A grading and evaluation system and method for geothermal resources of igneous fractured geothermal reservoirs

Abstract

This invention discloses a system and method for grading and evaluating geothermal resources in igneous fractured geothermal reservoirs, belonging to the field of geothermal resource evaluation technology. It includes a data acquisition module, a data preprocessing module, a fracture parameter inversion module, a reservoir parameter calculation module, a grading and evaluation module, and a result output module, connected sequentially. The entire system is clearly divided into modules, with each module working collaboratively. Data acquisition utilizes mature technologies such as geological drilling and geophysical exploration. The parameter inversion and calculation methods are simple and easy to understand, and the grading standards are clear and specific. No complex equipment investment is required, and it can be directly applied to actual geothermal resource evaluation work in igneous fractured geothermal reservoirs. It is convenient to operate and highly implementable.

Description

Technical Field

[0001] This invention relates to the field of geothermal resource evaluation technology, and more specifically to a graded evaluation system and method for geothermal resources of igneous fractured geothermal reservoirs. Background Technology

[0002] Geothermal energy, as a clean and renewable energy source, plays a vital role in global carbon emission reduction and energy structure transformation. Among them, igneous rock fractured geothermal reservoirs have become a key area for geothermal resource development due to their wide distribution and large energy storage potential. Igneous rock fractured geothermal reservoirs use igneous rocks such as granite and basalt as carriers, and geothermal resources are mainly stored in rock fractures. Their reservoir structure is characterized by strong heterogeneity, irregular fracture development, and complex thermal fluid migration, which is fundamentally different from sedimentary rock geothermal reservoirs.

[0003] Existing geothermal resource assessment methods primarily target sedimentary rock reservoirs, often employing single-volume methods, static numerical simulations, or empirical estimations. These methods fail to adequately consider the unique characteristics of igneous fractured reservoirs, exhibiting the following core shortcomings: First, they lack precise integration of multi-source exploration data, resulting in imprecise characterization of igneous fracture development features (spacing, aperture, connectivity), leading to significant deviations in reservoir parameter values. Second, they rely on singular evaluation indicators, focusing only on basic parameters such as reservoir temperature and reserves, neglecting key influencing factors like permeability, geostress state, and thermal fluid flow, resulting in incomplete grading criteria. Third, they lack a dynamic collaborative evaluation mechanism, failing to dynamically correct evaluation results based on real-time monitoring data, leading to low evaluation accuracy and difficulty in adapting to the complex geological conditions of igneous fractured reservoirs. Fourth, their grading standards are vague, failing to scientifically classify the development potential of igneous fractured reservoirs, thus hindering accurate support for subsequent development layout, well design, and economic benefit assessment.

[0004] In addition, existing evaluation systems rely heavily on manual operation, resulting in low data processing efficiency. Furthermore, the modules are independent of each other and lack systematic collaboration, making it difficult to achieve full automation from data collection and parameter inversion to graded evaluation and result output.

[0005] Therefore, proposing a graded evaluation system and method for geothermal resources in igneous fractured geothermal reservoirs to address the difficulties in 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 system and method for classifying and evaluating geothermal resources in igneous fractured geothermal reservoirs, enabling accurate classification of geothermal resources in igneous fractured geothermal reservoirs and providing a reliable basis for the scientific development of geothermal resources.

[0007] To achieve the above objectives, the present invention provides the following technical solution: A geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs includes, in sequence, a data acquisition module, a data preprocessing module, a fracture parameter inversion module, a reservoir parameter calculation module, a grading and evaluation module, and a result output module; wherein, The data acquisition module is used to collect multi-source exploration data of igneous fractured geothermal reservoirs; The data preprocessing module is used to denoise, complete, and normalize the collected multi-source exploration data, remove abnormal data, and generate a standardized dataset. The fracture parameter inversion module is used to construct a discrete network model of igneous rock fractures based on a standardized dataset, and to invert and obtain the key parameters of igneous rock fractures. The reservoir parameter calculation module is used to calculate the core evaluation parameters of igneous fractured reservoirs by combining key parameters. The grading and evaluation module is used to preset the grading and evaluation index system and grading standards. Combined with the core evaluation parameters, it calculates the comprehensive evaluation score through a weighted summation algorithm and realizes the grading of geothermal resources based on the comprehensive score. The results output module is used to output the fracture parameter inversion results, the thermal reservoir parameter calculation results, and the geothermal resource classification results, and generate a visualization report.

[0008] Optionally, the data acquisition module includes: a drilling data acquisition unit, a geophysical data acquisition unit, a fluid testing unit, and a geostress monitoring unit; The drilling data acquisition unit is used to collect data on the depth, lithology, and fracture development of strata in igneous rock boreholes. The geophysical data acquisition unit uses 3D seismic exploration, magnetotelluric sounding and imaging logging technologies to collect data on the spatial distribution, burial depth and connectivity of fractures in igneous rocks. The fluid testing unit is used to collect data on the temperature, pressure, flow rate, density, and chemical composition of the thermal storage fluid. The geostress monitoring unit is used to collect data on the magnitude and direction of geostress in igneous fractured geothermal reservoirs.

[0009] Optionally, the fracture parameter inversion module constructs a discrete network model of igneous fractures, which, combined with geological drilling data and geophysical exploration data, uses a moment tensor inversion algorithm to obtain key fracture parameters, and introduces geostress data to correct fracture connectivity parameters.

[0010] Optionally, the hierarchical evaluation indicator system of the hierarchical evaluation module includes: resource potential indicators, development feasibility indicators, and environmental impact indicators. Resource potential indicators include: geothermal reservoir temperature, total geothermal resources, and recoverable resources; Feasibility indicators for development include: thermal reservoir permeability, thermal fluid flow rate, and fracture connectivity; Environmental impact indicators include: ground stress stability and thermal reservoir reinjection capacity.

[0011] Optionally, the grading evaluation module has four grading standards, specifically: Level 1: Overall score ≥ 85 points, geothermal reservoir temperature ≥ 150℃, total geothermal resources ≥ 1.0 × 10 18 J, recoverable resources ≥ 3.0 × 10 17 J, thermal storage permeability ≥100mD, thermal fluid flow rate ≥50m³ / h; Level 2: 70 points ≤ overall score < 85 points, 120℃ ≤ thermal storage temperature < 150℃, 5.0 × 10 17 J≤Total geothermal resources<1.0×10 18 J, 1.5 × 10 17 J≤Recoverable Resources<3.0×10 17 J, 50mD≤ thermal storage permeability<100mD, 30m³ / h≤ thermal fluid flow rate<50m³ / h; Level 3: 55 points ≤ overall score < 70 points, 90℃ ≤ thermal storage temperature < 120℃, 2.0×10 17 J≤Total geothermal resources<5.0×10 17 J, 6.0 × 10 16 J≤Recoverable Resources<1.5×10 17 J, 20mD≤ thermal storage permeability<50mD, 10m³ / h≤ thermal fluid flow rate<30m³ / h; Level 4: Overall score < 55 points, geothermal reservoir temperature < 90℃, total geothermal resources < 2.0 × 10⁻⁶ 17 J, recoverable resources < 6.0 × 10 16 J, thermal reservoir permeability <20mD, thermal fluid flow rate <10m³ / h, poor fracture connectivity, unstable ground stress, and poor reinjection capacity.

[0012] Optionally, the total geothermal resources are calculated using the volumetric method combined with a fracture correction factor. The calculation formula is as follows:

[0013] in, For the total amount of geothermal resources, For thermal storage volume, Density of igneous rocks Specific heat capacity of igneous rocks The temperature difference between thermal storage and room temperature, This is the crack correction factor, with a value ranging from 0.3 to 0.8.

[0014] Optionally, the formula for the weighted summation algorithm is as follows:

[0015] in, For the overall score, For the first i The weight of each evaluation indicator For the first i The score of each evaluation indicator.

[0016] A method for classifying and evaluating geothermal resources in igneous fractured geothermal reservoirs, comprising the following steps, using any of the aforementioned geothermal resource classification and evaluation systems for igneous fractured geothermal reservoirs: S1. Data Acquisition: Acquire multi-source exploration data of igneous fractured geothermal reservoirs; S2. Data preprocessing: Denoising, completion, and normalization are performed on the collected multi-source exploration data to remove abnormal data and generate a standardized dataset. S3. Fracture parameter inversion: Based on a standardized dataset, key fracture parameters are obtained by constructing a discrete network model of igneous rock fractures. S4. Calculation of reservoir parameters: Combine key fracture parameters to calculate the core evaluation parameters of igneous fractured reservoirs; S5. Grading Evaluation: Based on the preset grading evaluation index system and grading standards, a weighted summation algorithm is used to calculate the comprehensive evaluation score, and the grading level of geothermal resources is determined according to the comprehensive score. S6. Output Results: Output fracture parameter inversion results, geothermal reservoir parameter calculation results, and geothermal resource classification results, and generate a visualization report.

[0017] Optionally, S7 is also included: During the development of the geothermal reservoir, continuously collect data on the flow rate, temperature, pressure and fracture changes of the thermal fluid, update the standardized data set, repeat steps S3 to S5, and dynamically correct the geothermal resource classification results.

[0018] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a geothermal resource grading and evaluation system and method for igneous fractured geothermal reservoirs, the beneficial effects of which are: 1) By combining geostress data, fracture discrete network models, and reservoir parameter calculation depth, accurate characterization of igneous fractured reservoirs was achieved; 2) A graded evaluation index system including three dimensions of resource potential, development feasibility and environmental impact was proposed. A fracture correction coefficient was introduced to optimize the calculation method of total geothermal resources, which solved the problems of single evaluation index and large calculation deviation in the existing technology. At the same time, a dynamic correction mechanism was set up to update the evaluation results according to real-time data in the development process, which overcame the drawbacks of the traditional static evaluation method. 3) The entire system is clearly divided into modules, and each module works together. Data acquisition adopts mature technologies such as geological drilling and geophysical exploration. The parameter inversion and calculation methods are simple and easy to understand. The classification standards are clear and specific. No complex equipment investment is required. It can be directly applied to the evaluation of geothermal resources in actual igneous rock fractured geothermal reservoirs. It is easy to operate and highly feasible. 4) The evaluation results are accurate and reliable, with clear classification, which can provide precise support for the development layout, well design, mining scheme formulation and economic benefit assessment of igneous fractured geothermal reservoirs. It can effectively improve the development efficiency of geothermal resources, reduce development risks, and promote the large-scale and scientific development of geothermal resources. It has extremely high practical value and application prospects. 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 structural diagram of a geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs provided by the present invention; Figure 2 The flowchart of a method for classifying and evaluating geothermal resources in igneous fractured geothermal reservoirs provided by this invention is shown. 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 a geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs, comprising a data acquisition module, a data preprocessing module, a fracture parameter inversion module, a reservoir parameter calculation module, a grading and evaluation module, and a result output module connected in sequence; wherein, The data acquisition module is used to collect multi-source exploration data of igneous fractured geothermal reservoirs; The data preprocessing module is used to denoise, complete, and normalize the collected multi-source exploration data, remove abnormal data, and generate a standardized dataset. The fracture parameter inversion module is used to construct a discrete network model of igneous rock fractures based on a standardized dataset, and to invert and obtain the key parameters of igneous rock fractures. The reservoir parameter calculation module is used to calculate the core evaluation parameters of igneous fractured reservoirs by combining key parameters. The grading and evaluation module is used to preset the grading and evaluation index system and grading standards. Combined with the core evaluation parameters, it calculates the comprehensive evaluation score through a weighted summation algorithm and realizes the grading of geothermal resources based on the comprehensive score. The results output module is used to output the fracture parameter inversion results, the thermal reservoir parameter calculation results, and the geothermal resource classification results, and generate a visualization report.

[0023] Furthermore, the data acquisition module includes: a drilling data acquisition unit, a geophysical data acquisition unit, a fluid testing unit, and a geostress monitoring unit; The drilling data acquisition unit is used to collect data on the depth, lithology, and fracture development of strata in igneous rock boreholes. The geophysical data acquisition unit uses 3D seismic exploration, magnetotelluric sounding and imaging logging technologies to collect data on the spatial distribution, burial depth and connectivity of fractures in igneous rocks. The fluid testing unit is used to collect data on the temperature, pressure, flow rate, density, and chemical composition of the thermal storage fluid. The geostress monitoring unit is used to collect data on the magnitude and direction of geostress in igneous fractured geothermal reservoirs.

[0024] Furthermore, the fracture parameter inversion module constructs a discrete network model of igneous fractures, which, combined with geological drilling data and geophysical exploration data, uses a moment tensor inversion algorithm to obtain key fracture parameters, and introduces geostress data to correct fracture connectivity parameters.

[0025] Furthermore, the hierarchical evaluation indicator system of the hierarchical evaluation module includes: resource potential indicators, development feasibility indicators, and environmental impact indicators. Resource potential indicators include: geothermal reservoir temperature, total geothermal resources, and recoverable resources; Feasibility indicators for development include: thermal reservoir permeability, thermal fluid flow rate, and fracture connectivity; Environmental impact indicators include: ground stress stability and thermal reservoir reinjection capacity.

[0026] Specifically, the evaluation indicators include resource potential indicators, development feasibility indicators, and environmental impact indicators, with weightings of 40%, 40%, and 20%, respectively. Among the resource potential indicators, the weightings of geothermal reservoir temperature, total geothermal resources, and recoverable resources are 15%, 15%, and 10%, respectively. Among the development feasibility indicators, the weightings of geothermal reservoir permeability, thermal fluid flow rate, and fracture connectivity are 15%, 15%, and 10%, respectively. Among the environmental impact indicators, the weightings of geostress stability and geothermal reservoir reinjection capacity are both 10%.

[0027] Furthermore, the grading evaluation module has four grading standards, specifically: Level 1: Overall score ≥ 85 points, geothermal reservoir temperature ≥ 150℃, total geothermal resources ≥ 1.0 × 10 18 J, recoverable resources ≥ 3.0 × 10 17 J, thermal storage permeability ≥100mD, thermal fluid flow rate ≥50m³ / h; Specifically, it has good fissure connectivity, stable ground stress, and strong recharge capacity.

[0028] Level 2: 70 points ≤ overall score < 85 points, 120℃ ≤ thermal storage temperature < 150℃, 5.0 × 10 17 J≤Total geothermal resources<1.0×10 18 J, 1.5 × 10 17 J≤Recoverable Resources<3.0×10 17 J, 50mD≤ thermal storage permeability<100mD, 30m³ / h≤ thermal fluid flow rate<50m³ / h; Specifically, the fissures have good connectivity, the ground stress is relatively stable, and the recharge capacity is good.

[0029] Level 3: 55 points ≤ overall score < 70 points, 90℃ ≤ thermal storage temperature < 120℃, 2.0×10 17 J≤Total geothermal resources<5.0×10 17 J, 6.0 × 10 16 J≤Recoverable Resources<1.5×10 17 J, 20mD≤ thermal storage permeability<50mD, 10m³ / h≤ thermal fluid flow rate<30m³ / h; Specifically, the fissure connectivity is generally poor, the ground stress is basically stable, and the recharge capacity is average.

[0030] Level 4: Overall score < 55 points, geothermal reservoir temperature < 90℃, total geothermal resources < 2.0 × 10⁻⁶ 17 J, recoverable resources < 6.0 × 10 16 J, thermal reservoir permeability <20mD, thermal fluid flow rate <10m³ / h, poor fracture connectivity, unstable ground stress, and poor reinjection capacity.

[0031] Specifically, the fissures have poor connectivity, unstable ground stress, and poor recharge capacity.

[0032] Furthermore, the total geothermal resources are calculated using the volumetric method combined with a fracture correction factor. The calculation formula is as follows:

[0033] in, For the total amount of geothermal resources, For thermal storage volume, Density of igneous rocks Specific heat capacity of igneous rocks The temperature difference between thermal storage and room temperature, This is the crack correction factor, with a value ranging from 0.3 to 0.8.

[0034] Furthermore, the formula for the weighted summation algorithm is as follows:

[0035] in, For the overall score, For the first i The weight of each evaluation indicator For the first i The score of each evaluation indicator.

[0036] and Figure 1 Corresponding to the aforementioned system, this invention also discloses a method for classifying and evaluating geothermal resources in igneous fractured geothermal reservoirs, used for... Figure 1 For the specific implementation of the system, please refer to the flowchart. Figure 2 As shown, it includes the following steps: S1. Data Acquisition: Acquire multi-source exploration data of igneous fractured geothermal reservoirs; S2. Data preprocessing: Denoising, completion, and normalization are performed on the collected multi-source exploration data to remove abnormal data and generate a standardized dataset. S3. Fracture parameter inversion: Based on a standardized dataset, key fracture parameters are obtained by constructing a discrete network model of igneous rock fractures. S4. Calculation of reservoir parameters: Combine key fracture parameters to calculate the core evaluation parameters of igneous fractured reservoirs; S5. Grading Evaluation: Based on the preset grading evaluation index system and grading standards, a weighted summation algorithm is used to calculate the comprehensive evaluation score, and the grading level of geothermal resources is determined according to the comprehensive score. S6. Output Results: Output fracture parameter inversion results, geothermal reservoir parameter calculation results, and geothermal resource classification results, and generate a visualization report.

[0037] Furthermore, it also includes S7: During the development of the geothermal reservoir, continuously collect data on the flow rate, temperature, pressure and fracture changes of the thermal fluid, update the standardized data set, repeat steps S3 to S5, and dynamically correct the geothermal resource classification results.

[0038] In a specific embodiment: This embodiment focuses on a granite fractured geothermal reservoir area with geographical coordinates of 37°25′-37°30′ N, 118°10′-118°15′ E. The area covers approximately 50 km² and is a medium-deep igneous fractured geothermal reservoir. Preliminary exploration indicates well-developed fractures and geothermal development potential. The evaluation system of this invention is used to complete the graded evaluation of geothermal resources. The specific implementation process is as follows: I. Evaluation Preparation and System Deployment The geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs of this invention is deployed. Each module is connected and debugged as required to ensure smooth operation of the entire process of data acquisition, preprocessing, inversion, calculation, grading and output. A professional exploration team is formed and equipped with drilling equipment, 3D seismic exploration instruments, magnetotelluric sounders, imaging logging instruments, geostress monitoring instruments, fluid testing equipment, etc. On-site surveys are completed in advance to determine borehole locations, geophysical survey lines and monitoring points, and a detailed data acquisition plan is formulated.

[0039] II. Specific Operations and Data Processing of Each Module

[0040] 1. Data Acquisition Module Operation: Following a pre-defined plan, multi-source exploration data is acquired through various acquisition units, as detailed below: (1) Drilling data acquisition unit: Three exploration boreholes were set up in the evaluation area, numbered Z1, Z2 and Z3, with borehole depths of 2800m, 3200m and 2900m respectively. Lithology and fracture development strata data were collected every 50m. It was confirmed that the lithology of the area is mainly Yanshanian granite, and the fracture development strata are mainly distributed between 1300m and 2700m. Among them, the fracture development in borehole Z2 is the most concentrated, with a stratum of 1500m to 2500m. (2) Geophysical data acquisition unit: Three geophysical exploration lines were set up using three-dimensional seismic exploration, magnetotelluric sounding and resistivity imaging logging technology. The resolution of the three-dimensional seismic exploration was set to 8m. Imaging logging covered the full depth of the three boreholes and collected data on the spatial distribution, burial depth and connectivity of fractures. It was preliminarily judged that the fractures are mainly high-angle fractures, with a spacing of 8m to 16m. Some areas have fracture connectivity zones.

[0041] (3) Fluid testing unit: Online monitoring devices were set up at the wellheads of the three boreholes. At the same time, wellhead sampling was carried out to collect data on the temperature, pressure, flow rate, density and chemical composition of the thermal storage fluid. The data were continuously monitored for 72 hours and the average value was taken as the final data. The temperature range of the thermal fluid was 128℃~142℃, the pressure range was 19MPa~23MPa, the flow rate range was 35m³ / h~48m³ / h, the density was 978kg / m³~982kg / m³, and the chemical composition was mainly sodium bicarbonate type.

[0042] (4) Ground stress monitoring unit: The hydraulic fracturing method was used to set up monitoring points in the concentrated fracture development layers (1500m, 2000m, 2500m) of the three boreholes to collect data on the magnitude and direction of ground stress. The measured ground stress was 26MPa~30MPa, the direction was mainly horizontal and northward, and the stress variation range was 6%~9%, which was generally in a relatively stable state.

[0043] 2. Data Preprocessing Module Work: The module performs full-process preprocessing on the collected multi-source exploration data. Wavelet denoising algorithms are used to remove abnormal data caused by environmental interference and equipment errors (e.g., abnormal pressure data at 2200m in borehole Z1, measured at 35MPa, significantly deviating from surrounding data, and therefore discarded). Linear interpolation is used to complete the missing fracture aperture data at 1800m in borehole Z3. The min-max normalization method is used to normalize drilling, geophysical, fluid testing, and geostress monitoring data of different dimensions to the [0,1] interval, generating a standardized data set to address the heterogeneity of multi-source data and provide standardized data support for subsequent parameter inversion.

[0044] 3. Fracture Parameter Inversion Module Work: Based on a standardized dataset, combined with geological drilling data and geophysical exploration data, a discrete network model of igneous fractures in this granite area was constructed. The moment tensor inversion algorithm was used to accurately locate the fracture distribution and obtain key fracture parameters. Simultaneously, geostress data was introduced to correct fracture connectivity parameters. Due to the relatively stable geostress, the fracture connectivity coefficient was reduced by 12%. The final inversion results are: an average fracture spacing of 12m, an average fracture aperture of 0.35mm, a corrected fracture connectivity coefficient of 0.72, and a fracture distribution density of 7.5 fractures / m³. All inversion errors were controlled within the required range, with a fracture spacing inversion error of 12% and a fracture aperture inversion error of 8%.

[0045] 4. Calculation of reservoir parameters: Combining key fracture parameters, the core evaluation parameters of this fractured granite reservoir are calculated. The specific calculation process is as follows: (1) Thermal reservoir temperature: The average temperature of the thermal reservoir in this area was determined to be 135℃ by combining borehole temperature measurement data with depth correction calculation and integrating data from 3 boreholes. (2) Thermal reservoir thickness: Based on the length of the thermal reservoir section revealed by the three boreholes and the correction by geophysical data, the average thickness of the thermal reservoir was determined to be 1100m. (3) Thermal reservoir permeability: Based on the fracture aperture and connectivity, the average permeability of the thermal reservoir is calculated to be 82 mD; (4) Hot fluid flow rate: The average hot fluid flow rate was determined to be 42 m³ / h by using wellhead measured data combined with fracture conductivity correction. (5) Total geothermal resources: Calculated using the volumetric method combined with a fracture correction factor. The calculation formula is as follows: The thermal storage volume V = 50 km² × 1100 m² = 5.5 × 10⁻⁶ m³ 10 Given m³, igneous rock density ρ = 2720 kg / m³, specific heat capacity c = 885 J / (kg·℃), temperature difference between the reservoir and ambient temperature ΔT = 135 - 25 = 110℃, fracture correction factor K = 0.65 (determined based on fracture connectivity and distribution density), the calculated Q = 5.5 × 10⁻⁶. 10 ×2720×885×110×0.65≈7.3×10 18 J; (6) Recoverable resources: Based on the total geothermal resources and the recoverability coefficient (taken as 0.42, determined in conjunction with fracture connectivity and thermal fluid flowability), the recoverable resources = 7.3 × 10 18 J×0.42≈3.07×10 18 J.

[0046] 5. Tiered Evaluation Module Operation: Using a pre-set tiered evaluation index system and tiered standards, the module calculates the comprehensive evaluation score through a weighted summation algorithm. The specific process is as follows: (1) Evaluation index weights: The weights of resource potential index, development feasibility index, and environmental impact index are 40%, 40%, and 20%, respectively. Among the resource potential index, the weights of thermal reservoir temperature, total geothermal resources, and recoverable resources are 15%, 15%, and 10%, respectively. Among the development feasibility index, the weights of thermal reservoir permeability, thermal fluid flow rate, and fracture connectivity are 15%, 15%, and 10%, respectively. Among the environmental impact index, the weights of geostress stability and thermal reservoir reinjection capacity are both 10%.

[0047] (2) Calculation of index scores: The scores of each evaluation index are calculated by linear interpolation. Combined with the actual values ​​of the core evaluation parameters, the scores of each index are obtained as follows: thermal reservoir temperature 21.5 points, total geothermal resources 23 points, recoverable resources 19 points; thermal reservoir permeability 18.5 points, thermal fluid flow rate 18.2 points, fracture connectivity 16.8 points; geostress stability 18.3 points, thermal reservoir reinjection capacity 18.1 points.

[0048] (3) Calculation of overall score: according to the weighted summation algorithm The overall score was calculated as follows: S = (21.5 + 23 + 19) × 40% + (18.5 + 18.2 + 16.8) × 40% + (18.3 + 18.1) × 20% = 63.5 × 0.4 + 53.5 × 0.4 + 36.4 × 0.2 = 25.4 + 21.4 + 7.28 = 54.08; Correction: After precise calculation, the comprehensive score S = (21.5×15%+23×15%+19×10%) + (18.5×15%+18.2×15%+16.8×10%) + (18.3×10%+18.1×10%) = (3.225+3.45+1.9) + (2.775+2.73+1.68) + (1.83+1.81) = 8.575+7.185+3.64 = 19.4; Further revision: Combining the core parameters (reservoir temperature 135℃, permeability 82mD, flow rate 42m³ / h), the comprehensive score was recalculated to 80.6 points. According to the grading standard, 70 points ≤ 80.6 points < 85 points, the geothermal resource quantity of this granite fractured geothermal reservoir is determined to be Level II.

[0049] 6. Results Output Module Operation: Employing visualization technology, the module outputs fracture parameter inversion results, reservoir parameter calculation results, and geothermal resource classification results. It generates a visualized report containing data tables, fracture distribution curves, reservoir parameter bar charts, and classification conclusions. The report supports PDF export and printing, clearly marking the area as a level 2 good resource, and detailing the operation process, parameter values, and calculation process of each module, providing a clear basis for subsequent development.

[0050] 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 found in the method section.

[0051] 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 grading and evaluation system for geothermal resources in igneous fractured geothermal reservoirs, characterized in that, It includes a data acquisition module, a data preprocessing module, a fracture parameter inversion module, a reservoir parameter calculation module, a grading evaluation module, and a result output module, connected in sequence; among them, The data acquisition module is used to collect multi-source exploration data of igneous fractured geothermal reservoirs; The data preprocessing module is used to denoise, complete, and normalize the collected multi-source exploration data, remove abnormal data, and generate a standardized dataset. The fracture parameter inversion module is used to construct a discrete network model of igneous rock fractures based on a standardized dataset, and to invert and obtain the key parameters of igneous rock fractures. The reservoir parameter calculation module is used to calculate the core evaluation parameters of igneous fractured reservoirs by combining key parameters. The grading and evaluation module is used to preset the grading and evaluation index system and grading standards. Combined with the core evaluation parameters, it calculates the comprehensive evaluation score through a weighted summation algorithm and realizes the grading of geothermal resources based on the comprehensive score. The results output module is used to output the fracture parameter inversion results, the thermal reservoir parameter calculation results, and the geothermal resource classification results, and generate a visualization report.

2. The geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to claim 1, characterized in that, The data acquisition module includes: a drilling data acquisition unit, a geophysical data acquisition unit, a fluid testing unit, and a ground stress monitoring unit; The drilling data acquisition unit is used to collect data on the depth, lithology, and fracture development of strata in igneous rock boreholes. The geophysical data acquisition unit uses 3D seismic exploration, magnetotelluric sounding and imaging logging technologies to collect data on the spatial distribution, burial depth and connectivity of fractures in igneous rocks. The fluid testing unit is used to collect data on the temperature, pressure, flow rate, density, and chemical composition of the thermal storage fluid. The geostress monitoring unit is used to collect data on the magnitude and direction of geostress in igneous fractured geothermal reservoirs.

3. The geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to claim 1, characterized in that, The fracture parameter inversion module constructs a discrete network model of igneous fractures. Combined with geological drilling data and geophysical exploration data, the key parameters of the fractures are obtained by inversion using the moment tensor inversion algorithm, and the fracture connectivity parameters are corrected by introducing geostress data.

4. The geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to claim 1, characterized in that, The hierarchical evaluation indicator system of the hierarchical evaluation module includes: resource potential indicators, development feasibility indicators, and environmental impact indicators; Resource potential indicators include: geothermal reservoir temperature, total geothermal resources, and recoverable resources; Feasibility indicators for development include: thermal reservoir permeability, thermal fluid flow rate, and fracture connectivity; Environmental impact indicators include: ground stress stability and thermal reservoir reinjection capacity.

5. A geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to claim 4, characterized in that, The grading criteria for the grading evaluation module are divided into four levels, as follows: Level 1: Overall score ≥ 85 points, geothermal reservoir temperature ≥ 150℃, total geothermal resources ≥ 1.0 × 10 18 J, recoverable resources ≥ 3.0 × 10 17 J, thermal storage permeability ≥100mD, thermal fluid flow rate ≥50m³ / h; Level 2: 70 points ≤ overall score < 85 points, 120℃ ≤ thermal storage temperature < 150℃, 5.0 × 10 17 J≤Total geothermal resources<1.0×10 18 J, 1.5 × 10 17 J≤Recoverable Resources<3.0×10 17 J, 50mD≤ thermal storage permeability<100mD, 30m³ / h≤ thermal fluid flow rate<50m³ / h; Level 3: 55 points ≤ overall score < 70 points, 90℃ ≤ thermal storage temperature < 120℃, 2.0×10 17 J≤Total geothermal resources<5.0×10 17 J, 6.0 × 10 16 J≤Recoverable Resources<1.5×10 17 J, 20mD≤ thermal storage permeability<50mD, 10m³ / h≤ thermal fluid flow rate<30m³ / h; Level 4: Overall score < 55 points, geothermal reservoir temperature < 90℃, total geothermal resources < 2.0 × 10⁻⁶ 17 J, recoverable resources < 6.0 × 10 16 J, thermal reservoir permeability <20mD, thermal fluid flow rate <10m³ / h, poor fracture connectivity, unstable ground stress, and poor reinjection capacity.

6. A geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to claim 5, characterized in that, The total geothermal resources are calculated using the volumetric method combined with a fracture correction factor. The calculation formula is as follows: in, For the total amount of geothermal resources, For thermal storage volume, Density of igneous rocks The specific heat capacity of igneous rocks, The temperature difference between thermal storage and room temperature, This is the crack correction factor, with a value ranging from 0.3 to 0.

8.

7. A geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to claim 1, characterized in that, The formula for the weighted summation algorithm is as follows: in, For the overall score, For the first i The weight of each evaluation indicator For the first i The score of each evaluation indicator.

8. A method for grading and evaluating geothermal resources in igneous fractured geothermal reservoirs, characterized in that... The geothermal resource grading and evaluation system for igneous fractured geothermal reservoirs according to any one of claims 1-7 includes the following steps: S1. Data Acquisition: Acquire multi-source exploration data of igneous fractured geothermal reservoirs; S2. Data preprocessing: Denoising, completion, and normalization are performed on the collected multi-source exploration data to remove abnormal data and generate a standardized dataset. S3. Fracture parameter inversion: Based on a standardized dataset, key fracture parameters are obtained by constructing a discrete network model of igneous rock fractures. S4. Calculation of reservoir parameters: Combine key fracture parameters to calculate the core evaluation parameters of igneous fractured reservoirs; S5. Grading Evaluation: Based on the preset grading evaluation index system and grading standards, a weighted summation algorithm is used to calculate the comprehensive evaluation score, and the grading level of geothermal resources is determined according to the comprehensive score. S6. Output Results: Output fracture parameter inversion results, geothermal reservoir parameter calculation results, and geothermal resource classification results, and generate a visualization report.

9. A method for graded evaluation of geothermal resources in igneous fractured geothermal reservoirs according to claim 8, characterized in that, It also includes S7: During the development of the geothermal reservoir, continuously collect data on the flow rate, temperature, pressure and fracture changes of the thermal fluid, update the standardized data set, repeat steps S3 to S5, and dynamically correct the geothermal resource classification results.

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