Geothermal resource grade evaluation method based on spatial analysis

Abstract

The invention discloses a geothermal resource grade evaluation method based on spatial analysis, and relates to the technical field of geothermal resource grade evaluation. Comprising the following steps: acquiring geothermal field exploration data, determining an evaluation factor grade threshold value, establishing an evaluation factor distribution model, selecting a spatial analysis platform, performing spatial attribute analysis on the evaluation factor distribution model on the spatial analysis platform, and forming a spatial attribute analysis unit; and performing meshing division on the spatial attribute analysis units, and calculating an evaluation result value Si grade partition for each spatial attribute analysis unit i. The method has the beneficial effects that grade classification can be quickly and effectively performed on the geothermal fields in different regions through analysis of the spatial analysis platform, the higher the grade is, the higher the mining value is, and the geothermal fields can be preferentially mined.

Description

Technical Field

[0001] The present invention relates to the technical field of geothermal resource grade evaluation, and more particularly to a geothermal resource grade evaluation method based on spatial analysis. Background Art

[0002] A geothermal field is a structure occupying a certain spatial location in the Earth's crust, containing aquifers, and possessing physical properties such as temperature, pressure, and phase state that can be exploited within a reasonable depth by drilling wells;

[0003] The evaluation of geothermal fields requires multiple data factors, such as reservoir lithology, burial depth, temperature, flow rate, and water quality. In addition, the geographical distribution of different regions is different, resulting in extremely different data and a large amount of information. In order to prioritize the exploitation of geothermal fields with stable heat reserves and large scale, manual verification is often required step by step, and it is impossible to quickly and effectively grade geothermal fields. Therefore, a method that can quickly evaluate the grade of geothermal resources is needed. Summary of the Invention

[0004] In view of the above defects, the present invention provides a geothermal resource grade evaluation method based on spatial analysis to solve the above problems.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] The geothermal resource grade evaluation method based on spatial analysis includes the following steps:

[0007] 1) Obtain geothermal field exploration data, including reservoir lithology, burial depth, drillability, temperature, flow rate, and water quality characteristics;

[0008] 2) Determine the evaluation factor level thresholds (R1, R2, R3, R4, R5);

[0009] Establish an evaluation factor distribution model, including geothermal mining conditions Y1, heat storage stability Y2, groundwater temperature Y3, groundwater flow Y4, and groundwater quality Y5;

[0010] 3) Select MAPGIS series as the spatial analysis platform;

[0011] 4) Input the evaluation factor level threshold and the evaluation factor distribution model into the spatial analysis platform for analysis, and perform spatial attribute analysis on the evaluation factor distribution model in the spatial analysis platform to form a spatial attribute analysis unit;

[0012] 5) Divide the spatial attribute analysis unit into grids and calculate the evaluation result value S for each spatial attribute analysis unit i i ;

[0013] 6) Initialize S i=0;

[0014] If Y1i≥R1, it is the geothermal mining condition A, then the geothermal mining condition S i =S i +1;

[0015] If Y 2i ≥R2, thermal storage stability is A level, then thermal storage stability S i =S i +1;

[0016] If Y 3i ≥R3, for the temperature of underground hot water, level A, then the temperature of underground hot water, S i =S i +1;

[0017] If Y 4i ≥R4, for underground hot water flow rate A, then the underground hot water flow rate S i =S i +1;

[0018] If Y 5i ≥R5, the water quality of underground hot water is A, and the water quality of underground hot water is S i =S i +1;

[0019] 7) Level Partitioning

[0020] Evaluation result value S i That is the partition level, such as the evaluation result value S i =1, that is, the evaluation area is 1A-level geothermal resources, S i Value = 2, that is, the evaluation area is 2A-level geothermal resources, and so on to S i =5 corresponds to 5A-level geothermal resources.

[0021] Furthermore, you can also choose the ARCGIS series as a spatial analysis platform.

[0022] Furthermore, the construction of the geothermal mining condition distribution model uses at least one of the following parameters:

[0023] 1) Lithology; 2) Burial depth; 3) Drillability.

[0024] Furthermore, the construction of the thermal storage stability distribution model uses at least one of the following parameters:

[0025] 1) Lithology; 2) Occurrence; 3) Structural complexity.

[0026] Furthermore, the construction of the water quality distribution model of underground hot water adopts at least one of the following parameters:

[0027] 1) Total dissolved solids; 2) Elements.

[0028] Furthermore, when geothermal mining conditions meet any two of the following conditions at the same time, then Y 1i ≥R1;

[0029] Condition 1: The lithology is porous sandstone or basalt;

[0030] Condition 2: Burial depth ranges from 20 meters to 3000 meters;

[0031] Condition 3: The rock characteristics are loose sandstone or porous limestone.

[0032] Furthermore, when the thermal storage stability satisfies any two of the following conditions at the same time, then Y 2i ≥R2;

[0033] Condition 1: The lithology is porous sandstone or basalt;

[0034] Condition 2: The dip angle range in the occurrence is 0-35 degrees;

[0035] Condition 3: The fault length is less than 1000 meters and the fault distance is less than 10 meters.

[0036] Furthermore, when the underground hot water temperature meets the following conditions, then Y 3i ≥R3;

[0037] Condition 1: Temperature range is 20-300 degrees Celsius.

[0038] Furthermore, when the underground hot water flow meets the following conditions, then Y 4i ≥R4;

[0039] Condition 1: Water flow range is 30-200m 3 / h.

[0040] Furthermore, when the underground hot water quality meets the following conditions, then Y 5i ≥R5;

[0041] Condition 1: Mineralization is less than 3500 mg / L.

[0042] The beneficial effects of the present invention are: through the analysis of the spatial analysis platform, geothermal fields in different regions can be quickly and effectively classified into grades. The higher the grade, the greater its mining value, and it can be mined first.

[0043] By establishing an evaluation factor distribution model, the data of geothermal fields can be refined, providing accurate data support for grade assessment and a feasible technical solution for the quantitative evaluation of geothermal resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1It is a flow chart of the geothermal resource grade evaluation method based on spatial analysis described in the present invention.

[0045] Figure 2 It is a flow chart of the evaluation factor analysis of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0047] This application provides a geothermal resource grade evaluation method based on spatial analysis, please refer to Figure 1 and Figure 2 :Comprising the following steps;

[0048] 1) Obtain geothermal field exploration data, including reservoir lithology, burial depth, drillability, temperature, flow rate, and water quality characteristics;

[0049] 2) Determine the evaluation factor level thresholds (R1, R2, R3, R4, R5);

[0050] Establish an evaluation factor distribution model, including geothermal mining conditions Y1, heat storage stability Y2, groundwater temperature Y3, groundwater flow Y4, and groundwater quality Y5;

[0051] 3) Select MAPGIS series as the spatial analysis platform;

[0052] 4) Input the evaluation factor level threshold and the evaluation factor distribution model into the spatial analysis platform for analysis, and perform spatial attribute analysis on the evaluation factor distribution model in the spatial analysis platform to form a spatial attribute analysis unit;

[0053] 5) Divide the spatial attribute analysis unit into grids and calculate the evaluation result value S for each spatial attribute analysis unit i i ;

[0054] 6) Initialize S i =0;

[0055] If Y 1i ≥R1, the geothermal mining condition is Class A, then the geothermal mining condition is S i =S i +1;

[0056] If Y 2i ≥R2, thermal storage stability is A level, then thermal storage stability S i =S i +1;

[0057] If Y 3i ≥R3, for the temperature of underground hot water, level A, then the temperature of underground hot water, S i =Si +1;

[0058] If Y 4i ≥R4, for underground hot water flow rate A, then the underground hot water flow rate S i =S i +1;

[0059] If Y 5i ≥R5, the water quality of underground hot water is A, and the water quality of underground hot water is S i =S i +1;

[0060] 7) Level Partitioning

[0061] Evaluation result value S i That is the partition level, such as the evaluation result value S i =1, that is, the evaluation area is 1A-level geothermal resources, S i Value = 2, that is, the evaluation area is 2A-level geothermal resources, and so on to S i =5 corresponds to 5A-level geothermal resources.

[0062] You can also choose the ARCGIS series as a spatial analysis platform.

[0063] The construction of the geothermal mining condition distribution model uses at least one of the following parameters:

[0064] 1) Lithology; 2) Burial depth; 3) Drillability.

[0065] The thermal reservoir stability distribution model is constructed using at least one of the following parameters:

[0066] 1) Lithology; 2) Occurrence; 3) Structural complexity.

[0067] The water quality distribution model of underground hot water is constructed using at least one of the following parameters:

[0068] 1) Total dissolved solids; 2) Elements.

[0069] When geothermal mining conditions meet any two of the following conditions at the same time, then Y 1i ≥R1;

[0070] Condition 1: The lithology is porous sandstone or basalt;

[0071] Condition 2: Burial depth ranges from 20 meters to 3000 meters;

[0072] Condition 3: The rock characteristics are loose sandstone or porous limestone.

[0073] When the thermal storage stability satisfies any two of the following conditions at the same time, then Y 2i ≥R2;

[0074] Condition 1: The lithology is porous sandstone or basalt;

[0075] Condition 2: The dip angle range in the occurrence is 0-35 degrees;

[0076] Condition 3: The fault length is less than 1000 meters and the fault distance is less than 10 meters.

[0077] When the underground hot water temperature meets the following conditions, then Y 3i ≥R3;

[0078] Condition 1: Temperature range is 20-300 degrees Celsius.

[0079] Underground hot water flow, if the following conditions are met, then Y 4i ≥R4;

[0080] Condition 1: Water flow range is 30-200m 3 / h.

[0081] When the underground hot water quality meets the following conditions, then Y 5i ≥R5;

[0082] Condition 1: Mineralization is less than 3500 mg / L.

[0083] Figure 2 This is a flow chart for evaluating factor analysis. The example is a flow chart for analyzing geothermal mining condition distribution model. Figure 2 process, will Figure 2 The "geothermal mining condition distribution model" is replaced by the heat storage stability distribution model, groundwater temperature distribution model, groundwater flow distribution model, and groundwater quality distribution model respectively;

[0084] The “evaluation factor level threshold R1” is replaced by the evaluation factor level threshold R2 (corresponding to the thermal storage stability distribution model), the evaluation factor level threshold R3 (groundwater temperature distribution model), the evaluation factor level threshold R4 (groundwater flow distribution model), and the evaluation factor level threshold R5 (groundwater quality distribution model).

[0085] Replace "lithology, burial depth, and drillability" with corresponding parameters;

[0086] The heat storage stability analysis flow chart, underground hot water temperature analysis flow chart, underground hot water flow analysis flow chart, and underground hot water quality analysis flow chart can be obtained respectively.

[0087] Specifically, taking the geothermal resource grade evaluation method based on spatial analysis as an example, the first complete optimization step is:

[0088] 1) Obtain geothermal field exploration data, including reservoir lithology, burial depth, drillability, temperature, flow rate, and water quality characteristics;

[0089] Thermal reservoir lithology, burial depth, drillability, temperature, flow rate and water quality are the main factors in evaluating the level of geothermal resources. The surrounding environment of the geothermal field and its distance from the main urban area can also be considered in the actual assessment. For example, if the geothermal field is distributed near the main river, it is not easy to mine the geothermal energy; if it is far away from the main urban area, the geothermal energy cannot be used directly and needs to be converted into electricity for transportation. The mining cost is relatively high and it should be judged as a negative indicator.

[0090] 2) Determine the evaluation factor level thresholds (R1, R2, R3, R4, R5);

[0091] The evaluation factor level threshold is set. If the conditions in the local geothermal field exploration data are higher than or equal to the level threshold requirement, the evaluation factor is judged as a positive indicator.

[0092] Establish an evaluation factor distribution model, including geothermal mining conditions Y1, heat storage stability Y2, groundwater temperature Y3, groundwater flow Y4, and groundwater quality Y5;

[0093] Setting up the evaluation factor distribution model facilitates more accurate and efficient analysis of geothermal field exploration data. Five evaluation factors are given as examples, including geothermal mining conditions Y1, heat storage stability Y2, groundwater temperature Y3, groundwater flow Y4, and groundwater quality Y5.

[0094] 3) Select MAPGIS series as the spatial analysis platform;

[0095] The above-mentioned geothermal field exploration data were input into the corresponding evaluation factor distribution model one by one, and analyzed through the MAPGIS spatial analysis platform;

[0096] The MAPGIS spatial analysis platform can support the processing and analysis of full-space three-dimensional data on the surface and underground, realizing the integration of remote sensing data and the MAPGIS spatial analysis platform. It is more convenient to use in practice and is more affordable. If your budget is limited, choosing the MAPGIS series as a spatial analysis platform is very appropriate; however, its data computing capabilities are relatively weak and cannot meet the needs of data with large computational requirements.

[0097] 4) Input the evaluation factor level threshold and the evaluation factor distribution model into the spatial analysis platform for analysis, and perform spatial attribute analysis on the evaluation factor distribution model in the spatial analysis platform to form a spatial attribute analysis unit;

[0098] 5) Divide the spatial attribute analysis unit into grids and calculate the evaluation result value S for each spatial attribute analysis unit i i ;

[0099] The spatial analysis platform processes the data and uniformly outputs them as spatial attribute analysis units, and uses i as a symbol to replace the evaluation result value. i .

[0100] 6) Initialize S i =0;

[0101] If Y 1i ≥R1, the geothermal mining condition is Class A, then the geothermal mining condition is S i =S i +1;

[0102] If Y 2i ≥R2, thermal storage stability is A level, then thermal storage stability S i =S i +1;

[0103] If Y 3i ≥R3, for the temperature of underground hot water, level A, then the temperature of underground hot water, S i =S i +1;

[0104] If Y 4i ≥R4, for underground hot water flow rate A, then the underground hot water flow rate S i =S i +1;

[0105] If Y 5i ≥R5, the water quality of underground hot water is A, and the water quality of underground hot water is S i =S i +1;

[0106] The spatial analysis platform evaluates the processed data according to the above rules. The following example illustrates that: 1i It is the result of analyzing the data of geothermal mining conditions. If the result is greater than or equal to the value or condition set by R1, then S i =1, that is, the assessment area is a 1A-level geothermal resource;

[0107] According to the above rules, if Y 1i ≥R1, Y 2i ≥R2, then S i =2, that is, the evaluation area is a 2A-level geothermal resource.

[0108] 7) Level Partitioning

[0109] Evaluation result value S i That is the partition level, such as the evaluation result value S i =1, that is, the evaluation area is 1A-level geothermal resources, S i Value = 2, that is, the evaluation area is 2A-level geothermal resources, and so on to S i=5 corresponds to 5A-level geothermal resources.

[0110] You can also choose the ARCGIS series as a spatial analysis platform.

[0111] The ARCGIS series is a powerful spatial analysis platform with unique advantages in buffer analysis and overlay analysis for evaluation factor distribution models.

[0112] The following simplified data is used for illustration;

[0113] The construction of the geothermal mining condition distribution model uses the burial depth parameter:

[0114] This embodiment uses only one parameter, the burial depth.

[0115] The thermal reservoir stability distribution model is constructed using the occurrence parameters:

[0116] This embodiment uses only one parameter, namely, the occurrence.

[0117] The water quality distribution model of underground hot water is constructed using the total dissolved solids parameter:

[0118] This example uses only one parameter, total dissolved solids.

[0119] When the above three parameters of burial depth, occurrence and total dissolved solids are met, it can be evaluated as a 3A geothermal resource.

[0120] Geothermal mining conditions meet the following conditions: 1. The lithology is porous sandstone or basalt; 2. The burial depth is 20 meters, then Y 1i ≥R1.

[0121] Regarding the conditions for geothermal mining, it is very easy to mine when the burial depth is 20 meters.

[0122] Thermal storage stability satisfies the following conditions simultaneously: 1. The lithology is porous sandstone or basalt; 2. The dip angle in the occurrence is 0 degrees, then Y 2i ≥R2.

[0123] The refinement of the heat storage stability conditions shows that when the dip angle in the occurrence is 0 degrees, the mining stability is very high and the heat supply is more stable.

[0124] When the underground hot water temperature meets the following conditions, then Y 3i ≥R3;

[0125] Condition 1: The temperature is 20 degrees Celsius.

[0126] When the water temperature is 20 degrees Celsius, it can be used as a cooling medium.

[0127] Underground hot water flow, if the following conditions are met, then Y 4i≥R4;

[0128] Condition 1: Water flow rate is 30m 3 / h.

[0129] When the underground hot water quality meets the following conditions, then Y 5i ≥R5;

[0130] Condition 1: Mineralization is 100 mg / L.

[0131] Mineralization is a comprehensive indicator of water quality. When the mineralization is 100 mg / L, only preliminary filtration of the water is required.

[0132] The second preferred complete step is:

[0133] 1) Obtain geothermal field exploration data, including reservoir lithology, burial depth, drillability, temperature, flow rate, and water quality characteristics;

[0134] 2) Determine the evaluation factor level thresholds (R1, R2, R3, R4, R5);

[0135] Establish an evaluation factor distribution model, including geothermal mining conditions Y1, heat storage stability Y2, groundwater temperature Y3, groundwater flow Y4, and groundwater quality Y5;

[0136] 3) Select MAPGIS series as the spatial analysis platform;

[0137] 4) Input the evaluation factor level threshold and the evaluation factor distribution model into the spatial analysis platform for analysis, and perform spatial attribute analysis on the evaluation factor distribution model in the spatial analysis platform to form a spatial attribute analysis unit;

[0138] 5) Divide the spatial attribute analysis unit into grids and calculate the evaluation result value S for each spatial attribute analysis unit i i ;

[0139] 6) Initialize S i =0;

[0140] If Y 1i ≥R1, the geothermal mining condition is Class A, then the geothermal mining condition is S i =S i +1;

[0141] If Y 2i ≥R2, thermal storage stability is A level, then thermal storage stability S i =S i +1;

[0142] If Y 3i ≥R3, for the temperature of underground hot water, level A, then the temperature of underground hot water, S i=S i +1;

[0143] If Y 4i ≥R4, for underground hot water flow rate A, then the underground hot water flow rate S i =S i +1;

[0144] If Y 5i ≥R5, the water quality of underground hot water is A, and the water quality of underground hot water is S i =S i +1;

[0145] 7) Level Partitioning

[0146] Evaluation result value S i That is the partition level, such as the evaluation result value S i =1, that is, the evaluation area is 1A-level geothermal resources, S i Value = 2, that is, the evaluation area is 2A-level geothermal resources, and so on to S i =5 corresponds to 5A-level geothermal resources.

[0147] You can also choose the ARCGIS series as a spatial analysis platform.

[0148] The following parameters are used to construct the geothermal mining condition distribution model:

[0149] 1) Lithology; 2) Burial depth; 3) Drillability.

[0150] When the above three conditions are used to construct the geothermal mining condition distribution model, it means that the geothermal mining conditions are more stringent.

[0151] The following parameters are used to construct the thermal storage stability distribution model:

[0152] 1) Lithology; 2) Occurrence; 3) Structural complexity.

[0153] The water quality distribution model of underground hot water is constructed using the following parameters:

[0154] 1) Total dissolved solids; 2) Elements.

[0155] When geothermal mining conditions meet the following conditions at the same time, then Y 1i ≥R1;

[0156] Condition 1: The lithology is porous sandstone or basalt;

[0157] Condition 2: burial depth is 3,000 meters;

[0158] Condition 3: The rock characteristics are loose sandstone or porous limestone.

[0159] Condition 1 is an indicator of lithology, condition 2 is an indicator of burial depth, and condition 3 is an indicator of drillability. If all three conditions are met, then Y 1i ≥R1, can be evaluated as 1A-level geothermal resources.

[0160] When the thermal storage stability satisfies the following conditions at the same time, then Y 2i ≥R2;

[0161] Condition 1: The lithology is porous sandstone or basalt;

[0162] Condition 2: The dip angle in the occurrence is 35 degrees;

[0163] Condition 3: The fault length is 1000 meters and the fault distance is 10 meters.

[0164] Condition 1 is an indicator of lithology, condition 2 is an indicator of occurrence, and condition 3 is an indicator of structural complexity. If all three conditions are met, then Y 2i ≥R2, can be evaluated as 2A-level geothermal resources.

[0165] When the underground hot water temperature meets the following conditions, then Y 3i ≥R3;

[0166] Condition 1: The temperature is 300 degrees Celsius.

[0167] 300 degrees Celsius is a high-temperature thermal energy resource and can be used in a cascaded manner. For example, temperatures above 90 degrees Celsius can be used for industrial power generation, 60-90 degrees Celsius can be used for heating, and 45-60 degrees Celsius can be used for greenhouse farming after heating.

[0168] Underground hot water flow, if the following conditions are met, then Y 4i ≥R4;

[0169] Condition 1: Water flow rate is 200m 3 / h.

[0170] When the underground hot water quality meets the following conditions, then Y 5i ≥R5;

[0171] Condition 1: Mineralization is 3499 mg / L.

Claims

1. A geothermal resource grade evaluation method based on spatial analysis, characterized in that: The following steps are included: 1) Obtain geothermal field exploration data, including reservoir lithology, burial depth, drillability, temperature, flow rate, and water quality characteristics; 2) Determine the evaluation factor level thresholds (R1, R2, R3, R4, R5); Establish an evaluation factor distribution model, including geothermal mining conditions Y1, heat storage stability Y2, groundwater temperature Y3, groundwater flow Y4, and groundwater quality Y5; 3) Select MAPGIS series as the spatial analysis platform; 4) Input the evaluation factor level threshold and the evaluation factor distribution model into the spatial analysis platform for analysis, and perform spatial attribute analysis on the evaluation factor distribution model in the spatial analysis platform to form a spatial attribute analysis unit; 5) Divide the spatial attribute analysis unit into grids and calculate the evaluation result value S for each spatial attribute analysis unit i i ; 6) Initialize S i =0; If Y 1i ≥R1, the geothermal mining condition is Class A, then the geothermal mining condition is S i =S i +1; If Y 2i ≥R2, thermal storage stability is A level, then thermal storage stability S i =S i +1; If Y 3i ≥R3, for the temperature of underground hot water, level A, then the temperature of underground hot water, S i =S i +1; If Y 4i ≥R4, for underground hot water flow rate A, then the underground hot water flow rate S i =S i +1; If Y 5i ≥R5, the water quality of underground hot water is A, and the water quality of underground hot water is S i =S i +1; 7) Level Partitioning Evaluation result value S i That is the partition level, such as the evaluation result value S i =1, that is, the evaluation area is 1A-level geothermal resources, S i Value = 2, that is, the evaluation area is a 2A-level geothermal resource, and so on to S i =5 corresponds to 5A-level geothermal resources.

2. The geothermal resource grade evaluation method based on spatial analysis according to claim 1, characterized in that: You can also choose the ARCGIS series as a spatial analysis platform.

3. The geothermal resource grade evaluation method based on spatial analysis according to claim 1, characterized in that: The construction of the geothermal mining condition distribution model uses at least one of the following parameters: 1) Lithology; 2) Burial depth; 3) Drillability.

4. The geothermal resource grade evaluation method based on spatial analysis according to claim 1, characterized in that: The thermal reservoir stability distribution model is constructed using at least one of the following parameters: 1) Lithology; 2) Occurrence; 3) Structural complexity.

5. The geothermal resource grade evaluation method based on spatial analysis according to claim 1, characterized in that: The water quality distribution model of underground hot water is constructed using at least one of the following parameters: 1) Total dissolved solids; 2) Elements.

6. The geothermal resource grade evaluation method based on spatial analysis according to claim 3, characterized in that: When geothermal mining conditions meet any two of the following conditions at the same time, then Y 1i ≥R1; Condition 1: The lithology is porous sandstone or basalt; Condition 2: Burial depth ranges from 20 meters to 3000 meters; Condition 3: The rock characteristics are loose sandstone or porous limestone.

7. The geothermal resource grade evaluation method based on spatial analysis according to claim 4, characterized in that: When the thermal storage stability satisfies any two of the following conditions at the same time, then Y 2i ≥R2; Condition 1: The lithology is porous sandstone or basalt; Condition 2: The dip angle range in the occurrence is 0-35 degrees; Condition 3: The fault length is less than 1000 meters and the fault distance is less than 10 meters.

8. The geothermal resource grade evaluation method based on spatial analysis according to claim 5, characterized in that: When the underground hot water temperature meets the following conditions, then Y 3i ≥R3; Condition 1: Temperature range is 20-300 degrees Celsius.

9. The geothermal resource grade evaluation method based on spatial analysis according to any one of claims 6 to 8, characterized in that: Underground hot water flow, if the following conditions are met, then Y 4i ≥R4; Condition 1: Water flow range is 30-200m 3 / h.

10. The geothermal resource grade evaluation method based on spatial analysis according to any one of claims 6 to 8, characterized in that: When the underground hot water quality meets the following conditions, then Y 5i ≥R5; Condition 1: Mineralization is less than 3500 mg / L.

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