Geothermal resource intelligent positioning and grading method and system based on multi-stage heat control and fuzzy comprehensive evaluation

Abstract

This invention discloses an intelligent positioning and classification method and system for geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation, belonging to the field of geothermal resource exploration and evaluation technology. It includes: constructing a multi-source professional geothermal database; integrating multi-source geophysical and geological data to identify three types of heat-controlling structures: primary mantle fault structures, secondary crustal fault structures, and tertiary extensional faults, and constructing a three-dimensional geological model of the multi-level heat-controlling structures; extracting structural parameters from the three-dimensional geological model to calculate the geothermal enrichment index, and automatically delineating and classifying geothermal enrichment target areas based on the numerical values; establishing a multi-level evaluation index system for geothermal field quality, using fuzzy comprehensive discrimination to automatically evaluate the quality of delineated target areas or known geothermal fields, and outputting the grade; and matching the geothermal field quality evaluation results with geothermal occurrence patterns, and matching development and utilization technologies with industrial application directions. This invention significantly improves the scientificity and accuracy of target area positioning and reduces exploration risks.

Description

Technical Field

[0001] This invention relates to the field of geothermal resource exploration and evaluation technology, and more specifically to a method and system for intelligent positioning and classification of geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation. Background Technology

[0002] Geothermal energy, as a renewable and reliable energy source with abundant reserves, plays an important role in the transformation of the energy structure. However, the exploration and development of geothermal resources in my country still faces many challenges: unclear resource reserves, low accuracy in locating exploration target areas, strong subjectivity in resource evaluation, and unscientific matching between development models and resource endowments.

[0003] Currently, geothermal resource exploration mainly relies on traditional geological surveys and geophysical exploration methods. These methods are often time-consuming, labor-intensive, and costly, and heavily dependent on the experience of exploration personnel, making it difficult to achieve rapid and accurate target area delineation. In terms of resource evaluation, although single-index methods and comprehensive index methods exist, they generally suffer from problems such as subjective index weighting and inability to handle fuzzy information. This leads to biased evaluation results that fail to comprehensively and objectively reflect the overall quality of geothermal fields and cannot provide a reliable basis for prioritizing development. Furthermore, existing Geographic Information Systems (GIS) or digital platforms mostly focus on visualizing basic data, lacking the ability to integrate, model, and analyze deep geological theories (such as tectonic heat control mechanisms) with multi-source data and directly output quantitative decision support information. While a few platforms have begun to integrate AI question answering, they are mostly based on general knowledge bases and lack deep coupling with professional geothermal databases, evaluation models, and industry knowledge, failing to provide accurate exploration and development assessments.

[0004] Therefore, there is an urgent need for a new technology for geothermal resource exploration and evaluation that can integrate multidisciplinary data, quantify geological laws, and achieve automated and intelligent analysis and evaluation, so as to reduce exploration risks, improve development efficiency, and scientifically guide industrial planning.

[0005] Therefore, proposing a method and system for intelligent positioning and classification of geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation to solve the difficulties of existing technologies is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, the present invention provides a method and system for intelligent positioning and classification of geothermal resources based on multi-level tectonic heat control and fuzzy comprehensive evaluation. It aims to digitize and model the original "tectonic heat control theory" and "source-reservoir theory", and automatically identify heat-controlling structures, calculate quantitative evaluation indicators, realize intelligent positioning of target areas and automatic quality classification by integrating multi-source geophysical and geological data, and finally match and recommend suitable development and utilization modes, thereby forming a complete, objective and efficient digital decision support technology system from "resource positioning" to "development suggestions".

[0007] To achieve the above objectives, the present invention provides the following technical solution: A smart location and classification method for geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation includes the following steps: S1. Construct a multi-source geothermal professional database; S2. By integrating multi-source geophysical and geological data, three types of heat-controlling structures are identified in a hierarchical manner: primary mantle fault structures, secondary crustal fault structures, and tertiary extensional fault structures. A three-dimensional geological model of multi-level heat-controlling structures is then constructed. S3. Calculate the geothermal enrichment index Qh by extracting structural parameters based on the three-dimensional geological model, and automatically delineate and classify the geothermal enrichment target area according to the Qh value. S4. Establish a multi-level evaluation index system for the quality of geothermal fields, and use the fuzzy comprehensive discrimination method to automatically evaluate the quality of the delineated target area or known geothermal fields, and output 5A, 4A and 3A levels. S5. Combine the geothermal field quality evaluation results to match the geothermal occurrence pattern, and match the most suitable development and utilization technology and industrial application direction based on the occurrence pattern.

[0008] Optionally, the geothermal multi-source professional database in S1 includes: data on large and medium-sized fault zones nationwide, hot spring data, full parameter data of geothermal wells, geophysical exploration data, geological structure data, hydrological and climatic data, and geothermal policy and regulatory documents; the full parameters of geothermal wells include: well depth, water temperature, water output, water quality, and historical mining data.

[0009] Optionally, the specific content of S2 is as follows: S21. Use gravity anomaly data and seismic tomography data to conduct GIS spatial overlay analysis to identify the spatial distribution of first-order fault-mantle structures. S22. Identification of secondary fault structures based on controlled-source audio-frequency magnetotelluric sounding (CSAMT) profile data and magnetic data. S23. Identify third-order tensional fractures using high-resolution seismic exploration data and UAV aeromagnetic data; S24. Analyze the spatial topological relationships of multi-level structures, verify the structural connectivity through the resistivity vertical overlay method, and integrate and construct a three-dimensional geological structural model containing first-, second-, and third-level structures.

[0010] Optionally, the formula for calculating the geothermal enrichment index Qh in S3 is:

[0011] in, The thermal conductivity of the fracture zone is... To construct a geothermal gradient, To construct the area of ​​the intersection zone, To construct connectivity coefficients; Constructing connectivity coefficients The assignment rule is: when multi-level structures are directly connected. =1.0; When the intersection angle is less than 30°. =0.8; when an isolated fracture has no structural intersection =0.3.

[0012] Optionally, the specific content of the fuzzy comprehensive discrimination method in S4 is as follows: S41. Construct a quality evaluation system for hydrothermal geothermal fields that includes 5 primary indicators and 15 secondary indicators, and use the analytic hierarchy process (AHP) to calculate the weight vectors of each level of indicators. S42. Input the measured / deduced data of each secondary indicator of the geothermal field to be evaluated, and construct the indicator membership matrix based on the preset 5A, 4A, and 3A three-level evaluation standards. S43. Perform fuzzy synthesis operation on the weight vector and the membership matrix to obtain the membership vector corresponding to the three quality levels; S44. Calculate the comprehensive quality evaluation value M of the geothermal field based on the weighted scoring method, and determine the quality level according to the preset threshold.

[0013] Optionally, the industrial application direction in S5 can be selected from the preset five-industry model library. The five-industry models include energy-based power generation, large-scale heating and cooling, specialized cultural tourism and leisure, distinctive planting and breeding, and integrated health and wellness medical care.

[0014] The intelligent geothermal resource positioning and classification system based on multi-level structural heat control and fuzzy comprehensive evaluation executes any of the above-mentioned intelligent geothermal resource positioning and classification methods based on multi-level structural heat control and fuzzy comprehensive evaluation, including: The data storage and management module is used to store and maintain the geothermal multi-source professional database; The structure identification and modeling module is connected to the data storage and management module to perform multi-level thermal control structure hierarchical identification, connectivity verification, and three-dimensional geological model construction. The target area quantitative positioning module is connected to the structure identification and modeling module. It has a built-in Qh index calculation model to complete the calculation of geothermal enrichment index and automatic target area delineation and classification. The quality comprehensive evaluation module is connected to the target area quantitative positioning module. It has a built-in AHP weighting system and fuzzy comprehensive evaluation model for the quantitative grading of geothermal field quality. The development solution recommendation module is connected to the quality comprehensive evaluation module. It has built-in assignment mode classification rules, development technology matching rules, and industry model matching rules, which are used to output adapted development technology and industry application solutions. The 3D visualization and interaction module is connected to the structure recognition and modeling module, the target area quantitative positioning module, the quality comprehensive evaluation module, and the development plan recommendation module, respectively, and is used for 3D rendering, interactive display of structure models, target area classification, evaluation results, and development plan data.

[0015] Optionally, the 3D visualization and interaction module is developed based on the Cesium framework and uses dynamic tileization, view frustum-driven scheduling, and hybrid caching technology to render spatial data. Specifically, it includes: the server dynamically tile-processes geospatial data and establishes a quadtree spatial index, and the client dynamically loads and schedules tile data based on view frustum parameters.

[0016] Optionally, an intelligent question-and-answer analysis module is also included. The intelligent question-and-answer analysis module is built on the retrieval-enhanced generation (RAG) technology. The retrieval link connects the geothermal multi-source professional database, the target area quantitative positioning module, the quality comprehensive evaluation module, and the development scheme recommendation module. It is used to receive natural language query commands, retrieve multi-source professional data and model calculation results, and automatically generate professional analysis reports on geothermal exploration, resource evaluation, and development planning.

[0017] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the intelligent positioning and classification method for geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation as described above.

[0018] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a method and system for intelligent positioning and classification of geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation, the beneficial effects of which are: 1) Theory-driven, precision-enhanced: For the first time, the "tectonic heat control theory" and "source-reservoir theory" have been systematically digitized and algorithmized, forming a complete technical chain from macroscopic structural identification to microscopic target area location. Through quantitative models such as the Qh index, a quantitative evaluation of the tectonic heat control effect has been achieved, significantly improving the scientificity and accuracy of target area location and reducing exploration risks; 2) Objective evaluation and unified standards: The innovative fuzzy comprehensive discrimination method effectively overcomes the subjectivity and arbitrariness of traditional methods by establishing a multi-dimensional and hierarchical evaluation index system and adopting objective weighting and fuzzy operation. It realizes standardized and repeatable automatic evaluation of geothermal field quality, and the results provide a reliable basis for prioritizing resource development. 3) Closed-loop decision-making and industry empowerment: This invention is not limited to resource evaluation, but extends further to development plan recommendations. By intelligently matching resource endowment (endowment mode, quality grade) with development technology and industrial applications, a closed-loop decision-making process of "resource positioning - quality evaluation - development suggestions" is formed, which strongly supports the scientific planning and efficient utilization of geothermal resources; 4) System Integration, Intelligent and Efficient: The integrated system combines multi-source heterogeneous data, professional analysis models, 3D visualization, and AI-powered intelligent question answering, realizing the transformation of geothermal resource management from "experience-driven" to "data and model-driven." This significantly improves the efficiency and intelligence level of exploration and evaluation work, providing core tools for the digital and refined development of the geothermal industry. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 A flowchart of the intelligent geothermal resource positioning and classification method based on multi-level structural heat control and fuzzy comprehensive evaluation provided by the present invention; Figure 2 This is a schematic diagram of the multi-level thermal control structure identification and modeling process provided by the present invention; Figure 3 A schematic diagram of the quantitative location (Qh index calculation) process for geothermal enrichment target areas provided by this invention; Figure 4 A schematic diagram of the fuzzy comprehensive evaluation process for the quality of hydrothermal geothermal fields provided by this invention; Figure 5 A schematic diagram of the intelligent recommendation process for the development and utilization model provided by this invention; Figure 6 The structural diagram of the intelligent geothermal resource positioning and classification system based on multi-level structural heat control and fuzzy comprehensive evaluation provided by the present invention; Figure 7 A planar distribution map of the geothermal field and secondary heat-controlling structures in the Niutuo Town uplift area of ​​the North China Basin, provided by this invention. Figure 8 This invention provides a schematic diagram of the geological profile of the three-level extensional fault in the Niubei slope. Figure 9 This is a longitudinal profile model of the multi-level tectonic thermal control of the deep heat column and shallow geothermal island group in the North China Basin, provided by the present invention. Detailed Implementation

[0021] 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.

[0022] See Figure 1 As shown, this invention discloses an intelligent location and classification method for geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation, including the following steps: S1. Construct a multi-source geothermal professional database; S2. By integrating multi-source geophysical and geological data, three types of heat-controlling structures are identified in a hierarchical manner: primary mantle fault structures, secondary crustal fault structures, and tertiary extensional fault structures. A three-dimensional geological model of multi-level heat-controlling structures is then constructed. S3. Calculate the geothermal enrichment index Qh by extracting structural parameters based on the three-dimensional geological model, and automatically delineate and classify the geothermal enrichment target area according to the Qh value. S4. Establish a multi-level evaluation index system for the quality of geothermal fields, and use the fuzzy comprehensive discrimination method to automatically evaluate the quality of the delineated target area or known geothermal fields, and output 5A, 4A and 3A levels. S5. Combine the geothermal field quality evaluation results to match the geothermal occurrence pattern, and match the most suitable development and utilization technology and industrial application direction based on the occurrence pattern.

[0023] Furthermore, the S1 geothermal multi-source professional database includes: data on large and medium-sized fault zones nationwide, hot spring data, full parameter data of geothermal wells, geophysical exploration data, geological structure data, hydrological and climatic data, and geothermal policy and regulatory documents; the full parameters of geothermal wells include: well depth, water temperature, water output, water quality, and historical mining data.

[0024] Further, see Figure 2 As shown, the specific content of S2 is as follows: S21. Use gravity anomaly data and seismic tomography data to conduct GIS spatial overlay analysis to identify the spatial distribution of first-order fault-mantle structures. S22. Identification of secondary fault structures based on controlled-source audio-frequency magnetotelluric sounding (CSAMT) profile data and magnetic data. S23. Identify third-order tensional fractures using high-resolution seismic exploration data and UAV aeromagnetic data; S24. Analyze the spatial topological relationships of multi-level structures, verify the structural connectivity through the resistivity vertical overlay method, and integrate and construct a three-dimensional geological structural model containing first-, second-, and third-level structures.

[0025] Further, see Figure 3As shown, the calculation formula of geothermal enrichment index Qh in S3 is:

[0026] wherein, is the thermal conductivity of the fault zone, is the geothermal gradient of the structural zone, is the area of the structural intersection area, is the structural connectivity coefficient; structural connectivity coefficient has the following assignment rules: when multi-level structures are directly connected =1.0; when the intersection angle of structures is less than 30° =0.8; when the isolated fault has no structural intersection =0.3.

[0027] Specifically, grading thresholds are set, and the target areas are automatically graded according to the calculated Qh value. For example: Qh>100 is a first-class target area (core enrichment area), 70<Qh≤100 is a second-class target area, and 50<Qh≤70 is a third-class target area.

[0028] Further, see Figure 4 As shown, the specific content of the fuzzy comprehensive discrimination method in S4 is: S41, constructing a quality evaluation system for hydrothermal geothermal fields including 5 first-level indicators and 15 second-level indicators, and calculating the weight vector of indicators at all levels by analytic hierarchy process AHP; Specifically, the first-level indicators include thermal reservoir conditions, mining conditions, water source conditions, heat source conditions and water quality conditions, and the 15 second-level indicators include thermal reservoir thickness, type, burial depth, lithology, geothermal gradient, water temperature, flow rate, distance from deep-large faults, total dissolved solids, etc.

[0029] S42, inputting the measured / deduced data of each secondary index of the geothermal field to be evaluated, and constructing an index membership degree matrix according to the preset 5A, 4A and 3A three-level evaluation standards; S43, performing fuzzy composition operation on the weight vector and the membership matrix to obtain a membership vector corresponding to the three-level quality grade; S44, calculating the comprehensive quality evaluation value M of the geothermal field based on the weighted scoring method, and determining the quality grade according to the preset threshold.

[0030] Specifically, preset thresholds are (for example, M>0.79 is grade 5A, 0.5<M≤0.79 is grade 4A, and M≤0.5 is grade 3A).

[0031] Further, the industrial application direction in S5 is selected from a preset five-modification industrial model library, and the five-modification industrial models include energy-based power generation, large-scale heating and cooling, professional cultural tourism and leisure, characteristic planting and breeding, and integrated health care and medical treatment.

[0032] For details, see Figure 5 As shown, the specific content of S5 is as follows: S51. Based on the geothermal reservoir characteristics and water source conditions of the geothermal field, determine the occurrence mode, which includes dual-source fracture-karst type, dual-source pore-tectonic type, dual-source karst type, and dual-source tectonic type.

[0033] S52. Based on the quality level obtained in S4 (especially key parameters such as temperature and water quality) and the storage mode determined in S51, the most suitable development and utilization technology is matched from the pre-set rule base. The development and utilization technologies include "heat extraction without water consumption and same-layer reinjection", "heat extraction without water extraction" and "direct utilization".

[0034] S53. Based on the temperature, water quality, location, and regional industrial planning of the geothermal field, recommend industrial application directions from the pre-set "five-fold" industrial model database. The "five-fold" model includes energy-based power generation, large-scale heating and cooling, specialized cultural tourism and leisure, distinctive planting and breeding, and integrated health and wellness medical care.

[0035] and Figure 1 Corresponding to the method described above, this invention also discloses an intelligent geothermal resource positioning and classification system based on multi-level structural heat control and fuzzy comprehensive evaluation, used for... Figure 1 For a detailed implementation of the method, please refer to its structure diagram. Figure 6 As shown, it includes: The data storage and management module is used to store and maintain the geothermal multi-source professional database; The structure identification and modeling module is connected to the data storage and management module to perform multi-level thermal control structure hierarchical identification, connectivity verification, and three-dimensional geological model construction. The target area quantitative positioning module is connected to the structure identification and modeling module. It has a built-in Qh index calculation model to complete the calculation of geothermal enrichment index and automatic target area delineation and classification. The quality comprehensive evaluation module is connected to the target area quantitative positioning module. It has a built-in AHP weighting system and fuzzy comprehensive evaluation model for the quantitative grading of geothermal field quality. The development solution recommendation module is connected to the quality comprehensive evaluation module. It has built-in assignment mode classification rules, development technology matching rules, and industry model matching rules, which are used to output adapted development technology and industry application solutions. The 3D visualization and interaction module is connected to the structure recognition and modeling module, the target area quantitative positioning module, the quality comprehensive evaluation module, and the development plan recommendation module, respectively, and is used for 3D rendering, interactive display of structure models, target area classification, evaluation results, and development plan data.

[0036] Furthermore, the 3D visualization and interaction module is developed based on the Cesium framework and uses dynamic tileization, view frustum-driven scheduling, and hybrid caching technology to realize spatial data rendering. Specifically, the server dynamically tiles the geospatial data and establishes a quadtree spatial index, while the client dynamically loads and schedules the tile data according to the view frustum parameters.

[0037] Furthermore, it also includes an intelligent question-and-answer analysis module; the intelligent question-and-answer analysis module is built on the retrieval enhancement generation RAG technology, and the retrieval link connects the geothermal multi-source professional database, the target area quantitative positioning module, the quality comprehensive evaluation module, and the development plan recommendation module. It is used to receive natural language query commands, retrieve multi-source professional data and model calculation results, and automatically generate professional analysis reports on geothermal exploration, resource evaluation, and development planning.

[0038] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the intelligent positioning and classification method for geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation as described above.

[0039] The implementation of this invention system is based on a database containing nationwide geothermal professional data. An example is the evaluation of the "Niutuo Town Uplift Geothermal Field in the Jizhong Depression," which identifies the primary structure as the "Lower Liaohe-North China Extensional Rift System." (See also...) Figure 7 The secondary structure identified is "Niu Tuo Town Protrusion" (see also...). Figure 8 The diagram shows the identification of the relevant third-order tensile fracture network; see also... Figure 9 A three-dimensional geological model of the three-level tectonic system of the region is constructed as shown, and its connectivity is analyzed.

[0040] S1. The system retrieves all relevant data for the region from the database, including gravity, magnetism, seismic data, drilling data, and hydrological data.

[0041] S2, the construction identification and modeling module runs.

[0042] S3. The target area quantitative positioning module operates, selecting the "Niutuo Town Uplift" structural unit in the 3D geological model. The module automatically associates the empirical value of the fracture thermal conductivity (K) of the area with borehole temperature data to calculate the geothermal gradient (ΔT / ΔL), calculates the uplift area (A) through spatial analysis, and assigns a connectivity coefficient (Φ) according to the structural model. Substituting into the Qh formula, a Qh value greater than 100 is obtained, and the system automatically marks it as a "Level 1 Target Area" and highlights it with a prominent color in the 3D scene.

[0043] S4, the comprehensive quality evaluation module is running.

[0044] Based on the existing exploration data of the target area, the system automatically fills in the values ​​of various secondary indicators: reservoir thickness (>200m), reservoir type (fractured / porous), water temperature (45-65℃), geothermal gradient (3.2-3.4℃ / 100m), flow rate (>60m³ / h), distance from Tanlu Fault (approximately 50km), total dissolved solids (1500mg / L), etc.

[0045] The module calls preset indicator weights (such as heat source condition weight 0.385, water source condition weight 0.304, etc.) and membership functions.

[0046] Perform fuzzy comprehensive calculation to obtain the membership vector R=[0.44,0.38,0.00] (example value).

[0047] The overall evaluation value is calculated to be M=0.90.

[0048] Since M>0.79, the system automatically outputs that the geothermal field is graded as "5A".

[0049] S5, Development Solution Recommendation Module Run.

[0050] Based on the fact that its reservoir consists of limestone (Wumishan Formation) and sandstone (Guantao Formation and Minghuazhen Formation) and has a stable water source, the system determines that its occurrence mode is "dual-source fracture-karst type (S-LY)".

[0051] Based on its 5A-level quality (especially good runoff conditions and water quality), the recommended development technology from the rule base is "heat extraction without water consumption, same-layer reinjection (H)".

[0052] Based on its temperature range (mainly medium and low temperatures) and location in a densely populated area, the recommended industry models from the "Five-fold" industry database are "Large-scale building heating and cooling applications (G)" and "Specialized cultural tourism and leisure applications (W)".

[0053] S6. All results (target area location, structural model, Qh value, quality grade, and recommended mode) are integrated and displayed in the "China Geothermal One Map" 3D scene through a 3D visualization and interactive module. Users can ask questions through the intelligent question-and-answer assessment module, such as "What is the development potential of the Niutuo Town geothermal field?" The system will automatically retrieve the result data generated in the above steps, organize the language, and generate a comprehensive assessment report including location, rating, and recommended scheme.

[0054] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the systems disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the descriptions are relatively simple; relevant parts can be referred to the method section.

[0055] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A geothermal resource intelligent positioning and grading method based on multi-level heat control and fuzzy comprehensive evaluation, characterized in that, Includes the following steps: S1. Construct a multi-source geothermal professional database; S2. By integrating multi-source geophysical and geological data, three types of heat-controlling structures are identified in a hierarchical manner: primary mantle fault structures, secondary crustal fault structures, and tertiary extensional fault structures. A three-dimensional geological model of multi-level heat-controlling structures is then constructed. S3. Calculate the geothermal enrichment index Qh by extracting structural parameters based on the three-dimensional geological model, and automatically delineate and classify the geothermal enrichment target area according to the Qh value. S4. Establish a multi-level evaluation index system for the quality of geothermal fields, and use the fuzzy comprehensive discrimination method to automatically evaluate the quality of the delineated target area or known geothermal fields, and output 5A, 4A and 3A levels. S5. Combine the geothermal field quality evaluation results to match the geothermal occurrence pattern, and match the most suitable development and utilization technology and industrial application direction based on the occurrence pattern.

2. The multi-level structure-based heat control and fuzzy comprehensive evaluation-based geothermal resource intelligent positioning and grading method according to claim 1, characterized in that, The S1 geothermal multi-source professional database includes: data on large and medium-sized fault zones nationwide, hot spring data, full parameter data of geothermal wells, geophysical exploration data, geological structure data, hydrological and climatic data, and geothermal policy and regulatory documents; the full parameters of geothermal wells include: well depth, water temperature, water output, water quality, and historical mining data.

3. The multi-level structure-based heat control and fuzzy comprehensive evaluation-based geothermal resource intelligent positioning and grading method according to claim 1, characterized in that, The specific content of S2 is as follows: S21. Use gravity anomaly data and seismic tomography data to conduct GIS spatial overlay analysis to identify the spatial distribution of first-order fault-mantle structures. S22. Identification of secondary fault structures based on controlled-source audio-frequency magnetotelluric sounding (CSAMT) profile data and magnetic data. S23. Identify third-order tensional fractures using high-resolution seismic exploration data and UAV aeromagnetic data; S24. Analyze the spatial topological relationships of multi-level structures, verify the structural connectivity through the resistivity vertical overlay method, and integrate and construct a three-dimensional geological structural model containing first-, second-, and third-level structures.

4. The multi-level structure-based heat control and fuzzy comprehensive evaluation-based geothermal resource intelligent positioning and grading method according to claim 1, characterized in that, The formula for calculating the geothermal enrichment index Qh in S3 is: wherein, is the thermal conductivity of the fault zone, is the geothermal gradient of the tectonic zone, is the area of the tectonic intersection zone, is the tectonic connectivity coefficient; Constructing connectivity coefficients The assignment rule is: when multi-level structures are directly connected. =1.0; When the intersection angle is less than 30°. =0.8; when an isolated fracture has no structural intersection =0.

3.

5. The multi-level structure-based heat control and fuzzy comprehensive evaluation-based geothermal resource intelligent positioning and grading method according to claim 1, characterized in that, The specific content of the fuzzy comprehensive discrimination method in S4 is as follows: S41. Construct a quality evaluation system for hydrothermal geothermal fields that includes 5 primary indicators and 15 secondary indicators, and use the analytic hierarchy process (AHP) to calculate the weight vectors of each level of indicators. S42. Input the measured / deduced data of each secondary indicator of the geothermal field to be evaluated, and construct the indicator membership matrix based on the preset 5A, 4A, and 3A three-level evaluation standards. S43. Perform fuzzy synthesis operation on the weight vector and the membership matrix to obtain the membership vector corresponding to the three quality levels; S44. Calculate the comprehensive quality evaluation value M of the geothermal field based on the weighted scoring method, and determine the quality level according to the preset threshold.

6. The multi-level structure-based heat control and fuzzy comprehensive evaluation-based geothermal resource intelligent positioning and grading method according to claim 1, characterized in that, In S5, the industrial application directions are selected from the preset five-industry model library. The five-industry models include energy-based power generation, large-scale heating and cooling, specialized cultural tourism and leisure, distinctive planting and breeding, and integrated health and wellness medical care.

7. The geothermal resource intelligent positioning and grading system based on multi-level heat control and fuzzy comprehensive evaluation, characterized in that The method for intelligent location and classification of geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation as described in any one of claims 1-6 includes: The data storage and management module is used to store and maintain the geothermal multi-source professional database; The structure identification and modeling module is connected to the data storage and management module to perform multi-level thermal control structure hierarchical identification, connectivity verification, and three-dimensional geological model construction. The target area quantitative positioning module is connected to the structure identification and modeling module. It has a built-in Qh index calculation model to complete the calculation of geothermal enrichment index and automatic target area delineation and classification. The quality comprehensive evaluation module is connected to the target area quantitative positioning module. It has a built-in AHP weighting system and fuzzy comprehensive evaluation model for the quantitative grading of geothermal field quality. The development solution recommendation module is connected to the quality comprehensive evaluation module. It has built-in assignment mode classification rules, development technology matching rules, and industry model matching rules, which are used to output adapted development technology and industry application solutions. The 3D visualization and interaction module is connected to the structure recognition and modeling module, the target area quantitative positioning module, the quality comprehensive evaluation module, and the development plan recommendation module, respectively, and is used for 3D rendering, interactive display of structure models, target area classification, evaluation results, and development plan data.

8. The multi-level configuration-based heat control and fuzzy comprehensive evaluation integrated geothermal resource intelligent positioning and grading system according to claim 7, characterized in that, The 3D visualization and interaction module is developed based on the Cesium framework and uses dynamic tileization, view frustum-driven scheduling, and hybrid caching technology to render spatial data. Specifically, the server dynamically tiles the geospatial data and establishes a quadtree spatial index, while the client dynamically loads and schedules the tile data based on the view frustum parameters.

9. The multi-level configuration-based heat control and fuzzy comprehensive evaluation integrated geothermal resource intelligent positioning and grading system according to claim 7, characterized in that, It also includes an intelligent question-and-answer analysis module; the intelligent question-and-answer analysis module is built on the retrieval enhancement generation RAG technology, and the retrieval link connects the geothermal multi-source professional database, the target area quantitative positioning module, the quality comprehensive evaluation module, and the development plan recommendation module. It is used to receive natural language query commands, retrieve multi-source professional data and model calculation results, and automatically generate professional analysis reports on geothermal exploration, resource evaluation, and development planning.

10. A computer readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the intelligent positioning and classification method for geothermal resources based on multi-level structural heat control and fuzzy comprehensive evaluation as described in any one of claims 1 to 6.

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