Demand-optimization-oriented hydrothermal geothermal resource evaluation method

Abstract

The invention discloses a demand optimization-oriented hydrothermal geothermal resource evaluation method, and relates to the technical field of geothermal resource quality and development and utilization time sequence classification evaluation, and the method comprises the steps: determining a relative importance relationship between evaluation indexes of an evaluation object through an expert scoring system, and carrying out the evaluation of the evaluation object based on the relative importance relationship. And constructing a judgment matrix for the evaluation object, determining the weight and the standardized numerical value of each evaluation index, multiplying and accumulating the weight of each evaluation index and the corresponding standardized numerical value to obtain a comprehensive score, and determining an evaluation result of the evaluation object according to the comprehensive score. It can be seen that the relative importance relation of the evaluation indexes is determined through the expert scoring system, the indexes of the resource demand side and the resource supply side are comprehensively considered, the judgment matrix is constructed, accurate evaluation of the evaluation object is achieved, and therefore the actual development decision is better guided.

Description

Technical Field

[0001] The present invention relates to the technical field of geothermal resource quality and development and utilization time series classification evaluation, and specifically to a demand-optimized hydrothermal geothermal resource evaluation method. Background Art

[0002] Geothermal resources are an important non-carbon-based renewable energy source with the advantages of large reserves, wide distribution, stability and reliability, cleanliness and environmental protection. They have a wide range of application scenarios in urban heating and cooling, tourism and facility agriculture. According to the depth of burial, temperature and energy storage medium, geothermal resources are generally divided into shallow geothermal energy, medium and deep geothermal resources (hydrothermal type, rock thermal type) and hot dry rocks, which correspond to different resource evaluation methods and development and utilization methods. From a national perspective, hydrothermal geothermal resources are currently the main development and utilization objects, and the utilization direction is mainly geothermal heating and hot spring tourism. Market demand and policy are the main driving forces for their development and utilization. For decision makers who are preparing to invest in the development of hydrothermal geothermal resources, especially resource managers, it is particularly important to establish a simple, feasible, scientific and intuitive evaluation method based on resource endowments while taking into account development needs and utilization directions.

[0003] In the related technologies, the quantity and quality of hydrothermal geothermal resources are mainly evaluated based on their supply side (resource endowment), and there is a lack of comprehensive consideration of the demand side (demand policy) of hydrothermal geothermal resources, which leads to a disconnect between the evaluation results of hydrothermal geothermal resources and actual development. In addition, the judgment matrix constructed for hydrothermal geothermal resources is not accurate enough, which makes the evaluation results of hydrothermal geothermal resources determined based on the judgment matrix not accurate enough, and thus has limitations in guiding actual development decisions. Summary of the invention

[0004] In order to solve the above technical problems, the present invention is implemented through the following technical solutions: a hydrothermal geothermal resource evaluation method oriented to demand optimization, comprising:

[0005] Determining the relative importance relationship between various evaluation indicators of the evaluation object through an expert scoring system; wherein the evaluation indicators include indicators for reflecting the resource demand side of the evaluation object and indicators for reflecting the resource supply side of the evaluation object;

[0006] Based on the relative importance relationship, construct a judgment matrix for the evaluation object, and use the judgment matrix to determine the weight of each evaluation indicator;

[0007] Collecting the original data corresponding to each evaluation index, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index, to obtain the standardized value corresponding to the original data;

[0008] The weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object;

[0009] According to the comprehensive score of the evaluation object, the evaluation object is divided into regions to obtain the evaluation result of the evaluation object.

[0010] Preferably, the evaluation objects include hot springs with point distribution determined based on the uplift mountain convection-type geothermal resources among the hydrothermal geothermal resources or counties with surface distribution determined based on the sedimentary basin conduction-type geothermal resources among the hydrothermal geothermal resources. The single utilization direction corresponding to the uplift mountain convection-type geothermal resources is hot spring tourism, and the single utilization direction corresponding to the sedimentary basin conduction-type geothermal resources is geothermal heating.

[0011] Preferably, the evaluation index of the hot spring includes a primary evaluation index corresponding to the hot spring and a secondary evaluation index corresponding to the hot spring, the judgment matrix is ​​a multi-level judgment matrix, and the judgment matrix is ​​constructed for the evaluation object based on the relative importance relationship, and the weight of each evaluation index is determined by using the judgment matrix, including:

[0012] Based on the relative importance relationship between each first-level evaluation index of the hot spring, a first-level judgment matrix of the hot spring is constructed; based on the relative importance relationship between each second-level evaluation index of the hot spring, a second-level judgment matrix corresponding to each first-level evaluation index of the hot spring is constructed; the first-level judgment matrix of the hot spring and each second-level judgment matrix of the hot spring constitute a multi-level judgment matrix of the hot spring;

[0013] Using the multi-level judgment matrix, determining the weights of the secondary evaluation indicators of the hot spring;

[0014] Accordingly, the collecting of the original data corresponding to the respective evaluation indicators, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation indicator to obtain the standardized value corresponding to the original data, includes:

[0015] Collecting the original data corresponding to each secondary evaluation index of the hot spring, and performing interval standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index, to obtain the standardized value corresponding to the original data;

[0016] The weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object, including:

[0017] The weights of the secondary evaluation indicators of the hot spring are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the hot spring.

[0018] Preferably, the evaluation index of the county includes the primary evaluation index corresponding to the county and the secondary evaluation index corresponding to the county, the judgment matrix is ​​a multi-level judgment matrix, and the judgment matrix is ​​constructed for the evaluation object based on the relative importance relationship, and the weight of each evaluation index is determined by using the judgment matrix, including:

[0019] Based on the relative importance relationship between each first-level evaluation index of the county, a first-level judgment matrix of the county is constructed; based on the relative importance relationship between each second-level evaluation index of the county, a second-level judgment matrix corresponding to each first-level evaluation index of the county is constructed; the first-level judgment matrix of the county and each second-level judgment matrix of the county constitute a multi-level judgment matrix of the county;

[0020] Using the multi-level judgment matrix, determine the weight of each secondary evaluation index of the county;

[0021] Accordingly, the collecting of the original data corresponding to the respective evaluation indicators, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation indicator to obtain the standardized value corresponding to the original data, includes:

[0022] Collecting the original data corresponding to each secondary evaluation index of the county, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index, to obtain the standardized value corresponding to the original data;

[0023] The weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object, including:

[0024] The weights of the secondary evaluation indicators of the county are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the county.

[0025] Preferably, the multi-level judgment matrix is ​​a matrix constructed for the evaluation object in a single utilization direction based on the hierarchical analysis method.

[0026] Preferably, the evaluation index of the evaluation object includes a first evaluation index and a second evaluation index, and the relative importance relationship between the evaluation indexes of the evaluation object is determined by the expert scoring system, including:

[0027] Selecting industry experts to score the relative importance relationship between the first evaluation indicator and the second evaluation indicator, thereby obtaining an expert scoring result corresponding to the relative importance relationship between the first evaluation indicator and the second evaluation indicator;

[0028] A consistency check is performed on the expert scoring results, and the average value of the expert scoring results that pass the consistency check is used as a representation of the relative importance relationship between the first evaluation indicator and the second evaluation indicator; wherein the expert scoring system adopts a combination of qualitative and quantitative methods to determine the relative importance relationship between each evaluation indicator.

[0029] Preferably, the step of performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index to obtain the standardized value corresponding to the original data includes:

[0030] If the standardized value assignment intervals corresponding to the preset evaluation index are four intervals, the four intervals are used to perform interval standardized value assignment on the original data, and the standardized values ​​corresponding to the original data are obtained as 25 points, 50 points, 75 points, and 100 points respectively;

[0031] If the standardized value assignment intervals corresponding to the preset evaluation index are five intervals, the five intervals are used to perform interval standardized value assignment on the original data, and the standardized values ​​corresponding to the original data are 20 points, 40 points, 60 points, 80 points, and 100 points respectively.

[0032] Preferably, the weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object, including:

[0033] The weight of each evaluation indicator is multiplied by its corresponding standardized data to obtain the score of each evaluation indicator, and the scores of each evaluation indicator are added together to obtain the comprehensive score of the evaluation object;

[0034] Preferably, dividing the evaluation object according to the comprehensive score of the evaluation object to obtain the evaluation result of the evaluation object includes:

[0035] Based on the comprehensive score of the evaluation object, the evaluation object is divided into three zoning levels: high potential, medium potential and low potential; wherein, the zoning level is used to characterize the evaluation result of the evaluation object, the evaluation object with the comprehensive score in the top 25% is classified into the high potential level, the evaluation object with the comprehensive score in the middle 50% is classified into the medium potential level, and the evaluation object with the comprehensive score in the bottom 25% is classified into the low potential level, and the high potential level, the medium potential level and the low potential level correspond to three development and utilization time sequences of priority development, encouraged development and suspended development respectively.

[0036] The present invention provides a demand-optimized hydrothermal geothermal resource evaluation method, which has the following beneficial effects:

[0037] The demand-optimized hydrothermal geothermal resource evaluation method disclosed herein determines the relative importance relationship between various evaluation indicators of the evaluation object through an expert scoring system, so that the judgment matrix determined based on the relative importance relationship is more accurate, thereby more accurately evaluating the evaluation object. In addition, when evaluating the evaluation object, the indicators on the resource demand side and the resource supply side of the evaluation object are also comprehensively considered, so that the results of the evaluation object are more accurate and can better guide actual development decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A flow chart of a demand-optimized hydrothermal geothermal resource evaluation method provided in an embodiment of the present disclosure;

[0039] Figure 2 A flow chart of another demand-optimized hydrothermal geothermal resource evaluation method provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0040] The present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for the purpose of illustration and description, and are not intended to be exhaustive or to limit the present invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention, and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

[0041] In order to make the results of the evaluation object more accurate and to better guide actual development decisions, the embodiment of the present disclosure provides a hydrothermal geothermal resource evaluation method oriented to demand optimization.

[0042] Specifically, the relative importance relationship between each evaluation index of the evaluation object is determined by the expert scoring system, wherein the evaluation index includes an index for reflecting the resource demand side of the evaluation object and an index for reflecting the resource supply side of the evaluation object. Based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the weight of each evaluation index is determined by using the judgment matrix, and the original data corresponding to each evaluation index is collected, and based on the standardized value interval corresponding to the preset evaluation index, the original data is interval standardized and assigned to obtain the standardized value corresponding to the original data, and the weight of each evaluation index is multiplied and accumulated with the corresponding standardized value to obtain the comprehensive score of the evaluation object, and the evaluation object is divided according to the comprehensive score of the evaluation object to obtain the evaluation result of the evaluation object. It can be seen that the present disclosure determines the relative importance relationship between each evaluation index of the evaluation object through the expert scoring system, so that the judgment matrix determined based on the relative importance relationship is more accurate, thereby more accurately evaluating the evaluation object. In addition, when evaluating the evaluation object, the indicators of the resource demand side and the resource supply side of the evaluation object are also comprehensively considered, so that the result of the evaluation object is more accurate, which can better guide the actual development decision.

[0043] In order to solve the above problems, the embodiments of the present disclosure provide a method for evaluating hydrothermal geothermal resources for demand optimization, which is introduced below in conjunction with specific embodiments.

[0044] Figure 1 A flow chart of a demand-optimized hydrothermal geothermal resource evaluation method provided in an embodiment of the present disclosure, the method comprising:

[0045] S101: Determine the relative importance relationship between various evaluation indicators of the evaluation object through an expert scoring system.

[0046] The evaluation indicators include indicators for reflecting the resource demand side of the evaluation object and indicators for reflecting the resource supply side of the evaluation object.

[0047] The expert scoring system is a system used to collect and summarize the opinions of experts in the field. By integrating the professional knowledge and experience of multiple experts in the field, it aims to score the relative importance relationship between various evaluation indicators to determine the relative importance of various evaluation indicators.

[0048] Specifically, a preset number of industry experts may be selected to determine the relative importance of various evaluation indicators through a scoring system.

[0049] In practical applications, the SAATY scale can be used to quantify the relative importance of each evaluation indicator.

[0050] Through the expert scoring system, this step ensures that the determination of the relative importance relationship between the various evaluation indicators of the evaluation object is both scientific and reasonable, making the judgment matrix determined based on the relative importance relationship more accurate, thereby more accurately evaluating the evaluation object. In addition, the reliability of the relative importance relationship between the various evaluation indicators of the evaluation object can be further ensured through consistency testing. Specifically, for the specific introduction to consistency testing, please refer to the following description.

[0051] The evaluation object may be any object that requires resource evaluation.

[0052] Preferably, the evaluation objects include hot springs with point distribution determined by uplift mountain convection-type geothermal resources among hydrothermal geothermal resources or counties with surface distribution determined by sedimentary basin conduction-type geothermal resources among hydrothermal geothermal resources. The single utilization direction corresponding to the uplift mountain convection-type geothermal resources is hot spring tourism, and the single utilization direction corresponding to the sedimentary basin conduction-type geothermal resources is geothermal heating.

[0053] Specifically, uplift mountain convection-type geothermal resources generally refer to naturally exposed hot springs, and sedimentary basin conduction-type geothermal resources generally refer to geothermal fluids directly exploited and utilized through artificial drilling.

[0054] like Figure 2 As shown, it is a flow chart of another demand-optimized hydrothermal geothermal resource evaluation method provided by an embodiment of the present disclosure. When the evaluation object is a point-distributed hot spring determined based on the uplifted mountain convection geothermal resources in the hydrothermal geothermal resources, the evaluation index of the hot spring includes a primary evaluation index corresponding to the hot spring and a secondary evaluation index corresponding to the hot spring. The primary evaluation index corresponding to the hot spring includes fluid quality, location conditions, development needs and policies, among which fluid quality and location conditions are used to reflect the indicators of the resource supply side of the hot spring, and development needs and policies are used to reflect the indicators of the resource demand side of the hot spring. The secondary evaluation indicators corresponding to the hot spring include water temperature, water volume, water quality, transportation, population, GDP (gross domestic product) and regulated quantities, among which water temperature, water volume, water quality and transportation are used to reflect the indicators of the resource supply side of the hot spring, and population, GDP and regulated quantities are used to reflect the indicators of the resource demand side of the hot spring.

[0055] When the evaluation object is a county with a planar distribution determined based on the sedimentary basin conductive geothermal resources in the hydrothermal geothermal resources, the evaluation indicators of the county include the first-level evaluation indicators corresponding to the county and the second-level evaluation indicators corresponding to the county. The first-level evaluation indicators corresponding to the county include resource conditions, development potential, development needs and policies, among which resource conditions and development potential are used to reflect the indicators of the resource supply side of the county, and development needs and policies are used to reflect the indicators of the resource demand side of the county. The second-level evaluation indicators corresponding to the county include recoverable heat, water quality, exploration degree, population, GDP, heating time and number of regulations involved, among which recoverable heat, water quality and exploration degree are used to reflect the indicators of the resource supply side of the county, and population, GDP, heating time and number of regulations involved are used to reflect the indicators of the resource demand side of the county.

[0056] In addition, in the embodiment of the present disclosure, the evaluation index of the evaluation object comprehensively considers the resource demand side and the resource supply side of the evaluation object, ensuring that the evaluation result is more comprehensive and practical, making the result of the evaluation object more accurate and can better guide actual development decisions.

[0057] S102: Based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the weight of each evaluation indicator is determined using the judgment matrix.

[0058] In the embodiment of the present disclosure, the judgment matrix can be a multi-level judgment matrix. Accordingly, the multi-level judgment matrix can be constructed based on the hierarchical analysis method. Taking the evaluation object including the first-level evaluation indicators and the second-level evaluation indicators as an example, specifically, the multi-level judgment matrix includes a first-level judgment matrix of the evaluation object constructed based on the relative importance relationship between the first-level evaluation indicators of the evaluation object, and a second-level judgment matrix corresponding to each first-level evaluation indicator of the evaluation object constructed based on the relative importance relationship between the second-level evaluation indicators of the evaluation object.

[0059] Preferably, the multi-level judgment matrix is ​​a matrix constructed for the evaluation object in a single utilization direction based on the hierarchical analysis method.

[0060] Preferably, when the evaluation object is a hot spring, the evaluation indicators of the hot spring include the first-level evaluation indicators corresponding to the hot spring and the second-level evaluation indicators corresponding to the hot spring. Based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the weight of each evaluation indicator is determined using the judgment matrix, including: based on the relative importance relationship between each first-level evaluation indicator of the hot spring, a first-level judgment matrix for the hot spring is constructed; based on the relative importance relationship between each second-level evaluation indicator of the hot spring, a second-level judgment matrix corresponding to each first-level evaluation indicator of the hot spring is constructed; the first-level judgment matrix of the hot spring and each second-level judgment matrix of the hot spring constitute a multi-level judgment matrix for the hot spring; the weight of each second-level evaluation indicator of the hot spring is determined using the multi-level judgment matrix.

[0061] like Figure 2 As shown, the first-level evaluation indicators corresponding to hot springs include fluid quality, location conditions, development needs, and policies. First, based on the relative importance relationship between the various first-level evaluation indicators of hot springs, a first-level judgment matrix for hot springs is constructed, as shown in Table 3 below. Then, the second-level judgment matrices corresponding to each first-level evaluation indicator are constructed for the hot springs, as shown in Tables 4 to 5 below. Among them, Tables 3 to 5 constitute a multi-level judgment matrix for hot springs.

[0062] When the evaluation object is a county, the evaluation indicators of the county include the first-level evaluation indicators corresponding to the county and the second-level evaluation indicators corresponding to the county. Based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the weight of each evaluation indicator is determined by using the judgment matrix, including: based on the relative importance relationship between each first-level evaluation indicator of the county, a first-level judgment matrix of the county is constructed; based on the relative importance relationship between each second-level evaluation indicator of the county, a second-level judgment matrix corresponding to each first-level evaluation indicator of the county is constructed; the first-level judgment matrix of the county and each second-level judgment matrix of the county constitute a multi-level judgment matrix of the county; the weight of each second-level evaluation indicator of the county is determined by using the multi-level judgment matrix.

[0063] like Figure 2 As shown in Figure 1, the first-level evaluation indicators corresponding to the county include resource conditions, development potential, development needs, and policies. First, based on the relative importance relationship between the various first-level evaluation indicators of the county, the first-level judgment matrix of the county is constructed, as shown in Table 14 below. Then, the second-level judgment matrices corresponding to the various first-level evaluation indicators of the county are constructed separately, as shown in Tables 15 and 16 below. Among them, Tables 14 to 16 constitute a multi-level judgment matrix of the county.

[0064] In the disclosed embodiment, the multi-level judgment matrix can be analyzed based on the product method to obtain the weight of each evaluation index.

[0065] Specifically, for the specific method of determining the weights of each secondary evaluation index of hot springs and the weights of each secondary evaluation index of counties, please refer to the description of the following embodiments.

[0066] S103: Collecting the original data corresponding to each evaluation index, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index to obtain a standardized value corresponding to the original data.

[0067] In the disclosed embodiment, the raw data corresponding to the evaluation index may be a specific numerical value directly measured by the evaluation index. For example, when the evaluation index is water temperature, the raw data corresponding to the water temperature is the water temperature value measured within a specific time period (such as one day or one week).

[0068] The standardized value interval corresponding to the preset evaluation index is a process of converting raw data of different units and dimensions into a unified scale, which enables different evaluation indicators to be compared and comprehensively evaluated under the same standard.

[0069] Exemplarily, when the evaluation index is water temperature, the standardized value interval corresponding to the preset evaluation index can be as shown in Table 1 below. For example, when the water temperature is 95°C, by performing interval standardized value assignment on the original water temperature data, the standardized value corresponding to the original water temperature data can be obtained as 100.

[0070] This step involves collecting raw data related to the evaluation indicators and performing interval standardization to enhance the comparability of data for different indicators. Standardization not only eliminates the influence of data units and dimensions, but also makes the data more intuitive and facilitates subsequent calculations and analysis.

[0071] Preferably, if the standardized value assignment intervals corresponding to the preset evaluation indicators are four intervals, the original data are interval-standardized and assigned using the four intervals, and the standardized values ​​corresponding to the original data are 25 points, 50 points, 75 points, and 100 points, respectively.

[0072] If the standardized value assignment interval corresponding to the preset evaluation index is five intervals, the five intervals are used to perform interval standardized value assignment on the original data, and the standardized values ​​corresponding to the original data are 20 points, 40 points, 60 points, 80 points, and 100 points respectively.

[0073] Preferably, when the evaluation object is the above-mentioned hot spring, the original data corresponding to each secondary evaluation index of the hot spring are collected, and based on the standardized assignment interval corresponding to the preset evaluation index, the original data is interval-standardized and assigned to obtain the standardized value corresponding to the original data.

[0074] When the evaluation object is the above-mentioned county, the original data corresponding to each secondary evaluation index of the county are collected, and based on the standardized assignment interval corresponding to the preset evaluation index, the original data is interval-standardized and assigned to obtain the standardized value corresponding to the original data.

[0075] S104: Multiply and add the weight of each evaluation indicator by its corresponding standardized value to obtain a comprehensive score of the evaluation object.

[0076] In the disclosed embodiment, by multiplying and adding the weight of each evaluation indicator with its corresponding standardized value, a comprehensive score of the evaluation object can be obtained, which comprehensively reflects the performance of the evaluation object in multiple dimensions and provides a quantitative basis for the final evaluation result.

[0077] Preferably, the weight of each evaluation indicator is multiplied by its corresponding standardized data to obtain the score of each evaluation indicator, and the scores of each evaluation indicator are added together to obtain the comprehensive score of the evaluation object.

[0078] In the disclosed embodiment, when the evaluation object is the above-mentioned hot spring, the weights of each secondary evaluation index of the hot spring are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the hot spring. When the evaluation object is the above-mentioned county, the weights of each secondary evaluation index of the county are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the county.

[0079] S105: According to the comprehensive score of the evaluation object, the evaluation object is divided into regions to obtain the evaluation result of the evaluation object.

[0080] Preferably, based on the comprehensive scores of the evaluation objects, the evaluation objects are divided into three zoning levels: high potential, medium potential and low potential; wherein, the zoning levels are used to characterize the evaluation results of the evaluation objects, the evaluation objects with comprehensive scores in the top 25% are classified into the high potential level, the evaluation objects with comprehensive scores in the middle 50% are classified into the medium potential level, and the evaluation objects with comprehensive scores in the bottom 25% are classified into the low potential level, and the high potential level, medium potential level and low potential level correspond to the three development and utilization time sequences of priority development, encouraged development and suspended development, respectively.

[0081] The disclosed embodiment can divide the evaluation object into three levels according to the comprehensive score of the evaluation object. This division not only intuitively shows the development potential of the evaluation object, but also provides clear development suggestions for decision makers, namely, priority development, encouraged development and suspended development.

[0082] Through the technical effects in the above steps, a comprehensive, systematic and quantitative evaluation method is provided, which makes the evaluation of hydrothermal geothermal resources more scientific, objective and practical, and helps to guide actual resource development and management decisions.

[0083] To facilitate understanding of the embodiments of the present disclosure, the first-level evaluation indicators and second-level evaluation indicators corresponding to hot springs and counties are respectively introduced in detail below.

[0084] When the evaluation object is hot springs, the corresponding first-level evaluation indicators of hot springs include fluid quality, location conditions, development needs, and policies.

[0085] Among them, fluid quality represents the basic characteristics of hot springs, reflecting their physical and chemical properties; location conditions represent the geographical location of the hot springs, involving transportation and environmental factors; development demand represents the market demand for hot spring development and utilization, reflecting the potential demand for hot spring tourism due to population and economic development; and policy represents the government's relevant regulations and policy environment for hot spring development and utilization.

[0086] Specifically, the secondary evaluation indicators for fluid quality include water temperature, water volume and water quality; the secondary evaluation indicators for location conditions include transportation, development needs include population and GDP, and the secondary evaluation indicators for policies include the number of regulations involved. The above are the seven secondary evaluation indicators for hot springs.

[0087] Water temperature is used to quantify fluid quality and reflects the thermal characteristics of hot springs;

[0088] Water volume is used to quantify fluid quality and reflects the water output capacity of the hot spring;

[0089] Water quality is used to quantify fluid quality and reflect the therapeutic effects of hot springs;

[0090] Transportation is used to quantify location conditions, reflecting the accessibility and convenience of hot springs;

[0091] Population is used to quantify development needs and reflect potential demand;

[0092] GDP is used to quantify development needs and reflect economic level and consumption capacity;

[0093] The number of regulations involved is used to quantify policies and reflect the government’s support for the development and utilization of hot springs.

[0094] When the evaluation object is a county, the first-level evaluation indicators corresponding to the county include resource conditions, mining potential, development needs, and policies.

[0095] Among them, resource conditions are used to characterize the basic characteristics of geothermal resources in the county and reflect the status of available natural resources; exploitation potential is used to characterize the development potential of geothermal resources in the county and evaluate the degree of sustainable utilization; development demand is used to characterize the actual demand for geothermal resources in the county and reflect market demand; policies are used to characterize the government's relevant regulations and policy environment for the development and utilization of geothermal resources.

[0096] Specifically, the secondary evaluation indicators corresponding to resource conditions include recoverable heat and water quality, the secondary evaluation indicators corresponding to mining potential include exploration degree, development needs include population, GDP and heating time, and the secondary evaluation indicators corresponding to policies include the number of regulations involved. The above are the seven secondary evaluation indicators of the county.

[0097] Recoverable heat is used to quantify resource conditions and reflects the available amount of geothermal resources;

[0098] Water quality is used to quantify resource conditions and reflects the quality of geothermal resources;

[0099] The degree of exploration is used to quantify the exploitation potential and reflect the confidence level of geothermal resource conditions;

[0100] Population is used to quantify development needs and reflect potential demand;

[0101] GDP is used to quantify development needs and reflect economic level and consumption capacity;

[0102] Heating hours are used to quantify development demand and reflect the urgency of potential demand;

[0103] The number of regulations involved is used to quantify policies and reflect the government's support for geothermal development and utilization.

[0104] Preferably, the evaluation indicators of the evaluation object include a first evaluation indicator and a second evaluation indicator, and the relative importance relationship between the evaluation indicators of the evaluation object is determined by an expert scoring system, including: selecting industry experts to score the relative importance relationship between the first evaluation indicator and the second evaluation indicator, obtaining expert scoring results corresponding to the relative importance relationship between the first evaluation indicator and the second evaluation indicator, performing a consistency test on the expert scoring results, and taking the average value of the expert scoring results that pass the consistency test as a representation of the relative importance relationship between the first evaluation indicator and the second evaluation indicator.

[0105] Among them, the expert scoring system adopts a combination of qualitative and quantitative methods to determine the relative importance relationship between various evaluation indicators.

[0106] In the embodiment of the present disclosure, the first evaluation index and the second evaluation index may be any two evaluation indexes at the same level of the evaluation object, such as any two evaluation indexes in the above-mentioned first-level evaluation indexes and any two evaluation indexes in the second-level evaluation indexes.

[0107] In the disclosed embodiment, the selection of experts in the industry is based on their professional knowledge, practical experience and thorough understanding of geothermal resource evaluation; the expert scoring results are subjected to a consistency check, the consistency check is intended to ensure the reliability and rationality of the expert scoring results and reduce the impact of subjective bias on the evaluation results.

[0108] Specifically, the consistency check method is as follows:

[0109] The experts compare the importance of each evaluation indicator in the judgment matrix, determine the relative importance relationship between the indicators, and give the expert scoring results. The relative importance relationship is based on the scale of 1 to 9 in Table 1 below, such as the relative importance of the first evaluation indicator to the second evaluation indicator is an integer value from 1 (equally important) to 9 (extremely important).

[0110] Table 1 SAATY scale

[0111] SAATY Scale meaning 1 Both factors have equal importance 3 One factor is slightly more important than the other 5 One factor is significantly more important than the other 7 One factor is more important than another 9 One factor is more important than another 2、4、6、8 The importance of factors is compared between the above descriptions The reciprocal of the corresponding number The above description where one factor is less important than another

[0112] Perform consistency check on the judgment matrix. The consistency check formula is as follows:

[0113] CR=CI / RI

[0114] CI=(λ max -n) / (n-1)

[0115] Among them, CR (consistency ratio) is used to judge the consistency of the judgment matrix. The smaller the CR value, the better the consistency of the judgment matrix. Generally, the CR value is required to be less than 0.1.

[0116] CI (Consistency Index) is used to measure the consistency of the judgment matrix. The smaller the CI value, the better the consistency.

[0117] λ max (Maximum Eigenvalue) represents the maximum eigenvalue of the judgment matrix. It is related to the eigenvector of the judgment matrix and is an important parameter for calculating the consistency index CI.

[0118] n (matrix order) represents the number of rows (or columns) of the judgment matrix.

[0119] RI (Random Consistency Index) represents the average consistency index of random judgment matrices of different dimensions. The RI value is pre-calculated and is usually obtained by looking up the table based on the n value. The RI values ​​of judgment matrices of order 1 to 9 are shown in Table 2:

[0120] Table 2 Random consistency index RI value

[0121]

[0122] When CR is less than 10%, the consistency test passes. Otherwise, it is necessary to re-score the relative importance relationship between each evaluation indicator based on the expert scoring system or replace the corresponding scoring experts, and then re-score until CR is less than 10%, the consistency test passes. After the consistency test passes, based on the judgment matrix that passes the consistency test, the product method is used to calculate the parameters in the consistency test formula, and the weights of each evaluation indicator are obtained.

[0123] In the demand-optimization-oriented hydrothermal geothermal resource evaluation method provided by the embodiment of the present disclosure, the relative importance relationship between each evaluation index of the evaluation object is determined by an expert scoring system; wherein the evaluation index includes an index for reflecting the resource demand side of the evaluation object and an index for reflecting the resource supply side of the evaluation object, and based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the judgment matrix is ​​used to determine the weight of each evaluation index, collect the original data corresponding to each evaluation index, and based on the standardized assignment interval corresponding to the preset evaluation index, perform interval standardization on the original data to obtain the standardized value corresponding to the original data, and multiply and accumulate the weight of each evaluation index with its corresponding standardized value to obtain the comprehensive score of the evaluation object, and divide the evaluation object into zones according to the comprehensive score of the evaluation object to obtain the evaluation result of the evaluation object. It can be seen that the present disclosure determines the relative importance relationship between each evaluation index of the evaluation object through the expert scoring system, so that the judgment matrix determined based on the relative importance relationship is more accurate, thereby more accurately evaluating the evaluation object. In addition, when evaluating the evaluation object, the indicators of the resource demand side and the resource supply side of the evaluation object are also comprehensively considered, so that the results of the evaluation object are more accurate and can better guide actual development decisions.

[0124] In order to facilitate the understanding of the above embodiments, Figure 2 As shown, taking Qinghai Province as an example, the above method is used to carry out the evaluation of hydrothermal geothermal resources throughout the province. The process is as follows:

[0125] (1) Hot spring

[0126] Generally refers to naturally exposed hot springs, which are convection-type geothermal resources in uplifted mountains.

[0127] First, the relative importance relationship between the various evaluation indicators of hot springs is determined through the expert scoring system. Based on the relative importance relationship between the various primary evaluation indicators of hot springs, the primary judgment matrix of hot springs is constructed, as shown in Table 3 below:

[0128] Table 3 Evaluation object hot spring (A1) first-level judgment matrix

[0129]

[0130]

[0131] The above judgment matrix CR=0.0077, λ is calculated by the product method max =4.0206, CI=0.0069, RI=0.89, CR<0.1. Through the consistency test, the first-level evaluation index weights of hot springs are determined as follows: B1=0.478, B2=0.108, B3=0.197, B4=0.217.

[0132] Based on the relative importance relationship between the various secondary evaluation indicators of hot springs, a secondary judgment matrix corresponding to each primary evaluation indicator of hot springs is constructed, as shown in Tables 4 and 5 below:

[0133] Table 4 Fluid quality (B1) - Secondary judgment matrix

[0134] <![CDATA[B1]]> <![CDATA[C1]]> <![CDATA[C2]]> <![CDATA[C3]]> <![CDATA[C1]]> 1 3 5 <![CDATA[C2]]> 1 / 3 1 2 <![CDATA[C3]]> 1 / 5 1 / 2 1

[0135] The above judgment matrix CR=0.0032, λ is calculated by the product method max =3.0037, CI=0.0018, RI=0.58, CR<0.1, passed the consistency test, C1=0.648, C2=0.230, C3=0.122.

[0136] Table 5 Development Requirements (B3) - Secondary Evaluation Index Judgment Matrix

[0137] <![CDATA[B3]]> <![CDATA[C5]]> <![CDATA[C6]]> <![CDATA[C5]]> 1 2 <![CDATA[C6]]> 1 / 2 1

[0138] The above judgment matrix C5=0.667, C6=0.333 is calculated by using the product method.

[0139] According to C1+C2+C3=B1, C4=B2, C5+C6=B3, C7=B4, the weight of the secondary evaluation index of the evaluation object hot spring (A1) is: water temperature C 1新 =0.310, water volume C 2新 =0.110, water quality C 3新 =0.058, Traffic C 4新 =0.108, population C 5新 =0.131, GDP C 6新 =0.066, the number of regulations involved C 7新 =0.217.

[0140] Standardized value interval of evaluation index

[0141] ①Water temperature (C1)

[0142] Based on the highest outlet water temperature of the hot spring stated in the exploration report, the unit is ℃. According to the "Geothermal Resource Evaluation Method and Estimation Procedure" (DZ T 0331-2020), the geothermal resource temperature utilization classification, the standard of therapeutic hot mineral water and the characteristics of hot spring water temperature in Qinghai Province, five intervals are divided. The water temperature standardization assignment interval is as follows:

[0143] Table 6 Standardized value interval of water temperature (C1)

[0144] <![CDATA[C1]]> <![CDATA[C1≥90]]> <![CDATA[60≤C1<90]]> <![CDATA[36≤C1<60]]> <![CDATA[25≤C1<36]]> <![CDATA[C1<25]]> Assignment 100 80 60 40 20

[0145] ②Water volume (C2)

[0146] Based on the hot spring flow rate stated in the survey report, the unit is L / s. Referring to the classification of hot spring flow rate in the Geothermal Resource Assessment Manual of the United States Geological Survey and combined with the characteristics of hot spring water volume in Qinghai Province, four intervals are divided. The standardized value intervals of water volume are as follows:

[0147] Table 7 Standardized value intervals for water quantity

[0148] <![CDATA[C2]]> <![CDATA[10.0≤C2≤100]]> <![CDATA[1.0≤C2<10.0]]> <![CDATA[0.1≤C2<1.0]]> <![CDATA[C2<0.1]]> Assignment 100 75 50 25

[0149] ③Water quality (C3)

[0150] Based on the water quality test report, it is determined by the evaluation results of the comprehensive index scoring method in the "Groundwater Quality Standard" (GB / T 14848-93), dimensionless. The water quality standardization value range is as follows:

[0151] Table 8 Standardized value intervals for water quality

[0152] <![CDATA[C3]]> <![CDATA[C3 = excellent]]> <![CDATA[C3 = Good]]> <![CDATA[C3 = Better]]> <![CDATA[C3 = Poor]]> <![CDATA[C3 = range]]> Assignment 100 80 60 40 20

[0153] ④ Transportation (C4)

[0154] The time required to drive from the People's Government of the county where the hot spring is located, in minutes. According to the time tolerance of drivers and passengers and the distribution status of hot springs discovered in Qinghai Province, four intervals are divided. The traffic score standards are as follows:

[0155] Table 9 Standardized value intervals for traffic

[0156] <![CDATA[C4]]> <![CDATA[C4<50]]> <![CDATA[50≤C4<100]]> <![CDATA[100≤C4<200]]> <![CDATA[C4≥200]]> Assignment 100 75 50 25

[0157] ⑤ Population (C5)

[0158] The population of the county where the hot spring is located comes from the statistical bureau of each county. The data is counted until 2020, and the unit is 10,000 people. According to the State Council's "Notice on Adjusting the Standards for Classifying Urban Sizes" (Guofa

[2014] No. 51), which uses the permanent population of urban areas as the statistical caliber, cities are divided into five categories and seven grades, and the population of each county is combined for zoning. The standardized population assignment interval is as follows:

[0159] Table 10 Standardized value intervals for population

[0160] <![CDATA[C5]]> <![CDATA[300<C5]]> <![CDATA[100≤C5<300]]> <![CDATA[20≤C5<100]]> <![CDATA[10≤C5<20]]> <![CDATA[C5<10 <!-- 11 -->]]> Assignment 100 80 60 40 20

[0161] ⑥GDP (C6)

[0162] The GDP of the county where the hot spring is located comes from the statistical bureau of each county, and the statistics are up to 2021, in 100 million yuan. Since there is no zoning standard for GDP, the quartile method is used to divide the interval. The standardized value interval of GDP is as follows:

[0163] Table 11 Standardized value range of GDP

[0164] <![CDATA[C6]]> <![CDATA[500≤C6]]> <![CDATA[100≤C6<500]]> <![CDATA[10≤C6<100]]> <![CDATA[C6<10]]> Assignment 100 75 50 25

[0165] ⑦Number of regulations involved (C7)

[0166] The number of plans mainly comes from the mineral resource planning, national land space master plan, energy development plan, and financial plan (including pilot cities for clean winter heating in northern China) of 42 counties in Qinghai Province that were publicly released during the 14th Five-Year Plan period and involve the development and utilization of hot springs. The collection time ends at the end of 2023, and the unit is individual. The standardized value range of the number of plans involved is as follows:

[0167] Table 12 Standardized value ranges for the number of regulations involved

[0168] <![CDATA[C7]]> <![CDATA[C7≥4]]> <![CDATA[C7=3]]> <![CDATA[C7=2]]> <![CDATA[C7=1]]> <![CDATA[C7=0]]> Assignment 100 80 60 40 20

[0169] Specifically, the original data corresponding to each secondary evaluation index of the hot spring are determined, and based on the standardized value assignment intervals corresponding to each secondary evaluation index of the hot spring, the original data are interval-standardized and assigned to obtain standardized values ​​corresponding to the original data.

[0170] Then, the weights corresponding to the above-mentioned secondary evaluation indicators of hot springs (i.e., the water temperature C 1新 =0.310, water volume C 2新 =0.110, water quality C 3新 =0.058, Traffic C 4新 =0.108, population C 5新 =0.131, GDP C 6新 =0.066) is multiplied and added with the corresponding standardized value to obtain the comprehensive score of the hot spring. Then, the hot springs are divided into different areas according to the comprehensive score to obtain the evaluation result of the hot spring.

[0171] Table 13 Schematic diagram of the evaluation results of hydrothermal geothermal resources in Qinghai Province (hot springs)

[0172]

[0173]

[0174] Evaluation results

[0175] According to the calculation results, the evaluation results table 13 is obtained. The hot springs with the top 25% of the scores are evaluated as having great potential and are given priority for development; the middle 50% of the hot springs are evaluated as having medium potential and are encouraged to be developed; the bottom 25% of the hot springs are evaluated as having small potential and are temporarily suspended from development. In general, hot springs with high water temperature, policy support in the region, dense population, large water volume, convenient transportation, good economic foundation, and good water quality have great potential for development and utilization, and should be given priority in relevant planning or development plans.

[0176] (II) County

[0177] Generally refers to geothermal fluids that are directly exploited and utilized through artificial drilling (geothermal wells), which belong to the conductive geothermal resources of sedimentary basins;

[0178] First, the relative importance relationship between the various evaluation indicators of the county is determined through the expert scoring system. Based on the relative importance relationship between the various first-level evaluation indicators of the county, the first-level judgment matrix of the county is constructed, as shown in Table 14 below:

[0179] Table 14 Level 1 judgment matrix of the evaluation object county (A2)

[0180] <![CDATA[A2]]> <![CDATA[B5]]> <![CDATA[B6]]> <![CDATA[B7]]> <![CDATA[B8]]> <![CDATA[B5]]> 1 5 3 2 <![CDATA[B6]]> 1 / 5 1 1 / 2 1 / 4 <![CDATA[B7]]> 1 / 3 2 1 1 / 2 <![CDATA[B8]]> 1 / 2 4 2 1

[0181] The above judgment matrix CR is calculated by the product method. max =4.0211, CI=0.0070, RI=0.89, CR<0.1. Through the consistency test, the weights of the first-level evaluation indicators of the county are determined: B1=0.476, B2=0.082, B3=0.154, B4=0.288.

[0182] Based on the relative importance relationship between the various secondary evaluation indicators of the county, a secondary judgment matrix corresponding to each primary evaluation indicator of the county is constructed, as shown in Tables 15 and 16 below:

[0183] Table 15 Resource conditions (B5) - Secondary evaluation index judgment matrix

[0184]

[0185]

[0186] The above judgment matrix is ​​calculated by the product method, and after the consistency test, C1=0.667, C2=0.333.

[0187] Table 16 Evaluation object county (A2) secondary evaluation index judgment matrix - development demand (B7)

[0188] <![CDATA[B7]]> <![CDATA[C 11 ]]> <![CDATA[C 12 ]]> <![CDATA[C 13 ]]> <![CDATA[C 11 ]]> 1 3 2 <![CDATA[C 12 ]]> 1 / 3 1 1 <![CDATA[C 13 ]]> 1 / 2 1 1

[0189] The above judgment matrix CR is calculated by the product method. max =3.0183, CI = 0.0092, RI = 0.58, CR < 0.1, passed the consistency test, C 11 =0.548, C 12 =0.211, C 13 =0.241.

[0190] According to C8+C9=B5, C 10 =B6, C 11 +C 12 +C 13 =B7, C 14 =B8, thus the weight of the secondary evaluation index of the county (A2) is: recoverable heat C 8新 =0.317, water quality C 9新 =0.159, exploration level C 10新 =0.082, population C 11新 =0.084, GDP C 12新 =0.033, heating time C 13新 =0.037, the number of regulations involved C 14新 =0.288.

[0191] Standardized value interval of evaluation index

[0192] ①Recoverable heat (C8)

[0193] Based on the results of the exploration project calculation of the resources of the geothermal fields, hot springs and basins in the county (thermal reserve method), the spatial analysis method is used to comprehensively determine the unit of 10 15 J. Since there is no zoning standard for recoverable heat and the resource exploration level in the province is relatively low, in order to reflect the development and utilization potential, the standardized value range of recoverable heat is as follows:

[0194] Table 17 Standardized value range of recoverable heat

[0195] <![CDATA[C8]]> <![CDATA[10 6 ≤C8]]> <![CDATA[10 5 ≤C8<10 6 ]]> <![CDATA[10 4 ≤C8<10 5 ]]> <![CDATA[10 3 ≤C8<10 4 ]]> <![CDATA[C8<10 3 <!-- 13 -->]]> Assignment 100 80 60 40 20

[0196] ②Water quality (C9)

[0197] Based on the mineralization (TDS) results of geothermal wells and hot springs in the water quality test report, the plane contour mapping method and spatial analysis method are used to comprehensively determine the dimensionless value. The water quality standardization value interval is consistent with the water quality standardization value interval in the evaluation object hot spring. Among them, the mineralization (TDS) zoning standard is determined based on the "Classification and Grading of Groundwater Resources Reserves" (GB / T 15218-2021) and the "Geothermal Resources Evaluation Method and Estimation Procedure" (DZ / T 0331-2020).

[0198] Table 18 Mineralization (TDS) divisions

[0199] TDS(mg / L) TDS<1 1≤TDS<3 3≤TDS<10 10≤TDS<50 TDS≥50 category excellent good better Poor Very bad

[0200] ③ Exploration degree (C 10 )

[0201] It is determined comprehensively based on the exploration stage in the "Geothermal Resources Geological Exploration Specification" (GBT 11615-2010) and the "Guiding Opinions of the Ministry of Natural Resources and the Ministry of Finance on Formulating the Starting Price Standard for Mining Rights Transfer Income" (Natural Resources Development

[2023] No. 166), dimensionless. The standardized value range of the exploration degree is as follows:

[0202] Table 19 Standardized value intervals for exploration degree

[0203] <![CDATA[C 10 ]]> <![CDATA[C 10 =Mining]]> <![CDATA[C 10 =Feasibility Study]]> <![CDATA[C 10 =Pre-feasibility study]]> <![CDATA[C 10 =Investigation]]> <![CDATA[C 10 =Grassroots]]> Assignment 100 80 60 40 20

[0204] ④ Population (C 11 )

[0205] The permanent population data of each county comes from the National Bureau of Statistics, and the data are counted until 2020, in units of 10,000 people. The standardized population value interval is consistent with the standardized population value interval of the hot springs in the evaluation object.

[0206] ⑤GDP(C 12 )

[0207] The GDP data of each county mainly comes from the National Bureau of Statistics; the data is collected up to 2021, and the unit is 100 million yuan. The GDP standardization value interval is consistent with the GDP standardization value interval of the evaluation object hot spring.

[0208] ⑥ Heating time (C 13 )

[0209] The heating time data comes from the Qinghai Province Winter Clean Heating Implementation Plan (Qing Development and Reform Energy

[2019] No. 574) and is in days. The quartile method is used to divide the intervals for assignment, and the standardized assignment intervals for heating time are as follows:

[0210] Table 20 Standardized value intervals for heating time

[0211] <![CDATA[C 13 ]]> <![CDATA[240<C 13 ]]> <![CDATA[210<C 13 ≤240]]> <![CDATA[180<C 13 ≤210]]> <![CDATA[C 13 ≤180]]> Assignment 100 75 50 25

[0212] ⑦Number of regulations involved (C 14 )

[0213] Specifically, the original data corresponding to each secondary evaluation index of the county are determined, and based on the standardized value assignment intervals corresponding to each secondary evaluation index of the county, the original data are interval-standardized and assigned to obtain the standardized values ​​corresponding to the original data.

[0214] Then, the weights corresponding to the secondary evaluation indicators of the county obtained above are calculated (i.e., the weights of the secondary evaluation indicators of the county (A2) are: recoverable heat C 8新 =0.317, water quality C 9新 =0.159, exploration level C 10新 =0.082, population C 11新 =0.084, GDP C 12新 =0.033, heating time C 13新 =0.037, the number of regulations involved C 14新 =0.288) is multiplied and added with the corresponding standardized value to obtain the comprehensive score of the county. Then, the county is divided into regions according to the comprehensive score to obtain the evaluation result of the county.

[0215] Table 21 Schematic diagram of the evaluation results of hydrothermal geothermal resources in Qinghai Province (county level)

[0216] Sorting County comprehensive Evaluation results 1 County D 60 (top 25%) High potential level 2 County E 50 (middle 50%) Potential Medium 3 County F 40 (bottom 25%) Potential small level

[0217] Evaluation results

[0218] According to the calculation results, the evaluation results table 21 is obtained. The counties with the top 25% of the scores are evaluated as having great potential and are given priority for development; the middle 50% of the counties are evaluated as having medium potential and are encouraged to develop; the bottom 25% of the counties are evaluated as having small potential and are temporarily suspended from development. In general, counties with large recoverable heat, policy support, good water quality, dense population, high degree of exploration, strong heating demand, and good economic foundation have great potential for the development and utilization of geothermal resources and should be given priority in relevant planning or development plans.

[0219] According to the scoring results, the evaluation objects are divided into three levels: high potential, medium potential and low potential. The objects with the top 25% of the scores are classified into the high potential group, and it is recommended to give priority to development; the objects with the middle 50% of the scores are classified into the medium potential group, and it is recommended to encourage development; the objects with the bottom 25% of the scores are classified into the small potential group, and it is recommended to postpone development.

[0220] By applying it to the evaluation of hydrothermal geothermal resources in Qinghai Province, its effectiveness and reliability in practical application have been demonstrated. In the case of Qinghai Province, the hot springs and county geothermal resources throughout the province were evaluated, and development priorities with guiding significance were obtained, which can provide a scientific basis for the decision-making of governments and enterprises in geothermal resource development.

[0221] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without creative work should fall within the scope of protection of the present invention. The structures, devices and operating methods not specifically described and explained in the present invention are implemented according to the conventional means in the field unless otherwise specified and limited.

Claims

1. A method for evaluating hydrothermal geothermal resources for demand optimization, characterized in that: include: Determining the relative importance relationship between various evaluation indicators of the evaluation object through an expert scoring system; wherein the evaluation indicators include indicators for reflecting the resource demand side of the evaluation object and indicators for reflecting the resource supply side of the evaluation object; Based on the relative importance relationship, construct a judgment matrix for the evaluation object, and use the judgment matrix to determine the weight of each evaluation indicator; Collecting the original data corresponding to each evaluation index, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index, to obtain the standardized value corresponding to the original data; The weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object; According to the comprehensive score of the evaluation object, the evaluation object is divided into regions to obtain the evaluation result of the evaluation object.

2. A demand-optimized hydrothermal geothermal resource evaluation method according to claim 1, characterized in that: The evaluation objects include hot springs with point distribution determined based on the uplift mountain convection-type geothermal resources among the hydrothermal geothermal resources, or counties with surface distribution determined based on the sedimentary basin conduction-type geothermal resources among the hydrothermal geothermal resources. The single utilization direction corresponding to the uplift mountain convection-type geothermal resources is hot spring tourism, and the single utilization direction corresponding to the sedimentary basin conduction-type geothermal resources is geothermal heating.

3. A demand-optimized hydrothermal geothermal resource evaluation method according to claim 2, characterized in that: The evaluation index of the hot spring includes a primary evaluation index corresponding to the hot spring and a secondary evaluation index corresponding to the hot spring. The judgment matrix is ​​a multi-level judgment matrix. Based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the weight of each evaluation index is determined by using the judgment matrix, including: Based on the relative importance relationship between each first-level evaluation index of the hot spring, a first-level judgment matrix of the hot spring is constructed; based on the relative importance relationship between each second-level evaluation index of the hot spring, a second-level judgment matrix corresponding to each first-level evaluation index of the hot spring is constructed; the first-level judgment matrix of the hot spring and each second-level judgment matrix of the hot spring constitute a multi-level judgment matrix of the hot spring; Using the multi-level judgment matrix, determining the weights of the secondary evaluation indicators of the hot spring; Accordingly, the collecting of the original data corresponding to the respective evaluation indicators, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation indicator to obtain the standardized value corresponding to the original data, includes: Collecting the original data corresponding to each secondary evaluation index of the hot spring, and performing interval standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index, to obtain the standardized value corresponding to the original data; The weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object, including: The weights of the secondary evaluation indicators of the hot spring are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the hot spring.

4. The method for evaluating hydrothermal geothermal resources for demand optimization according to claim 2, characterized in that: The evaluation index of the county includes the primary evaluation index corresponding to the county and the secondary evaluation index corresponding to the county. The judgment matrix is ​​a multi-level judgment matrix. Based on the relative importance relationship, a judgment matrix is ​​constructed for the evaluation object, and the weight of each evaluation index is determined by using the judgment matrix, including: Based on the relative importance relationship between each first-level evaluation index of the county, a first-level judgment matrix of the county is constructed; based on the relative importance relationship between each second-level evaluation index of the county, a second-level judgment matrix corresponding to each first-level evaluation index of the county is constructed; the first-level judgment matrix of the county and each second-level judgment matrix of the county constitute a multi-level judgment matrix of the county; Using the multi-level judgment matrix, determine the weight of each secondary evaluation index of the county; Accordingly, the collecting of the original data corresponding to the respective evaluation indicators, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation indicator to obtain the standardized value corresponding to the original data, includes: Collecting the original data corresponding to each secondary evaluation index of the county, and performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index, to obtain the standardized value corresponding to the original data; The weights of the evaluation indicators are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the evaluation object, including: The weights of the secondary evaluation indicators of the county are multiplied and added with their corresponding standardized values ​​to obtain a comprehensive score of the county.

5. A demand-optimized hydrothermal geothermal resource evaluation method according to claim 3 or claim 4, characterized in that: The multi-level judgment matrix is ​​a matrix constructed for the evaluation object in a single utilization direction based on the hierarchical analysis method.

6. The method for evaluating hydrothermal geothermal resources for demand optimization according to claim 1, characterized in that: The evaluation index of the evaluation object includes a first evaluation index and a second evaluation index, and the relative importance relationship between the evaluation indexes of the evaluation object is determined by the expert scoring system, including: Selecting industry experts to score the relative importance relationship between the first evaluation indicator and the second evaluation indicator, thereby obtaining an expert scoring result corresponding to the relative importance relationship between the first evaluation indicator and the second evaluation indicator; A consistency check is performed on the expert scoring results, and the average value of the expert scoring results that pass the consistency check is used as a representation of the relative importance relationship between the first evaluation indicator and the second evaluation indicator; wherein the expert scoring system adopts a combination of qualitative and quantitative methods to determine the relative importance relationship between each evaluation indicator.

7. The method for evaluating hydrothermal geothermal resources for demand optimization according to claim 1, characterized in that: The step of performing interval-standardized value assignment on the original data based on the standardized value assignment interval corresponding to the preset evaluation index to obtain a standardized value corresponding to the original data includes: If the standardized value assignment intervals corresponding to the preset evaluation index are four intervals, the four intervals are used to perform interval standardized value assignment on the original data, and the standardized values ​​corresponding to the original data are obtained as 25 points, 50 points, 75 points, and 100 points respectively; If the standardized value assignment intervals corresponding to the preset evaluation index are five intervals, the five intervals are used to perform interval standardized value assignment on the original data, and the standardized values ​​corresponding to the original data are 20 points, 40 points, 60 points, 80 points, and 100 points respectively.

8. The method for evaluating hydrothermal geothermal resources for demand optimization according to claim 1, characterized in that: The weight distribution of each evaluation index and its corresponding standardized value are multiplied and added to obtain a comprehensive score of the evaluation object, including: The weight of each evaluation indicator is multiplied by its corresponding standardized data to obtain the score of each evaluation indicator, and the scores of each evaluation indicator are added together to obtain the comprehensive score of the evaluation object.

9. The method for evaluating hydrothermal geothermal resources for demand optimization according to claim 1, characterized in that: The step of dividing the evaluation object into zones according to the comprehensive score of the evaluation object and obtaining the evaluation result of the evaluation object includes: Based on the comprehensive score of the evaluation object, the evaluation object is divided into three zoning levels: high potential, medium potential and low potential; wherein, the zoning level is used to characterize the evaluation result of the evaluation object, the evaluation object with the comprehensive score in the top 25% is classified into the high potential level, the evaluation object with the comprehensive score in the middle 50% is classified into the medium potential level, and the evaluation object with the comprehensive score in the bottom 25% is classified into the low potential level, and the high potential level, the medium potential level and the low potential level correspond to three development and utilization time sequences of priority development, encouraged development and suspended development respectively.

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