Suitability evaluation method for development and utilization of geothermal energy water taking type project

Abstract

The invention discloses a suitability evaluation method for development and utilization of a geothermal energy water taking type project. The method comprises the steps that firstly, according to different geothermal resource heat storage types, a dominant marking method and a superposition method are combined for differentiated zoning; then, an evaluation index system is constructed from four dimensions of geology, technology, policy and regulation and economic market, an interaction relationship among indexes is quantified by using a DEMATEL method, and key influence factors such as the thickness and the porosity of the aquifer are objectively identified; and finally, determining a key index weight by adopting AHP, and calculating a comprehensive score of the water taking suitability of each subarea through index quantitative grading and linear weighted summation, thereby realizing scientific and accurate regional suitability grade division. According to the method, the problems of high subjectivity and index homogenization of a traditional method are effectively solved, systematic and visual evaluation on the development suitability of the geothermal energy water taking type project is realized, and a reliable basis is provided for sustainable development and planning management of geothermal resources.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geothermal energy development evaluation, in particular to a suitability evaluation method for geothermal energy water-taking type project development and utilization. BACKGROUND

[0002] As a clean and renewable energy, geothermal energy has been increasingly valued for its development and utilization. The core of water-taking type geothermal projects (such as geothermal heating, hot spring utilization, etc.) lies in the sustainable access to geothermal fluids, so it is crucial to scientifically evaluate the development suitability of different regions.

[0003] Currently, geothermal resource suitability evaluation mostly adopts a single method, such as analytic hierarchy process (AHP), principal component analysis, grey correlation method or expert scoring method. Although these methods are widely used, they have obvious limitations: first, the selection of evaluation indicators and the determination of weights are too dependent on expert experience, with strong subjectivity and lack of objective data to support their internal logical relationships; second, the existing methods usually use a "one-size-fits-all" universal index system, which fails to fully consider the essential differences in geological structure, fluid occurrence conditions, and recharge mechanism of different types of thermal reservoirs (such as porous, fractured, and karst types), resulting in weak pertinence of the evaluation results and inability to accurately reflect the suitability changes of different regions within the same area; finally, traditional methods are difficult to handle the systematic problems of mixed qualitative and quantitative indicators and complex mutual influence between indicators, with low transparency in the evaluation process and limited credibility of the results.

[0004] Therefore, there is an urgent need in the field for a comprehensive evaluation method system that integrates objective factor analysis, differentiated zoning evaluation and visual output to overcome the above-mentioned defects, so as to achieve scientific, accurate and efficient evaluation of the suitability of geothermal energy water-taking type project development and utilization. SUMMARY

[0005] The present application aims to solve the following problems: (1) strong subjectivity, lack of objective basis: the traditional method over-reliance on expert experience in index selection and weight determination, there is a large subjective randomness. Different expert group's opinion may lead to significant differences in evaluation results, lack of convincing objective data support, so that the decision-making risk. (2) index homogenization, lack of pertinence: the existing evaluation system usually uses a set of fixed "universal index" to evaluate all types of geothermal resources. Neglect the essential difference of different types of heat storage in the mechanism of formation, geological structure, fluid migration law, etc., leading to the evaluation results "unfit", can not accurately reflect the true suitability of a particular region. (3) ignore the complex relationship between indexes: the traditional method regards each evaluation index as an independent individual, ignoring the complex cause and effect, influence and feedback relationship existing in the index system. For example, "policy support" will affect "economic cost", and "recharge technology" is directly related to the compliance of "environmental regulations". This complex network relationship is simplified as an independent weight, leading to the distortion of the evaluation model. (4) implicit key indicators are easy to be missed: due to the dependence on subjective experience, some difficult to quantify but crucial "implicit" indicators are easy to be ignored or given inappropriate weight, so as to identify the real key bottleneck factor restricting the project sustainability. (5) the evaluation process is "black box", and the results are not comparable: the conversion process from qualitative description to quantitative score lacks unified and transparent standards. The evaluation results of different regions and different personnel are difficult to be compared horizontally, and cannot provide standardized and mutually recognized data support for the overall planning of national or regional geothermal resources. (6) disconnection with spatial geographic information: the traditional numerical scoring method is difficult to be closely combined with the actual geographical location of the project, and cannot intuitively show "where is suitable, where is not suitable" in space, which is not conducive to the intuitive layout of development planning and the accurate delineation of "red line".

[0006] The present application provides a geothermal energy water taking type project development and utilization suitability evaluation method, comprising the following steps: S1, determining the type of geothermal resources: obtaining the geological feature data of the target region, according to the heat storage genesis, structure and lithology conditions, the geothermal resources of the target region are divided into one of seven heat storage types, the seven types include: porous layered heat storage, fissure type belt heat storage, fissure type layered heat storage, fissure type belt and layered composite heat storage, karst type layered heat storage, upper porous and lower karst composite layered heat storage, upper porous and lower fissure composite layered heat storage; S2, determining geothermal resource multi-factor zoning: based on the heat storage type identified in step S1, determining zoning indicators from a pre-established indicator library through a dominant indicator method, dividing the zoning indicators into targeted zoning indicators and general zoning indicators; using geographic information system tools, respectively drawing single-factor zoning maps of each selected indicator; then using the superposition method to spatially superimpose the single-factor zoning maps to generate a multi-factor comprehensive zoning map of the target area, dividing the target area into several evaluation zones; S3, key evaluation indicator identification step: constructing a geothermal energy water-taking project development and utilization influence factor system, which includes four criterion layers of geology, technology, policies and regulations, and economic market and 20 index layer factors thereunder; using decision laboratory analysis to process expert scoring data, calculating the influence degree D, the affected degree C, the centrality M and the reason degree R of each indicator, and selecting a preset number of indicators as key evaluation indicators in descending order of centrality M; S4, calculating the geothermal resource evaluation score: based on the key evaluation indicators selected in S3, constructing an analytic hierarchy process model, calculating the weight of each key evaluation indicator through pairwise comparison judgment matrix; at the same time, quantitatively grading and scoring each key evaluation indicator in each evaluation zone, with a score range of 0-100; finally, using linear weighting and summing method, multiplying and accumulating the scores of each key evaluation indicator and its corresponding weight, calculating the comprehensive score of water-taking suitability of each evaluation zone, and determining the suitability grade of the zone according to the interval of the comprehensive score.

[0007] Preferably, the pre-established indicator library in S2 includes natural geographical factors and social factors, wherein the natural geographical factors include landform, geology, hydrology, climate, mineral resources, vegetation; the social factors include policy, regulation, human activity.

[0008] Preferably, the zoning indicators in S2 include geologic structure morphology, lithology, geothermal fluid hydrochemical type, heat storage water abundance, land use, porosity, permeability, total dissolved solids, fracture zone distribution, heat storage temperature.

[0009] Preferably, the general zoning indicators in S2 are indicators applicable to all the seven types of geothermal reservoirs, including geological structure, lithology, geothermal fluid water chemistry type, geothermal reservoir water abundance, land use; the specific zoning indicators are indicators selected according to specific geothermal reservoir types, and the corresponding relationship is: for the pore-type layered geothermal reservoir, the specific zoning indicator is geological structure; for the fracture-type zonal geothermal reservoir, the specific zoning indicator is fracture zone distribution; for the fracture-type layered geothermal reservoir and the fracture-type zonal layered composite geothermal reservoir, the specific zoning indicator is geothermal reservoir temperature; for the karst-type layered geothermal reservoir, the specific zoning indicator is total dissolved solids; for the upper-pore lower-karst composite layered geothermal reservoir, the specific zoning indicators are porosity, permeability, and total dissolved solids; for the upper-pore lower-fracture composite layered geothermal reservoir, the specific zoning indicators are porosity and permeability.

[0010] Preferably, the specific process of generating a multi-factor comprehensive zoning map by superimposition in S2 includes: S2-1: Superimpose two different single-factor zoning maps to generate a double-factor superimposed map; S2-2: Take the double-factor superimposed map as the base layer and continue to superimpose a third single-factor zoning map to generate a three-factor superimposed map; S2-3: Repeat step S2-2 until all selected single-factor zoning maps corresponding to the zoning indicators are superimposed to generate a final multi-factor comprehensive zoning map; S2-4: For small linear or point-shaped areas generated after superimposition, adopt a nearest merging strategy to merge them into adjacent larger blocks.

[0011] Preferably, the specific process of processing expert scoring data by decision laboratory analysis in S3 includes: S3-1, Construct an index system: establish an index system containing four factors of geology, technology, policy and regulations, and economic market, and collect basic data of the factors; S3-2, Establish a direct influence matrix: use x ij to represent the direct influence degree of factor i on factor j, and according to relevant literature and expert questionnaire scores, the influence degree is classified as no influence, weak influence, weak influence, strong influence, and very strong influence, respectively assigned 0, 1, 2, 3, and 4 points, to obtain the direct influence matrix of geothermal energy development and utilization water-taking projects; S3-3, Calculate the normalized influence matrix G and the comprehensive influence matrix T: determine the mutual logical relationship between the influencing factors, and calculate the normalized influence matrix G and the comprehensive influence matrix T: Where I is an n x n identity matrix, and n is the number of factors. S3-4. Calculate the influence degree D, the degree of influence C, the centrality M, and the degree of causation R: S3-5. Identify key evaluation indicators based on centrality and causality.

[0012] Preferably, the 20 index factors in step S3 are as follows: Geological factors include 8 indicators, namely geological structure, topography, soil and rock type, geothermal fluid hydrochemistry type, aquifer thickness, porosity, geothermal resource reserves, and the degree of guarantee of lateral recharge during extraction; Technical factors include 5 indicators, namely water extraction technology, reinjection technology, reservoir management, unit water output, and groundwater drawdown; Policy and regulations factors include 3 indicators, namely policy support, environmental regulations, and local regulations; Economic and market factors include 4 indicators, namely economic cost, energy demand and market, social acceptance, and insurance and risk management.

[0013] Preferably, the quantitative grading and scoring process in step S4 is as follows: the evaluation value of each key evaluation indicator is mapped to the range of (0,100) using the equal distribution method, and divided into four levels: 75-100 points are good suitability, 50-75 points are relatively good suitability, 25-50 points are moderate suitability, and 0-25 points are poor suitability.

[0014] The beneficial effects of this invention are as follows: (1) Significantly improves the scientificity and objectivity of the evaluation: By introducing the decision laboratory analysis (DEMATEL) method, the expert experience is transformed from directly assigning weights to judging the mutual influence relationship between indicators, and the "centrality" and "causality" of each indicator are quantified based on strict matrix operations, thereby objectively identifying key driving indicators from the system level, greatly reducing subjective guessing and bias, and making the evaluation basis more solid and credible. (2) Greatly enhances the pertinence and accuracy of the evaluation: The innovative approach of "classification first, then calibration" is proposed. Based on the inherent characteristics of the seven types of geothermal reservoirs, a zoning and evaluation system combining "general indicators" and "pertinent indicators" is dynamically selected. This makes the evaluation of porous reservoirs focus on "porosity" and "permeability", while the evaluation of fractured reservoirs focuses on "fracture zone distribution", realizing a precise evaluation of "one type, one policy", and the results are more in line with geological reality. (3) Systematically handles the complex relationships between indicators: The core advantage of the DEMATEL method is that it can visualize and quantify the complex network relationships between indicators, distinguishing between "causal factors" (active drivers) and "outcome factors" (passive influencers). This not only helps to screen key indicators, but also allows decision-makers to understand the internal mechanisms of the system. For example, it can discover that "policy support" is the causal factor driving "economic costs" and "social acceptance", thus providing in-depth insights for formulating management strategies. (3) It achieves standardization and visualization of the evaluation process: It combines geographical methods such as dominant indicator method and overlay method with multi-criteria decision analysis (MCDA) and relies on the GIS platform to realize the entire evaluation process from single-factor zoning to multi-factor overlay, and then to the final result expression. The final result is an intuitive "suitability zoning map" rather than a simple numerical table, which greatly improves the practicality and interpretability of the results. (4) It strongly supports sustainable development and precise management: By accurately delineating "suitable areas", "restricted areas" and "prohibited areas", it can provide scientific decision-making basis for governments and enterprises. Projects are guided to prioritize development in areas with the best conditions, while areas unsuitable from a geological or techno-economic perspective are protected. This avoids resource waste and environmental damage caused by blind development and fundamentally ensures the sustainable development and utilization of geothermal resources. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of a suitability evaluation method for the development and utilization of a geothermal energy water extraction project. Detailed Implementation

[0016] The following examples will provide a more detailed explanation of this patent.

[0017] A suitability evaluation method for the development and utilization of geothermal energy water extraction projects includes the following steps: S1. Determine the type of geothermal resources: Obtain geological characteristic data of the target area, and classify the geothermal resources of the target area into one of seven types based on the genesis, structure and lithology of the reservoirs. The seven types include: porous layered reservoirs, fractured zoned reservoirs, fractured layered reservoirs, fractured zoned layered composite reservoirs, karst layered reservoirs, upper porous and lower karst composite layered reservoirs, and upper porous and lower fracture composite layered reservoirs. S2. Determine the multi-factor zoning of geothermal resources: Based on the geothermal reservoir type identified in step S1, zoning indicators are determined from the pre-established indicator library using the dominant indicator method. The zoning indicators are divided into targeted zoning indicators and general zoning indicators. Using geographic information system tools, single-factor zoning maps of each selected indicator are drawn respectively. Then, the single-factor zoning maps are spatially superimposed using the overlay method to generate a multi-factor comprehensive zoning map of the target area, dividing the target area into several evaluation zones. The pre-established index database includes natural geographical factors and social factors. The natural geographical factors include landforms, geology, hydrology, climate, mineral resources, and vegetation. The social factors include policies, regulations, and human activities.

[0018] The zoning indicators include geological structure, lithology, geothermal fluid hydrochemistry, reservoir water-bearing capacity, land use, porosity, permeability, total dissolved solids, fault zone distribution, and reservoir temperature.

[0019] The general zoning indicators are applicable to all seven types of geothermal reservoirs, including: geological structure, lithology, geothermal fluid hydrochemistry, reservoir water abundance, and land use. The specific zoning indicators are selected based on a particular reservoir type, with the following correspondences: for porous layered reservoirs, the specific zoning indicator is geological structure; for fractured zonal reservoirs, the specific zoning indicator is fault zone distribution; for fractured layered reservoirs and fractured zonal-layered composite reservoirs, the specific zoning indicator is reservoir temperature; for karst layered reservoirs, the specific zoning indicator is total dissolved solids; for upper porous and lower karst composite layered reservoirs, the specific zoning indicators are porosity, permeability, and total dissolved solids; for upper porous and lower fractured composite layered reservoirs, the specific zoning indicators are porosity and permeability.

[0020] The specific process of generating a multi-factor integrated zoning map using the overlay method includes: S2-1: Overlay two different single-factor zoning maps to generate a two-factor overlay map; S2-2: Using the two-factor overlay plot as the base layer, continue to overlay a third single-factor zoning plot to generate a three-factor overlay plot; S2-3: Repeat step S2-2 until all the single-factor zoning maps corresponding to all selected zoning indicators are superimposed to generate the final multi-factor comprehensive zoning map. S2-4: For small linear or dot-like regions generated after overlay, a nearest-neighbor merging strategy is used to merge them into adjacent larger blocks.

[0021] S3. Key evaluation indicator identification steps: Construct a system of influencing factors for the development and utilization of geothermal energy water extraction projects. This system includes four criteria layers: geology, technology, policy and regulations, and economic market, as well as 20 indicator layers under them. The 20 index factors are as follows: Geological factors include 8 indicators: geological structure, topography, soil and rock type, geothermal fluid hydrochemistry type, aquifer thickness, porosity, geothermal resource reserves, and the degree of guarantee of lateral recharge during extraction; Technological factors include 5 indicators: water extraction technology, reinjection technology, reservoir management, unit water output, and groundwater drawdown; Policy and regulations factors include 3 indicators: policy support, environmental regulations, and local regulations; Economic and market factors include 4 indicators: economic cost, energy demand and market, social acceptance, and insurance and risk management. The decision laboratory analysis method was used to process the expert scoring data, calculate the influence degree D, the degree of influence C, the centrality M and the causality R of each indicator, and select a predetermined number of indicators as key evaluation indicators based on the centrality M from high to low. The specific process of processing expert scoring data using the decision laboratory analysis method includes: S3-1. Construct an indicator system: Establish an indicator system that includes four categories of factors: geology, technology, policies and regulations, and economic market, and collect basic data on these factors; S3-2. Establish the direct influence matrix: using x ij The direct influence of factor i on factor j is represented by the score of relevant literature and expert questionnaires. The influence is classified into no influence, weak influence, weak influence, strong influence, and very strong influence, and assigned scores of 0, 1, 2, 3, and 4 respectively, to obtain the direct influence moment of the suitability of geothermal energy development and utilization water intake projects. S3-3, Calculate the normalized influence matrix G and the comprehensive influence matrix T: Determine the logical relationships between influencing factors, and calculate the normalized influence matrix G and the comprehensive influence matrix T. Where I is an n×n identity matrix, and n is the number of factors; S3-4. Calculate the influence degree D, the degree of influence C, the centrality M, and the degree of causation R: S3-5. Identify key evaluation indicators based on centrality and causality.

[0022] S4. Calculate the geothermal resource evaluation score: Based on the key evaluation indicators selected in S3, a hierarchical analysis model is constructed. The weights of each key evaluation indicator are calculated through pairwise comparison judgment matrices. Simultaneously, each key evaluation indicator within each evaluation zone is quantitatively graded and scored, with a score range of 0-100. Finally, a linear weighted sum method is used to multiply the scores of each key evaluation indicator by their corresponding weights and sum them to calculate the comprehensive water intake suitability score for each evaluation zone. The suitability level of the zone is determined based on the interval in which the comprehensive score falls. The quantitative grading and scoring process is as follows: the evaluation value of each key evaluation indicator is mapped to the interval (0, 100) using the equal distribution method and divided into four levels: 75-100 points for good suitability, 50-75 points for relatively good suitability, 25-50 points for moderate suitability, and 0-25 points for poor suitability.

Claims

1. A suitability evaluation method for the development and utilization of geothermal energy water extraction projects, characterized in that, It includes the following steps: S1. Determine the type of geothermal resources: Obtain geological characteristic data of the target area, and classify the geothermal resources of the target area into one of seven types of geothermal reservoirs based on the genesis, structure and lithological conditions of the reservoirs. The seven types of geothermal reservoirs include: porous layered geothermal reservoirs, fractured zoned geothermal reservoirs, fractured layered geothermal reservoirs, fractured zoned layered composite geothermal reservoirs, karst layered geothermal reservoirs, upper porous lower karst composite layered geothermal reservoirs, and upper porous lower fracture composite layered geothermal reservoirs. S2. Determine the multi-factor zoning of geothermal resources: Based on the geothermal reservoir type identified in step S1, zoning indicators are determined from the pre-established indicator library using the dominant indicator method. The zoning indicators are divided into targeted zoning indicators and general zoning indicators. Using geographic information system tools, single-factor zoning maps of each selected indicator are drawn respectively. Then, the single-factor zoning maps are spatially superimposed using the overlay method to generate a multi-factor comprehensive zoning map of the target area, dividing the target area into several evaluation zones. S3. Key Evaluation Indicator Identification Steps: Construct a system of influencing factors for the development and utilization of geothermal energy water extraction projects. This system includes four criteria layers: geology, technology, policy and regulations, and economic market, as well as 20 indicator layers under them. Use the decision laboratory analysis method to process expert scoring data, calculate the influence degree D, the degree of influence C, the centrality M, and the causality R of each indicator, and select a predetermined number of indicators as key evaluation indicators based on the centrality M from high to low. S4. Calculate the geothermal resource evaluation score: Based on the key evaluation indicators selected in S3, construct an analytic hierarchy process (AHP) model and calculate the weight of each key evaluation indicator through pairwise comparison judgment matrices. Simultaneously, quantify and grade each key evaluation indicator within each evaluation zone, with a score range of 0-100 points. Finally, using a linear weighted sum method, multiply the score of each key evaluation indicator by its corresponding weight and sum them to calculate the comprehensive water intake suitability score for each evaluation zone. Determine the suitability level of the zone based on the interval in which the comprehensive score falls.

2. The suitability evaluation method for the development and utilization of geothermal energy water extraction projects according to claim 1, characterized in that, The pre-established index library mentioned in S2 includes natural geographical factors and social factors. The natural geographical factors include landforms, geology, hydrology, climate, mineral resources, and vegetation; the social factors include policies, regulations, and human activities.

3. The suitability evaluation method for the development and utilization of geothermal energy water extraction projects according to claim 1, characterized in that, The zoning indicators mentioned in S2 include geological structural morphology, lithology, geothermal fluid hydrochemical type, reservoir water-bearing capacity, land use, porosity, permeability, total dissolved solids, fault zone distribution, and reservoir temperature.

4. The suitability evaluation method for the development and utilization of geothermal energy water extraction projects according to claim 1, characterized in that, The general zoning indicators mentioned in S2 are applicable to all seven types of geothermal reservoirs, including: geological structure, lithology, geothermal fluid hydrochemistry, reservoir water abundance, and land use. The specific zoning indicators are selected based on a particular reservoir type, and their correspondence is as follows: for porous layered reservoirs, the specific zoning indicator is geological structure; for fractured zoned reservoirs, the specific zoning indicator is fault zone distribution; for fractured layered reservoirs and fractured zoned-layered composite reservoirs, the specific zoning indicator is reservoir temperature; for karst layered reservoirs, the specific zoning indicator is total dissolved solids; for upper porous and lower karst composite layered reservoirs, the specific zoning indicators are porosity, permeability, and total dissolved solids; for upper porous and lower fractured composite layered reservoirs, the specific zoning indicators are porosity and permeability.

5. The suitability evaluation method for the development and utilization of geothermal energy water extraction projects according to claim 1, characterized in that, The specific process for generating a multi-factor integrated zoning map using the overlay method described in S2 includes: S2-1: Overlay two different single-factor zoning maps to generate a two-factor overlay map; S2-2: Using the two-factor overlay plot as the base layer, continue to overlay a third single-factor zoning plot to generate a three-factor overlay plot; S2-3: Repeat step S2-2 until all the single-factor zoning maps corresponding to all selected zoning indicators are superimposed to generate the final multi-factor comprehensive zoning map. S2-4: For small linear or dot-like regions generated after overlay, a nearest-neighbor merging strategy is used to merge them into adjacent larger blocks.

6. The suitability evaluation method for the development and utilization of a geothermal energy water extraction project according to claim 1, characterized in that, The specific process for processing expert scoring data using the decision laboratory analysis method described in S3 includes: S3-1. Construct an indicator system: Establish an indicator system that includes four categories of factors: geology, technology, policies and regulations, and economic market, and collect basic data on these factors; S3-2. Establish the direct influence matrix: using x ij The direct influence of factor i on factor j is represented by the score of relevant literature and expert questionnaires. The influence is classified into no influence, weak influence, weak influence, strong influence, and very strong influence, and assigned scores of 0, 1, 2, 3, and 4 respectively, to obtain the direct influence moment of the suitability of geothermal energy development and utilization water intake projects. S3-3, Calculate the normalized influence matrix G and the comprehensive influence matrix T: Determine the logical relationships between influencing factors, and calculate the normalized influence matrix G and the comprehensive influence matrix T. Where I is an n×n identity matrix, and n is the number of factors; S3-4. Calculate the influence degree D, the degree of influence C, the centrality M, and the degree of causation R: S3-5. Identify key evaluation indicators based on centrality and causality.

7. The suitability evaluation method for the development and utilization of a geothermal energy water extraction project according to claim 1, characterized in that, The 20 index factors mentioned in step S3 are as follows: Geology includes 8 indicators, namely geological structure, topography, soil and rock type, geothermal fluid hydrochemistry type, aquifer thickness, porosity, geothermal resource reserves, and the degree of guarantee of lateral recharge during extraction; Technology includes 5 indicators, namely water extraction technology, reinjection technology, reservoir management, unit water output, and groundwater drawdown; Policy and regulations include 3 indicators, namely policy support, environmental protection regulations, and local regulations; Economic market includes 4 indicators, namely economic cost, energy demand and market, social acceptance, and insurance and risk management.

8. The suitability evaluation method for the development and utilization of geothermal energy water extraction projects according to claim 1, characterized in that, The quantitative grading and scoring process described in step S4 is as follows: the evaluation value of each key evaluation indicator is mapped to the interval (0,100) using the average method and divided into four levels: 75-100 points are good suitability, 50-75 points are relatively good suitability, 25-50 points are moderate suitability, and 0-25 points are poor suitability.

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