model performance. In this case, the sample size ratio of the training set and prediction set in the sample data of S4 is adjusted, and machine learning calculations are re-performed using Matlab software until the model performs well.

[0049] S5: Simulate resource extraction in the large-scale geothermal resource exploration model, record the extraction process, and establish an extraction risk level gradient map based on the extraction process.

[0050] In this embodiment of the invention, resource extraction simulation is performed in a large-scale geothermal resource exploration model. Extraction simulations are conducted at different locations within the target study area, and the data changes of the large-scale geothermal resource exploration model at different extraction depths are monitored in real time. The data changes of the corresponding large-scale geothermal resource exploration models obtained at different extraction locations are compared to determine the extraction risk and impact, resulting in an extraction risk level gradient map. The higher the extraction risk and the higher the extraction impact, the higher the extraction risk level in the extraction risk level gradient map.

[0051] The formula for calculating the mining risk level is:

[0052] D = d1 * 60% + d2 * 40%;

[0053] Where D represents the mining risk level, d1 represents the mining risk degree, and d2 represents the mining impact degree;

[0054] Analyze geological data from different locations and depths of the mining area to obtain data on porosity, permeability, lithology, and stratigraphic sequence anomalies in core samples at different formation temperatures, and preset early warning values ​​for exploration and mining.

[0055] Based on preset exploration and mining early warning values, the porosity, permeability, lithology, and stratigraphic sequence anomaly data of geological layers at different formation temperatures are divided into different magnitudes, and mining risk levels are generated based on the different magnitudes of the porosity, permeability, lithology, and stratigraphic sequence anomaly data of geological layers at different formation temperatures;

[0056] After simulating resource extraction in the large-scale geothermal resource exploration model, recording the extraction process, and establishing an extraction risk level gradient map based on the extraction process, the process also includes: monitoring changes in geological temperature during the resource extraction simulation and performing geological temperature analysis; statistically analyzing the average temperature change within a unit time period; calculating the average of all average temperature changes within a day to obtain the daily average temperature change value; determining the relationship between the average temperature change within a unit time period and the daily average temperature change value, and setting alarm shutdown conditions; if the average temperature change is greater than the daily average temperature change value, and the average temperature change within the two consecutive unit time periods preceding the average temperature change is greater than the daily average temperature change value, then an alarm shutdown is triggered.

[0057] S6: Establish a geothermal resource extraction system plan based on the extraction risk level gradient map, and complete the geothermal resource extraction process based on the geothermal resource extraction system plan.

[0058] In this embodiment of the invention, the risk level and impact range of different mining schemes and mining locations are obtained according to the mining risk level gradient map, and a geothermal resource mining system scheme is established based on the lowest mining risk level and the smallest impact range.

[0059] like Figure 2 As shown, the present invention provides a geothermal resource exploration system based on a large model, characterized in that the system includes:

[0060] Data acquisition module: Collects data on the target study area, including geothermal geological conditions and geological temperature data within the study area;

[0061] Geological Environment Module: Establishes a geothermal geological condition data model based on collected geothermal geological condition data;

[0062] Geological temperature module: Establishes a geological temperature model based on geological temperature data;

[0063] Model integration module: Integrates geothermal geological condition data models and geological temperature models to obtain a large-scale model for geothermal resource exploration;

[0064] Mining Simulation Module: Simulates resource mining in a large-scale geothermal resource exploration model, records the mining process, and establishes a mining risk level gradient map based on the mining process.

[0065] Temperature Analysis Module: Monitors changes in geological temperature during resource extraction simulation and performs geological temperature analysis;

[0066] Scheme generation module: Establishes a geothermal resource extraction system scheme based on the extraction risk level gradient map, and completes the geothermal resource extraction process based on the geothermal resource extraction system scheme.

[0067] The beneficial effects of this invention are reflected in the following aspects: This invention establishes geothermal geological condition data models and geothermal temperature models by collecting geothermal geological condition data and geothermal temperature data. It fully considers various data information in the process of geothermal resource extraction, and divides the geological extraction environment into multiple segments through geological stratification and temperature zoning. This transforms the overall object information into multiple segments, making data analysis more accurate. After the segmentation, the data between each segment is correlated to achieve a holistic analysis from the parts. This analysis method enables data analysis to be both accurate and relevant to the object itself, making the exploration process more systematic. Finally, the extraction process is simulated, and an extraction risk level gradient map is established to achieve an optimal balance between extraction risk and extraction difficulty, maximizing benefits. Real-time temperature analysis is also incorporated to monitor changes in extraction risk in real time during the extraction process, maximizing safety and making extraction more intelligent.

[0068] The above descriptions are merely embodiments of the present invention. Commonly known technical solutions or characteristics are not described in detail here. It should be noted that those skilled in the art can make various modifications and improvements without departing from the present invention, and these should also be considered within the scope of protection of the present invention. These modifications and improvements will not affect the effectiveness of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A large model-based geothermal resource exploration method, characterized by, The method comprises: S1: data acquisition on the target research area, collecting geothermal geological condition data and geological temperature data within the research scope; S2: establishing a geothermal geological condition data model based on the collected geothermal geological condition data; S3: establishing a geological temperature model according to the geological temperature data; S4: integrating the geothermal geological condition data model and the geological temperature model to obtain a large geothermal resource exploration model; S5: resource exploitation simulation in the large geothermal resource exploration model, recording the exploitation process, and establishing an exploitation risk level gradient map according to the exploitation process; S6: establishing a geothermal resource exploitation system scheme according to the exploitation risk level gradient map, and completing the geothermal resource exploitation process according to the geothermal resource exploitation system scheme.

2. The geothermal resource exploration method based on a large model according to claim 1, characterized in that: the geothermal geological condition data is geological depth, geological lithology combination and geological structure map within the research scope; the geological temperature data is the average temperature of the geological resource reservoir in the research scope in the last year and the overall temperature distribution from the surface to the geothermal resource.

3. The method of claim 2, wherein the method is based on a large model. The step of establishing a geothermal geological condition data model based on the collected geothermal geological condition data comprises: establishing a three-dimensional geological model based on the geological depth, geological lithology combination and geological structure map, marking different areas in the geological structure with different geological lithology combinations in different layers, and establishing a separate geological environment system for each layer; establishing a geological layer affected situation gradient map according to the degree of influence of each geological environment system on exploitation; integrating the three-dimensional geological model, the geological environment system and the geological layer affected situation gradient map to obtain the geothermal geological condition data model.

4. The method for geothermal resource exploration based on a large model according to claim 3, characterized in that, The step of establishing a three-dimensional geological model based on the geological depth, geological lithology combination and geological structure map, marking different areas in the geological structure with different geological lithology combinations in different layers, and establishing a separate geological environment system for each layer comprises: establishing a three-dimensional rectangular coordinate system downward from the surface center position of the target research area; adding the geological depth and the geological structure map to the three-dimensional rectangular coordinate system, and splitting the Z-axis of the three-dimensional rectangular coordinate system into a multi-section linear shaft according to the different geological lithology combinations to obtain a three-dimensional geological model; marking different areas with different geological lithology combinations in different layers according to the multi-section linear shaft to obtain multiple geological environment layers; establishing a geological environment layer evaluation system according to the average temperature, exploitation difficulty, geological thickness and exploitation influence degree in the geological environment layer; converting different types of data in the geological environment evaluation system into the same form, integrating the different types of data, and establishing a geological environment system.

5. The method for geothermal resource exploration based on a large model according to claim 4, characterized in that, The step of establishing a geological layer affected situation gradient map according to the degree of influence of each geological environment system on exploitation comprises: simulating the changes of different types of data in the geological environment system when the geothermal resource exploitation is at different depths; According to the different data changes of the geological environment system, the highest value and the lowest value of the change of each kind of data are recorded; The average change of different kinds of data is calculated, and the relationship between the average change of different kinds of data and the highest value and the lowest value of the change is recorded in real time to obtain a geological layer affected situation gradient graph.

6. The method for geothermal resource exploration based on a large model according to claim 2, characterized in that, The step of establishing a geological temperature model according to the geological temperature data comprises: Collecting the average temperature of the geological resource reservoir in the research range in the past year and the overall temperature distribution from the surface to the geothermal resource through a sensor; Classifying and marking the overall temperature distribution from the surface to the geothermal resource in the research range by temperature zone; Calculating the temperature difference between the marked temperature zone and the average temperature of the geological resource reservoir in the research range in the past year; Obtaining a geological temperature model by analyzing the temperature difference influencing factors according to the temperature zone classification mark.

7. The method of claim 1, wherein the method is based on a large model. The step of simulating resource exploitation in the geothermal resource exploration large model, recording the exploitation process, and establishing a mining risk level gradient graph according to the exploitation process comprises: Simulating resource exploitation in the geothermal resource exploration large model, simulating exploitation from different positions in the target research area, and monitoring the data change of the geothermal resource exploration large model under the surface at different exploitation depths in real time; Comparing the data change of the geothermal resource exploration large model obtained from different exploitation positions to obtain the exploitation risk degree and the exploitation influence degree, and obtaining a mining risk level gradient graph; The higher the exploitation risk degree and the exploitation influence degree are, the higher the mining risk level in the mining risk level gradient graph is.

8. The method for geothermal resource exploration based on a large model according to claim 7, characterized in that, The calculation formula of the mining risk level is: D=d1*60%+d2*40%; Wherein, D is the mining risk level, d1 is the exploitation risk degree, and d2 is the exploitation influence degree.

9. The method for geothermal resource exploration based on a large model according to claim 1, characterized in that, After the step of simulating resource exploitation in the geothermal resource exploration large model, recording the exploitation process, and establishing a mining risk level gradient graph according to the exploitation process, the system further comprises: Monitoring the change of the geological temperature during the resource exploitation simulation, and analyzing the geological temperature; Statistically calculating the average change temperature of the geological temperature change in a unit time period; Calculating the average value of all the average change temperatures in a day to obtain a daily average temperature average change value; Judging the relationship between the average change temperature in the unit time period and the daily average temperature average change value, and setting an alarm shutdown condition; If the average change temperature is greater than the daily average temperature average change value, and the average change temperatures in the previous two consecutive unit time periods are greater than the daily average temperature average change value, an alarm shutdown is performed.

10. A large model-based geothermal resource exploration system, characterized by, The system comprises: A data acquisition module: acquiring data of a target research area, including geothermal geological condition data and geological temperature data in the research range; A geological environment module: establishing a geothermal geological condition data model through the acquired geothermal geological condition data; A geological temperature module: establishing a geological temperature model according to the geological temperature data; The model integration module integrates the geothermal geological condition data model and the geological temperature model to obtain a large geothermal resource exploration model. The exploitation simulation module simulates resource exploitation in the large geothermal resource exploration model, records the exploitation process, and establishes an exploitation risk level gradient map according to the exploitation process. The temperature analysis module monitors the change of geological temperature during the resource exploitation simulation process and analyzes the geological temperature. The scheme generation module establishes a geothermal resource exploitation system scheme according to the exploitation risk level gradient map and completes the geothermal resource exploitation process according to the geothermal resource exploitation system scheme.

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