Hydrothermal type geothermal field quality grade evaluation method based on fuzzy comprehensive discrimination

Abstract

The invention discloses a hydrothermal type geothermal field quality grade evaluation method based on fuzzy comprehensive discrimination, and the method comprises the steps: obtaining geothermal field exploration data which comprises a first-level index and a second-level index corresponding to the first-level index; rating based on an evaluation grade threshold, wherein a threshold formula is ai = ln (n + 2-i) / ln (n + 1); in the formula, ai is the score of the i grade; n is a grade number; a fuzzy comprehensive evaluation index is calculated based on the evaluation grade value, the formula is pi = Wi * R ', Wi is a first-level index weight, and R' is a first-level index score matrix; on the basis of the fuzzy comprehensive evaluation indexes, comprehensive evaluation grade values are calculated, and the formula is M = # imgabs0 #; and obtaining the quality grade of the geothermal field based on the comprehensive evaluation grade value. The fuzzy comprehensive discrimination method is adopted, the geothermal heat storage condition, the mining condition, the water source condition, the heat source condition and the water quality condition serve as first-level evaluation index factors, the geothermal field is divided into multiple levels, and a technical basis is provided for geothermal resource evaluation, development and utilization of the geothermal field.

Description

Technical Field

[0001] The present invention relates to the technical field of geothermal field quality grade evaluation, and in particular to a hydrothermal geothermal field quality grade evaluation method based on fuzzy comprehensive judgment. Background Art

[0002] Geothermal anomalies containing exploitable geothermal resources within accessible depths are called geothermal fields. Currently, various methods are used to evaluate geothermal field resources, including the heat reservoir volume method, heat flow method, analogy method, mining dynamics method, lumped parameter model method, plane fracture method, magma heat balance method, and Monte Carlo method. The choice of geothermal resource evaluation method depends on the exploration level and geological conditions of the geothermal field. Among them, the heat reservoir volume method is the most commonly used method, which is applicable to all geological conditions and widely adopted both domestically and internationally. However, existing geothermal resource evaluation methods mainly focus on estimating the static reserves of geothermal resources or their development potential, and the results obtained are often subject to significant uncertainty. Research has shown that the exploitation and utilization value of geothermal fields is influenced by multiple factors, such as burial depth, temperature, water production, geographical location, and mineralization. Given these numerous evaluation factors, how to assess the level of geothermal resources has become a major challenge. Summary of the Invention

[0003] In order to solve the above-mentioned problems, the present invention provides a method for evaluating the quality grade of hydrothermal geothermal fields based on fuzzy comprehensive judgment.

[0004] To achieve the above object, the present invention provides a method for evaluating the quality grade of hydrothermal geothermal fields based on fuzzy comprehensive discrimination, comprising: Acquiring geothermal field exploration data, the data including primary indicators and secondary indicators corresponding to the primary indicators; Rating is based on the evaluation level threshold formula, the formula is: a i =ln(n+2-i) / ln(n+1); Where: a i is the score of level i; n is the number of levels; The fuzzy comprehensive evaluation index is calculated based on the evaluation grade value, and the formula is p i =W i ×R',W i is the first-level indicator weight, R' is the first-level indicator score matrix; Based on the fuzzy comprehensive evaluation index, the comprehensive evaluation grade value is calculated, and the formula is: M= ; Based on the comprehensive evaluation level value M, a i , obtaining geothermal field quality grade.

[0005] Preferably, the first-level indicators include heat storage conditions, mining conditions, water source conditions, heat source conditions and the water quality conditions; the second-level indicators of the heat storage conditions include thickness, heat storage type, and inclination; the second-level indicators of the mining conditions include inclination, burial depth, and lithology; the second-level indicators of the water source conditions include precipitation, surface water, flow rate, and tensile fractures; the second-level indicators of the heat source conditions include geothermal gradient, water temperature, and deep and large active fractures; the second-level indicators of the water quality conditions include total dissolved solids, beneficial elements, and harmful elements.

[0006] Preferably, the secondary indicator scoring formula is: r ij =(C i1 +C i2 +...+C ig ) / m; Where: C i1 is the expert score for the secondary indicator; i is the ith secondary indicator; j is the jth level; g is the gth expert; m is the number of experts who have given valid (non-zero) scores for the ith secondary indicator at the jth level.

[0007] Preferably, the first-level indicator score matrix formula is R'=[W iq ×R Aq ]; Where: R Aq is the secondary indicator score matrix of the qth first-level indicator; W iq is the weight of the second-level indicator of the qth first-level indicator.

[0008] Preferably, the secondary indicator score matrix R Aq = ;

[0009] Where: q is the first-level indicator number; r ij The score of a certain level for each secondary indicator.

[0010] Preferably, the weight of the heat storage condition is W1=0.160, the weight of the mining condition is W2=0.086, the weight of the water source condition is W3=0.304, the weight of the heat source condition is W4=0.385, and the weight of the water quality condition is W5=0.065.

[0011] Preferably, the thickness weight is W 11 =0.637, the weight of the heat storage type is W 12 =0.258, the weight of the inclination angle of the heat storage condition is W 13 =0.105; the weight of the inclination angle of the mining condition is W 21=0.540, the weight of the burial depth is W 22 =0.297, the weight of the lithology is W 23 =0.163; the weight of the precipitation is W 31 =0.161, the weight of the surface water is W 32 =0.166, the weight of the traffic is W 33 =0.332, the weight of the tensile fracture is W 34 =0.341; the weight of the geothermal gradient is W 41 =0.323, the weight of the water temperature is W 42 =0.110, the weight of the deep and large active fault is W 43 =0.567; the weight of the total dissolved solids is W 51 =0.655, the weight of the beneficial element is W 52 =0.250, the weight of the harmful element is W 53 =0.095.

[0012] Preferably, the scoring values of each scoring expert are different.

[0013] Compared with the prior art, the present invention has the following beneficial effects: The present invention adopts a fuzzy comprehensive discrimination method, with geothermal heat storage conditions, mining conditions and water source conditions, heat source conditions and water quality conditions as the first-level evaluation index factors, to divide geothermal fields into multiple levels, providing a technical basis for the evaluation and development and utilization of geothermal resources in geothermal fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a flow chart of the quality grade evaluation method for hydrothermal geothermal fields based on fuzzy comprehensive judgment. DETAILED DESCRIPTION

[0015] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0016] Reference Figure 1 The present invention provides a method for evaluating the quality grade of hydrothermal geothermal fields based on fuzzy comprehensive discrimination, including Obtain geothermal field exploration data, including primary indicators and secondary indicators corresponding to the primary indicators; Rating is based on the evaluation level threshold formula, the formula is: a i =ln(n+2-i) / ln(n+1); Where: a i is the score of level i; n is the number of levels; The fuzzy comprehensive evaluation index is calculated based on the evaluation grade value, and the formula is p i =W i ×R',W i is the first-level indicator weight, R' is the first-level indicator score matrix; Based on the fuzzy comprehensive evaluation index, the comprehensive evaluation grade value is calculated. The formula is: M= ; Based on the comprehensive evaluation grade value, the geothermal field quality grade is obtained.

[0017] In this embodiment, the first-level indicators include heat storage conditions, mining conditions, water source conditions, heat source conditions and water quality conditions; the second-level indicators of heat storage conditions include thickness, heat storage type and inclination; the second-level indicators of mining conditions include inclination, burial depth and lithology; the second-level indicators of water source conditions include precipitation, surface water, flow rate and tensile faults; the second-level indicators of heat source conditions include geothermal gradient, water temperature and deep and large active faults; the second-level indicators of water quality conditions include total dissolved solids, beneficial elements and harmful elements.

[0018] Specifically, this application uses the "1-9 scale" proposed by American scholar Professor TLSaaty to establish the weights of primary and secondary indicators. This application also uses the qualitative ranking and quantitative conversion method of "Pan-system Observation and Control Technology" to name the comprehensive grade of geothermal fields.

[0019] Furthermore, the grade is calculated using the following formula: a i =ln(n+2-i) / ln(n+1); When divided into three levels, n=3, i=1,…,3; The formula is a i =ln(5-i) / ln(4) When i=1, a1= ln(4) / ln(4)=1; When i=2, a2= ln(3) / ln(4)=1.09861 / 1.38629=0.79; When i=3, a3= ln(2) / ln(4)=0.69314718 / 1.38629=0.5; Therefore, the threshold for the first level is (1-0.79), the threshold for the second level is (0.79-0.50), and the threshold for the third level is (0.50-0.0). This application uses 5A, 4A, and 3A to name the comprehensive grades of geothermal fields, which are derived from the naming method of tourist attractions (such as 5A tourist attractions, etc.).

[0020] In this embodiment, the secondary indicator scoring formula is: r ij =(C i1 +C i2 +...+C ig ) / m; Where: C i1 is the expert score for the secondary indicator; i is the ith secondary indicator; j is the jth level; g is the gth expert. m is the number of experts with valid (non-zero) scores for the ith secondary indicator at the jth level.

[0021] The first-level indicator score matrix formula is R'=[W iq ×R Aq ]; Where: R Aq is the secondary indicator score matrix of the qth first-level indicator; W iq is the weight of the second-level indicator of the qth first-level indicator.

[0022] Secondary indicator score matrix R Aq = .

[0023] In this embodiment, the weight of the heat storage condition is W1=0.160, the weight of the mining condition is W2=0.086, the weight of the water source condition is W3=0.304, the weight of the heat source condition is W4=0.385, and the weight of the water quality condition is W5=0.065. 11 =0.637, the weight of heat storage type is W 12 =0.258, the weight of the inclination angle of the heat storage condition is W 13 =0.105; the weight of the inclination angle of the mining condition is W 21 =0.540, the weight of the burial depth is W 22 =0.297, the lithology weight is W 23 =0.163; the weight of precipitation is W 31 =0.161, the weight of surface water is W 32 =0.166, the weight of the flow is W 33 =0.332, the weight of tensile fracture is W 34 =0.341; the weight of the geothermal gradient is W 41 =0.323, the weight of water temperature is W 42=0.110, the weight of deep and large active fault is W 43 =0.567; the weight of total dissolved solids is W 51 =0.655, the weight of the beneficial element is W 52 =0.250, the weight of harmful elements is W 53 =0.095.

[0024] Furthermore, the scoring values of each scoring expert are different.

[0025] Example 1 In this embodiment, three levels are preset, so n=3, so the formula is: ai=ln(5-i) / ln(4); the three levels are 5A with a score of (1~0.79), 4A with a score of (0.79~0.5), and 3A with a score of (0.5~0.0).

[0026] The secondary indicator scoring table is detailed in Table 1.

[0027] Table 1

[0028] Select n experts to evaluate and score according to the standards and exploration data in Table 1, and obtain Table 2. Each expert's secondary indicator can only have one score.

[0029] Table 2

[0030] where r ij =(C i1 +C i2 +...+C im ) / m, where m is the number of experts who effectively scored each secondary indicator at a certain level; if a secondary indicator at a certain level has no score, it is counted as 0.

[0031] r ij The score of each secondary indicator at a certain level is shown in the score column in Table 2. The total number of experts is n. There are only m experts scoring each secondary indicator at a certain level. For example, there are 5 experts, 3 of them scored the thickness at 5A level, which are 0.91, 0.85, and 0.88 respectively. 2 experts scored the thickness at 4A level, which are 0.75 and 0.73 respectively. That is, r 15 =(0.91+0.85+0.88) / 3=0.88,r 14 =(0.75+0.73) / 2=0.74. 13 =0.

[0032] The scores in Table 2 can be used to construct the secondary indicator score matrix of the five primary indicators: ; ; ; ; .

[0033] Scoring matrix of first-level indicators:

[0034] Calculate the fuzzy comprehensive evaluation index: .

[0035] Right now .

[0036] Calculate the comprehensive evaluation grade value M: M= ; in: The grade scores are 1, 0.79, and 0.5 respectively.

[0037] Different levels: M is (1~0.79), which is 5A; M is (0.79~0.5), which is 4A; M is (0.5~0.0), which is 3A.

[0038] Example 2 The thermal reservoir of a geothermal field is composed of fine sandstone, siltstone, and medium sandstone of the Guantao Formation. The relevant data are shown in Table 3. An expert was invited to provide a score, as shown in Table 4.

[0039] Table 3

[0040] Table 4

[0041] Construct a vector matrix:

[0042] Calculate the fuzzy comprehensive evaluation index: p i =W i ×R'; ; .

[0043] Calculate the comprehensive evaluation grade value: .

[0044] Conclusion: This area is a 5A-level geothermal field.

[0045] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A method for evaluating the quality grade of hydrothermal geothermal fields based on fuzzy comprehensive discrimination, characterized in that: include: Acquiring geothermal field exploration data, the data including primary indicators and secondary indicators corresponding to the primary indicators; Rating is based on the evaluation level threshold formula, the formula is: a i =ln(n+2-i) / ln(n+1); Where: a i is the score of level i; n is the number of levels; The fuzzy comprehensive evaluation index is calculated based on the evaluation grade value, and the formula is p i =W i ×R',W i is the first-level indicator weight, R' is the first-level indicator score matrix; Based on the fuzzy comprehensive evaluation index, the comprehensive evaluation grade value is calculated, and the formula is: M= ； Based on the comprehensive evaluation grade value, the geothermal field quality grade is obtained.

2. The method for evaluating the quality grade of hydrothermal geothermal fields based on fuzzy comprehensive discrimination according to claim 1 is characterized in that: The first-level indicators include heat storage conditions, mining conditions, water source conditions, heat source conditions and the water quality conditions. The second-level indicators of the heat storage conditions include thickness, heat storage type, and inclination; the second-level indicators of the mining conditions include inclination, burial depth, and lithology; the second-level indicators of the water source conditions include precipitation, surface water, flow, and tensile fractures; the second-level indicators of the heat source conditions include geothermal gradient, water temperature, and deep and large active fractures; the second-level indicators of the water quality conditions include total dissolved solids, beneficial elements, and harmful elements.

3. The method for evaluating the quality grade of a hydrothermal geothermal field based on fuzzy comprehensive discrimination according to claim 2 is characterized in that: The secondary indicator score matrix R of the qth primary indicator Aq = ; Where: q is the first-level indicator number; r ij The score of a certain level for each secondary indicator.

4. The method for evaluating the quality grade of a hydrothermal geothermal field based on fuzzy comprehensive discrimination according to claim 3 is characterized in that: The scoring formula for the secondary indicators is: r ij =(C i1 +C i2 +...+C ig ) / m; Where: C i1 is the expert score for the secondary indicator; i is the ith secondary indicator; j is the jth level; g is the gth expert; m is the number of experts who have effectively scored the jth level for the ith secondary indicator.

5. The method for evaluating the quality grade of a hydrothermal geothermal field based on fuzzy comprehensive discrimination according to claim 4 is characterized in that: The first-level indicator score matrix formula is R'=[W iq ×R Aq ]; Where: R Aq is the secondary indicator score matrix of the qth first-level indicator; W iq is the weight of the second-level indicator of the qth first-level indicator.

6. The method for evaluating the quality grade of a hydrothermal geothermal field based on fuzzy comprehensive discrimination according to claim 5 is characterized in that: The weight of the heat storage condition is W1=0.160, the weight of the mining condition is W2=0.086, the weight of the water source condition is W3=0.304, the weight of the heat source condition is W4=0.385, and the weight of the water quality condition is W5=0.

065.

7. The method for evaluating the quality grade of a hydrothermal geothermal field based on fuzzy comprehensive discrimination according to claim 6, characterized in that: The thickness weight is W 11 =0.637, the weight of the heat storage type is W 12 =0.258, the weight of the inclination angle of the heat storage condition is W 13 =0.105; the weight of the inclination angle of the mining condition is W 21 =0.540, the weight of the burial depth is W 22 =0.297, the weight of the lithology is W 23 =0.163; the weight of the precipitation is W 31 =0.161, the weight of the surface water is W 32 =0.166, the weight of the traffic is W 33 =0.332, the weight of the tensile fracture is W 34 =0.341; the weight of the geothermal gradient is W 41 =0.323, the weight of the water temperature is W 42 =0.110, the weight of the deep and large active fault is W 43 =0.567; the weight of the total dissolved solids is W 51 =0.655, the weight of the beneficial element is W 52 =0.250, the weight of the harmful element is W 53 =0.

095.

8. The method for evaluating the quality grade of a hydrothermal geothermal field based on fuzzy comprehensive discrimination according to claim 7 is characterized in that: Each scoring expert has a different scoring value.

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