CN114418252A - Comprehensive evaluation screening method for geothermal field - Google Patents
Comprehensive evaluation screening method for geothermal field Download PDFInfo
- Publication number
- CN114418252A CN114418252A CN202011175032.7A CN202011175032A CN114418252A CN 114418252 A CN114418252 A CN 114418252A CN 202011175032 A CN202011175032 A CN 202011175032A CN 114418252 A CN114418252 A CN 114418252A
- Authority
- CN
- China
- Prior art keywords
- region
- comprehensive
- subdivision
- weight
- indexes
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 89
- 238000012216 screening Methods 0.000 title claims abstract description 59
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000010606 normalization Methods 0.000 claims abstract description 32
- 238000012545 processing Methods 0.000 claims abstract description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 40
- 238000010438 heat treatment Methods 0.000 claims description 26
- 239000011159 matrix material Substances 0.000 claims description 26
- 230000015572 biosynthetic process Effects 0.000 claims description 15
- 230000005611 electricity Effects 0.000 claims description 13
- 230000033558 biomineral tissue development Effects 0.000 claims description 11
- 239000012530 fluid Substances 0.000 claims description 11
- 238000003973 irrigation Methods 0.000 claims description 11
- 239000013598 vector Substances 0.000 claims description 9
- 238000004458 analytical method Methods 0.000 claims description 8
- 230000002262 irrigation Effects 0.000 claims description 6
- 238000011160 research Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 238000000605 extraction Methods 0.000 claims 1
- 238000011161 development Methods 0.000 description 12
- 230000018109 developmental process Effects 0.000 description 12
- 230000000694 effects Effects 0.000 description 7
- 238000005065 mining Methods 0.000 description 7
- 238000004364 calculation method Methods 0.000 description 4
- 239000011435 rock Substances 0.000 description 4
- 238000009825 accumulation Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 2
- 238000005338 heat storage Methods 0.000 description 2
- 238000002347 injection Methods 0.000 description 2
- 239000007924 injection Substances 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 235000019738 Limestone Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000005553 drilling Methods 0.000 description 1
- 238000011234 economic evaluation Methods 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 239000006028 limestone Substances 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000004451 qualitative analysis Methods 0.000 description 1
- 238000004445 quantitative analysis Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a comprehensive evaluation screening method for a geothermal field, which comprises the following steps: obtaining a plurality of indexes influencing the evaluation of geothermal field resources, wherein the indexes comprise underground indexes, ground indexes and economic indexes, and the underground indexes, the ground indexes and the economic indexes all comprise a plurality of subdivision parameters; respectively carrying out normalization processing on a plurality of subdivision parameters of a plurality of regions to obtain a normalization coefficient of each subdivision parameter of each region; acquiring the comprehensive weight of each subdivision parameter of each region; obtaining a comprehensive evaluation coefficient of each area; and screening a plurality of geothermal fields of different types based on the comprehensive evaluation coefficient of each region. According to the method, comprehensive weight is calculated according to the class weight and the classification weight of the index to which each subdivision parameter belongs, the comprehensive evaluation coefficient of each region is obtained through the comprehensive weight and the normalization coefficient of the subdivision parameter, and the comprehensive evaluation coefficient of each region represents the explorable geothermal potential of each region.
Description
Technical Field
The invention belongs to the technical field of geothermal field exploration and development, and particularly relates to a comprehensive evaluation and screening method for a geothermal field.
Background
So far, no method is suitable for comprehensive evaluation of different types of geothermal fields and for comparative screening of a plurality of geothermal fields for domestic geothermal fields. The traditional geothermal field screening method mainly comprises two methods, one method is mainly single-property evaluation, the adopted parameters are often single-item, or are focused on basic geological characteristics, or are focused on heat accumulation projects, or are focused on drilling and mining projects, or are focused on heat accumulation management, or are focused on economic evaluation, and the evaluation is either contained in development scheme compilation, special planning or heat accumulation dynamic analysis, and the comprehensive evaluation on the development effect of the geothermal field is rarely considered comprehensively. And another method is that different experts of each geothermal field sequentially score according to their own experiences in work and production to evaluate and screen, so that the comprehensive capabilities such as the work experience, technical title, academic calendar, scientific and technical level of the experts are mainly relied on, and the comprehensive capabilities are objectively different and difficult to quantify, which may cause certain divergence to the screening of geothermal fields and even the evaluation of development effect.
The evaluation of the geothermal field heat resources has various methods, such as a surface heat flow method, which is a method for estimating the geothermal resources according to the heat emitted from the surface of the geothermal field, and is mainly used in regions with low geothermal resource exploration degree, but has great uncertainty; plane fracture method means that underground water flows along a flat fracture in rock with extremely poor permeability, and heat energy in the rock is transferred to the fracture surface by conduction and exchanges heat with flowing water, and then the heat energy is extracted. This method can only be used in geological conditions similar to iceland, because iceland has only basalt, the stratum has not been wrinkled, only the interface of lava has permeable layer. But the cracks in other places are complex to develop and are generally difficult to carry out according to the mode; the magma thermal balance method is mainly aimed at the evaluation of geothermal resources of hot dry rock, takes a young igneous rock mass as an object, and is suitable for areas with young magma invaded bodies; the heat storage method (volume method) is used for estimating the hot water quantity of the volume of the heat reservoir exploitation and further calculating the heat quantity, the geothermal energy and the general mineral resources are equivalent by the method, and the result has deviation due to the fact that the parameters have great uncertainty; mining dynamic method, centralized parameter model method generally require to accumulate many years of monitoring data, and are suitable for areas with high exploration degree and dynamic monitoring for many years. But there is a great difficulty in gathering the data.
In summary, the above methods have more or less subjective factors, so that indexes for evaluating the development effect of the geothermal field cannot effectively and truly guide the screening work of the geothermal field, and result deviation is caused, so that the method has great limitations.
Meanwhile, the development effect of the geothermal field is influenced and limited by a plurality of factors, a scientific method is needed to qualitatively and quantitatively evaluate certain attributes of a certain evaluation object or a plurality of evaluation objects from different angles, quantitative indexes can obtain accurate values through methods such as mathematical operation, field investigation and the like, and qualitative indexes are difficult to describe by an accurate number, so that the geothermal field has certain ambiguity, such as ground conditions and the like, and cannot be accurately evaluated.
Therefore, a method for scientifically, systematically and accurately evaluating development indexes of geothermal fields and screening the geothermal fields is particularly needed, so that the efficiency and quality of exploration and development are improved, and efficient and stable heat supply is further realized.
Disclosure of Invention
The invention aims to provide a method for scientifically, systematically and accurately screening geothermal fields.
The invention provides a comprehensive evaluation screening method for a geothermal field, which comprises the following steps: obtaining a plurality of indexes influencing the evaluation of geothermal field resources, wherein the indexes comprise underground indexes, ground indexes and economic indexes, and the underground indexes, the ground indexes and the economic indexes all comprise a plurality of subdivision parameters; respectively carrying out normalization processing on a plurality of subdivision parameters of a plurality of regions to obtain a normalization coefficient of each subdivision parameter of each region; acquiring the comprehensive weight of each subdivision parameter of each region; obtaining a comprehensive evaluation coefficient of each region based on the comprehensive weight and the normalized coefficient of each subdivision parameter of each region; and screening the geothermal fields of the plurality of regions based on the comprehensive evaluation coefficient of each region.
Optionally, the sub-division parameters included in the subsurface index are: well depth, water temperature, water quantity, production-irrigation ratio, formation pressure, fluid mineralization degree and risk additional factors; the ground indexes comprise subdivision parameters of heating days and outdoor temperature; the economic indexes comprise subdivision parameters of heating price, supporting facility fee, water resource tax, subsidy policy, resident electricity price and comprehensive charge rate; and respectively sequencing a plurality of parameters of subdivision parameters contained in the underground index, the ground index and the economic index.
Optionally, the following formula is adopted to obtain the normalized coefficients of water temperature, water quantity, irrigation and mining ratio, heating price, subsidy policy, comprehensive charge rate, outdoor temperature and heating days:
the normalized coefficients of well depth, fluid mineralization, supporting facility fee, water resource tax and resident electricity price are obtained by the following formulas:
optionally, the normalized coefficient of the formation pressure is obtained by using the following formula:
wherein r is a normalization coefficient, xijThe data of the i subdivision parameter of the j region, n is the number of the comprehensive evaluation and screening geothermal fields, ajIs the formation pressure reference.
Optionally, the obtaining the comprehensive weight of each subdivision parameter of each region includes: obtaining the class weight of each index; obtaining the classification weight of each subdivision parameter of each region; and obtaining the comprehensive weight of each subdivision parameter of each region based on the class weight and the classification weight.
Optionally, the integrated weight of each subdivision parameter of each region is a product of a class weight of an index to which the subdivision parameter belongs and a classification weight of the subdivision parameter.
Optionally, the obtaining the class weight of each index includes: establishing a first-level index quantity comparison judgment matrix according to three indexes by combining a Suddy relative importance index table according to an analysis result of expert research on each region; and taking the characteristic vector of the first-level index quantity comparison judgment matrix as the class weight of the index.
Optionally, the obtaining the classification weight of each subdivision parameter of each region includes: and combining the Suddy relative importance scale table with the actual data of each subdivision parameter of each region to obtain the classification weight of each subdivision parameter of each region.
Optionally, the obtaining the comprehensive evaluation coefficient of each region based on the comprehensive weight and the normalization coefficient of each subdivision parameter of each region includes: calculating the product of the comprehensive weight of each subdivision parameter of each region and the normalization coefficient to obtain the final comprehensive index of each subdivision parameter of each region; and adding the final comprehensive indexes of all the subdivision parameters of each region to obtain a comprehensive evaluation coefficient of each region.
The invention has the beneficial effects that: the comprehensive evaluation screening method of the geothermal field calculates the comprehensive weight according to the class weight of the index to which each subdivision parameter belongs and the classification weight of the subdivision parameter, obtains the final comprehensive index of each subdivision parameter through the comprehensive weight and the normalization coefficient of the subdivision parameter, further obtains the comprehensive evaluation coefficient of each region, the comprehensive evaluation coefficient of each region represents the size of the potential of the region capable of carrying out geothermal exploration, evaluates and screens different types of geothermal fields according to the comprehensive evaluation coefficient and the development characteristics of the geothermal fields of the region, and points out the direction for large-scale application of the geothermal fields.
The present invention has other features and advantages which will be apparent from or are set forth in detail in the accompanying drawings and the following detailed description, which are incorporated herein, and which together serve to explain certain principles of the invention.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent by describing in more detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
Fig. 1 shows a flow chart of a comprehensive evaluation screening method for geothermal fields according to an embodiment of the present invention.
Fig. 2 is a diagram illustrating the results of a comprehensive evaluation screening method for geothermal fields according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will be described in more detail below. While the following describes preferred embodiments of the present invention, it should be understood that the present invention may be embodied in various forms and should not be limited by the embodiments set forth herein.
The invention provides a comprehensive evaluation screening method for a geothermal field, which comprises the following steps: obtaining a plurality of indexes influencing the evaluation of geothermal field resources, wherein the indexes comprise underground indexes, ground indexes and economic indexes, and the underground indexes, the ground indexes and the economic indexes all comprise a plurality of subdivision parameters; respectively carrying out normalization processing on a plurality of subdivision parameters of a plurality of regions to obtain a normalization coefficient of each subdivision parameter of each region; acquiring the comprehensive weight of each subdivision parameter of each region; obtaining a comprehensive evaluation coefficient of each region based on the comprehensive weight and the normalized coefficient of each subdivision parameter of each region; and screening the geothermal fields of the plurality of regions based on the comprehensive evaluation coefficient of each region.
Specifically, screening indexes and subdivision parameters contained in the indexes according to the relation of the characteristics of the geothermal field and the influence factors thereof; calculating the class weight of the indexes and the classification weight of each subdivision parameter contained in each area index, evaluating developed limestone geothermal fields and sandstone geothermal fields according to different types of geothermal fields, calculating the comprehensive evaluation coefficient of the area where the geothermal field is located according to the comprehensive weight occupied by each area subdivision parameter and the normalization coefficient of the subdivision parameter, sequencing the target geothermal fields according to the comprehensive evaluation coefficient, and highly representing the potential of geothermal exploration of the geothermal field.
According to an exemplary embodiment, the comprehensive evaluation screening method of the geothermal field calculates comprehensive weight according to the class weight of the index to which each subdivision parameter belongs and the classification weight of the subdivision parameter, obtains the final comprehensive index of each subdivision parameter through the comprehensive weight and the normalization coefficient of the subdivision parameter, further obtains the comprehensive evaluation coefficient of each region, the comprehensive evaluation coefficient of each region represents the size of the potential of the geothermal field for geothermal exploration, evaluates and screens different types of geothermal fields according to the evaluation value and the development characteristics of the geothermal fields of the region, and indicates the direction for large-scale application of the geothermal field.
In one example, evaluation results are analyzed according to evaluation values of subdivision parameters of the geothermal field and actual production dynamics, particularly, reasons of some indexes with unsatisfactory evaluation results are analyzed, and then targeted adjustment measures are proposed to improve development effects.
Alternatively, the subsurface index contains the following subdivision parameters: well depth, water temperature, water quantity, production-irrigation ratio, formation pressure, fluid mineralization degree and risk additional factors; the ground index comprises subdivision parameters of heating days and outdoor temperature; the economic indexes comprise subdivision parameters of heating price, supporting facility fee, water resource tax, subsidy policy, resident electricity price and comprehensive charge rate.
Specifically, various factors influencing the evaluation of the thermal resources of the geothermal field are analyzed, and the factors comprise: (1) the underground indicators include: well depth, water temperature, water quantity, production-irrigation ratio, formation pressure, fluid mineralization degree and risk additional factors; (2) the ground indexes include: days of heating, outdoor temperature; (3) the economic indicators include: heating fee standard, matching fee standard, water resource tax, subsidy policy, electricity price and comprehensive charge rate. And sequencing the target geothermal fields according to the three major indexes and the 15 subdivision parameters, thereby finding out the geothermal fields with better exploration potential.
The underground indexes reflect the actual geological conditions of a certain area and a geothermal well, the ground indexes mainly reflect the local heating time, the economic indexes mainly reflect the conditions of local policy subsidies and the like, and the indexes are closely related to comprehensive evaluation and screening of the geothermal field.
As an alternative, the following formula is adopted to obtain the normalized coefficients of the water temperature, the water quantity, the irrigation and mining ratio, the heating price, the subsidy policy, the comprehensive charge rate, the outdoor temperature and the heating days:
the normalized coefficients of well depth, fluid mineralization, supporting facility fee, water resource tax and resident electricity price are obtained by the following formulas:
alternatively, the normalized coefficient of formation pressure is obtained using the following equation:
wherein r is a normalization coefficient, xijCorresponding to a specific parameter of a certain area, n is the number of the comprehensive evaluation and screening of the geothermal fields, ajIs the formation pressure reference.
Specifically, the preferred screening indexes are normalized in three evaluation modes, i.e., the smaller the evaluation value, the better the evaluation value, and the closer the evaluation value to the standard value, the better.
For parameters such as formation pressure, the calculation is carried out by using a formula (1) according to different geothermal fields, and the closer the evaluation value is to a standard value, the better the evaluation value is;
for parameters such as water temperature, water quantity, mining and irrigation ratio, heating price, subsidy policy, comprehensive charge rate, outdoor temperature, heating days and the like, the calculation is carried out by using a formula (2), and the larger the evaluation value is, the better the evaluation value is;
for parameters such as well depth, fluid mineralization, supporting facility fee, water resource tax, resident electricity price and the like, the calculation is carried out by using the formula (3), and the smaller the evaluation value is, the better the evaluation value is.
The 15 types of subdivision parameters are evaluated for different geothermal fields.
The risk-adding factor is typically 1.
As an alternative, obtaining the comprehensive weight of each subdivision parameter of each region includes: obtaining the class weight of each index; obtaining the classification weight of each subdivision parameter of each region; and obtaining the comprehensive weight of each subdivision parameter of each region based on the class weight and the classification weight.
Firstly, the class weight of each index and the class weight of each subdivision parameter of each region are obtained, and then the product of the class weight of the subdivision parameter and the class weight of the index to which the subdivision parameter belongs is obtained to obtain the comprehensive weight of the subdivision parameter.
Alternatively, the integrated weight of each subdivision parameter of each region is the product of the class weight of the index to which the subdivision parameter belongs and the classification weight of the subdivision parameter.
Specifically, the comprehensive weight of each subdivision parameter is the product of the class weight of the index to which the subdivision parameter belongs and the classification weight of the subdivision parameter, and the indexes include underground indexes, ground indexes and economic indexes.
Alternatively, obtaining the class weight of each index includes: establishing a first-level index quantity comparison judgment matrix according to three indexes by combining a Suddy relative importance index table according to an analysis result of expert research on each region; and taking the characteristic vector of the first-level index quantity comparison judgment matrix as the class weight of the index.
Specifically, combining the research and analysis results of experts, comparing indexes of all levels in respective levels according to an analytic hierarchy process and a Suddy relative importance level table, as shown in table 1, according to scales specified in the table, giving importance levels, writing the importance levels into a matrix form, and forming a judgment matrix of different types of geothermal field screening indexes through full discussion.
TABLE 1 Suddy relative importance rating Table
| Scale | Means of |
| 1 | Of equal importance when compared to two elements |
| 3 | The former being slightly more important than the latter in comparison with the two elements |
| 5 | The former is significantly more important than the latter when compared with the two elements |
| 7 | The former is more important than the latter in comparison with two elements |
| 9 | The former is extremely important than the latter in comparison with two elements |
| 2，4，6，8 | Intermediate value representing the above-mentioned adjacent judgment |
| Reciprocal of the | The latter being more important than the former |
Comparing and judging matrix for three first-level index quantities
Applying the feature vector method proposed by Saaty: AW ═ λmaxAnd W, calculating the characteristic root and the characteristic vector of the matrix. The largest feature root can be found as: lambda [ alpha ]max3; since the corresponding eigenvector of the determination matrix a is W (0.45450.09090.4545), the eigenvector of the determination matrix a corresponds to the three class weights of the corresponding region, that is, the underground index, the ground index, and the economic index correspond to the above numerical values, respectively.
Obtaining a fuzzy relation matrix according to the membership function as follows:
the fuzzy screening value of the level is as follows:
the fuzzy screening set on the level forms a fuzzy screening subset of the previous level, and the fuzzy screening subset is upwards step by step according to the same method, so that a first-level comprehensive fuzzy screening set is finally obtained.
And after the primary comprehensive fuzzy screening is finished, performing total screening. The weight set of the primary index is W ═ (0.454545,0.090909, 0.454545). The fuzzy relation matrix of the small first-order factor is that R is equal to (B)1,B2,B3,B4,B5) The total fuzzy comprehensive screening set:
B＝W×R＝(ω1，ω2，ω3)×(B1，B2，B3，B4)T＝(b1，b2，b3，b4，b5)
the principle of maximum membership is the currently general discriminant principle. For example, the obtained comprehensive screening set is B ═ (0.4, 0.5, 0.7, 0.4, 0.3), and the maximum membership rule is applied, that is, the screening object is classified into the grade corresponding to max ═ 0.7. Of course, in the case of fuzzy comprehensive screening, the principle of maximum membership is not well suited to the four seas. For example, assuming that we obtain the following screening result B ═ (0.2, 0.7, 0.69, 0.2, 0.1), it is clear that the screened object is between the first and second levels by visual analysis, and the screened object is classified into one level according to the principle of maximum membership, which is obviously not good. Therefore, in the screening, the quantitative analysis and the qualitative analysis are combined according to the actual situation, and the confidence interval of the obtained result is considered to ensure the reliability of the screening.
Alternatively, obtaining the classification weight of each subdivision parameter for each region comprises: and combining the Suddy relative importance scale table with the actual data of each subdivision parameter of each region to obtain the classification weight of each subdivision parameter of each region.
Specifically, a plurality of data of all subdivision parameters of each region are obtained in a database, actual data are obtained according to the characteristics of each subdivision parameter, for example, the heating standard is fixed data, the water temperature and the water quantity are average values of the existing data of the region, and the actual data of each parameter of each region are combined with a Sudi relative importance scale table to determine the classification weight of each subdivision parameter of each region. The relative importance in combination with sadi scale is shown in the table below.
Suddy relative importance rating table
| Scale | Means of |
| 1 | Of equal importance when compared to two elements |
| 3 | The former being slightly more important than the latter in comparison with the two elements |
| 5 | The former is significantly more important than the latter when compared with the two elements |
| 7 | The former is more important than the latter in comparison with two elements |
| 9 | The former is extremely important than the latter in comparison with two elements |
| 2，4，6，8 | Intermediate value representing the above-mentioned adjacent judgment |
| Reciprocal of the | The latter being more important than the former |
Alternatively, obtaining the comprehensive evaluation coefficient of each region based on the comprehensive weight and the normalization coefficient of each subdivision parameter of each region comprises: calculating the product of the comprehensive weight of each subdivision parameter of each region and the normalization coefficient to obtain the final comprehensive index of each subdivision parameter of each region; and adding the final comprehensive indexes of all the subdivision parameters of each region to obtain a comprehensive evaluation coefficient of each region.
Specifically, the comprehensive weight value of each subdivision parameter of each area is multiplied by the normalization coefficient of the subdivision parameter to obtain the final comprehensive index of the subdivision parameter, then the final comprehensive indexes of each parameter of the area are added to obtain the comprehensive evaluation coefficient of the area, and the comprehensive evaluation coefficient represents the size of the potential of geothermal exploration, so that a basis is provided for the exploitation of the geothermal field.
Example one
Fig. 1 shows a flow chart of a comprehensive evaluation screening method for geothermal fields according to an embodiment of the present invention. Fig. 2 is a diagram illustrating the results of a comprehensive evaluation screening method for geothermal fields according to an embodiment of the present invention.
Referring to fig. 1 and 2, the comprehensive evaluation screening method for the geothermal field comprises the following steps:
step 1: obtaining a plurality of indexes influencing the evaluation of geothermal field resources, wherein the indexes comprise underground indexes, ground indexes and economic indexes, and the underground indexes, the ground indexes and the economic indexes all comprise a plurality of subdivision parameters;
wherein, the subdivision parameters are as follows: well depth, water temperature, water quantity, production-irrigation ratio, formation pressure, fluid mineralization degree and risk additional factors; the ground index contains subdivision parameters: days of heating, outdoor temperature; the economic index comprises the following subdivision parameters: heating price, supporting facility fee, water resource tax, subsidy policy, resident electricity price and comprehensive charge rate; and sorting the subdivision parameters contained in the underground index, the ground index and the economic index respectively.
Step 2: respectively carrying out normalization processing on a plurality of subdivision parameters of a plurality of regions to obtain a normalization coefficient of each subdivision parameter of each region;
wherein, the following formulas are adopted to obtain the normalized coefficients of water temperature, water quantity, irrigation and mining ratio, heating price, subsidy policy, comprehensive charge rate, outdoor temperature and heating days:
the normalized coefficients of well depth, fluid mineralization, supporting facility fee, water resource tax and resident electricity price are obtained by the following formulas:
wherein, the normalized coefficient of the parameter of the formation pressure is obtained by adopting the following formula:
wherein r is a normalization coefficient, xijCorresponding to a specific parameter of a certain area, n is the number of the comprehensive evaluation and screening of the geothermal fields, ajIs the formation pressure reference.
And step 3: acquiring the comprehensive weight of each subdivision parameter of each region;
the method for obtaining the comprehensive weight of each subdivision parameter of each region comprises the following steps: obtaining the class weight of each index; obtaining the classification weight of each subdivision parameter of each region; and obtaining the comprehensive weight of each subdivision parameter of each region based on the class weight and the classification weight.
The comprehensive weight of each subdivision parameter of each region is the product of the class weight of the index to which the subdivision parameter belongs and the classification weight of the subdivision parameter.
Wherein obtaining the class weight of each index comprises: establishing a first-level index quantity comparison judgment matrix according to three indexes by combining a Suddy relative importance index table according to an analysis result of expert research on each region; and taking the characteristic vector of the first-level index quantity comparison judgment matrix as the class weight of the index.
Wherein, obtaining the classification weight of each subdivision parameter of each region comprises: and combining the Suddy relative importance scale table with the actual data of each subdivision parameter of each region to obtain the classification weight of each subdivision parameter of each region.
And 4, step 4: obtaining a comprehensive evaluation coefficient of each region based on the comprehensive weight and the normalization coefficient of each subdivision parameter of each region;
wherein, based on the comprehensive weight and the normalization coefficient of each subdivision parameter of each region, obtaining the comprehensive evaluation coefficient of each region comprises: calculating the product of the comprehensive weight of each subdivision parameter of each region and the normalization coefficient to obtain the final comprehensive index of each subdivision parameter of each region; and adding the final comprehensive indexes of all the subdivision parameters of each region to obtain a comprehensive evaluation coefficient of each region.
And 5: and screening the geothermal fields of the plurality of regions based on the comprehensive evaluation coefficient of each region.
Specifically, only part of sandstone geothermal fields are selected in the national regions for comparison and screening:
first, various factors affecting the development effect of the geothermal field are analyzed, and the quality of the geothermal field can be comprehensively reflected, and the geothermal field is screened according to the indexes.
On the basis of earlier-stage research and domestic and overseas investigation, the potential of factors such as underground resources, ground conditions, economic factors and the like of the geothermal field is comprehensively considered, and a screening system of 3 types and 15 subdivision indexes is established, and is specifically shown in table 2.
TABLE 2 screening index system for different types of geothermal fields
We have chosen 6 sandstone geothermal fields as examples, which are eastern urban district, long wall county, famous, qing river, hometown and yinchuan city, respectively, and the specific parameters are shown in table 3:
TABLE 3 multiple sandstone geothermal field screening index system
For the 6 regions, the values of the parameters in the underground conditions are obtained according to the actual conditions of the local geothermal wells or by referring to the basic geological conditions of the regions; the outdoor temperature in the ground condition is the average temperature in winter throughout the year, and the number of heating days is the actual number of local heating days; the values of all indexes in the economic factors are obtained according to documents made by local governments.
Next, each subdivision index of 6 regions is normalized;
taking the east-camp urban area as an example, the formula is used for parameters such as water temperature, water quantity, ratio of mining and irrigation, heating price, subsidy policy, comprehensive charge rate, outdoor temperature, heating days and the like
Obtaining a calculation result, wherein xijTaking the value of some factor in the area, max (x)i1…xij) The maximum value of the above certain factors, r, in the six regionsijAnd normalizing the processed coefficient for the certain factor, namely normalizing the coefficient.
For parameters such as well depth, fluid mineralization, supporting facility fee, water resource tax, resident electricity price and the like, a formula is used
Wherein x isijThe value of the above certain factor in the area is min (x)i1…xij) Is the minimum value of the above certain factors in the six regions, rijAnd normalizing the processed coefficient for the certain factor, namely normalizing the coefficient.
For parameters such as formation pressure, using formulas
And obtaining the normalized coefficient.
Typically, the risk-adding factor is typically 1.
And calculating the normalization coefficient of each parameter index of each region according to the formula to obtain the normalization coefficient of each parameter of each region.
Then, the weight of the primary index, i.e., the class weight of the index, is determined. The relative importance degree of the first-level indexes is mainly obtained by researching experts, the analysis result is combined with a Suddy relative importance scale table to form a comparison matrix (table 4), a first-level index quantity comparison and judgment matrix of each region is established, the first-level indexes are divided into three types, including underground indexes, ground indexes and economic factors, and data recorded in the table 4 are vectors of the first-level index quantity comparison and judgment matrix.
TABLE 4 different types of heat storage primary index judgment matrix
| Underground conditions | Ground conditions | Economic factor | |
| |
1 | 5 | 1 |
| Ground conditions | 0.2 | 1 | 0.2 |
| |
1 | 0.2 | 1 |
Comparing and judging matrix for three first-level index quantities
Applying the feature vector method proposed by Saaty: AW ═ λmaxAnd W, calculating the characteristic root and the characteristic vector of the matrix. The largest feature root can be found as: lambda [ alpha ]max3; since the corresponding eigenvector of the determination matrix a is W ═ 0.45450.09090.4545, the eigenvector of the determination matrix a corresponds to the three class weights of the corresponding region, that is, the class weights of the underground index, the ground index, and the economic index correspond to the above-mentioned numerical values, respectively.
According to the formula
Performing consistency check on the judgment matrix, specifically, λmaxN is the number of factors for the feature root. A CI value of 0 can be obtained, indicating complete consistency, indicating that the decision matrix is reasonable.
Determining the weight of each index by using an analytic hierarchy process and carrying out consistency check.
And combining the Suddy relative importance scale table with the actual data of each subdivision parameter of each region to obtain the classification weight of each subdivision parameter of each region, and as shown in tables 6 and 7, obtaining the classification weight judgment basis of classification injection condition weight of the subdivision parameters.
TABLE 6 weight discrimination table for secondary index injection status of economic factors of different types of geothermal fields
| Standard of warm charge | Standard of matching fee | Water resource tax | Subsidy policy | Price of electricity | Comprehensive charge rate | |
| Standard of |
1 | 2 | 4 | 2 | 4 | 0.5 |
| Standard of matching fee | 0.5 | 1 | 2 | 1 | 2 | 0.25 |
| Water resource tax | 0.25 | 0.5 | 1 | 0.5 | 1 | 0.125 |
| Subsidy policy | 0.5 | 1 | 2 | 1 | 2 | 0.25 |
| Price of electricity | 0.25 | 0.5 | 1 | 0.5 | 1 | 0.125 |
| Comprehensive charge rate | 2 | 4 | 8 | 4 | 8 | 1 |
TABLE 7 discrimination table for underground factor weight of secondary indexes of different geothermal fields
The class weight of the index to which the subdivision parameter belongs is multiplied by the classification weight of the subdivision parameter to obtain the comprehensive weight of each subdivision parameter, and the comprehensive weight is shown as a weight summary table of each subdivision parameter in table 8.
TABLE 8 summary table of screening effect index weights of different types of geothermal fields
And finally, multiplying the comprehensive weight value of the subdivision parameters of each area by the normalization coefficient to obtain a final comprehensive index of each parameter, adding the final comprehensive indexes of each parameter to obtain a comprehensive evaluation coefficient of each area, wherein the comprehensive evaluation coefficient represents the exploitable potential of the geothermal field in each area and provides a basis for exploitation of the geothermal field.
As shown in fig. 2, the evaluation values of the 6 regions are recorded, and it is known from the figure that the comprehensive evaluation coefficient of the east-run city region is the highest, that is, the explorable geothermal potential of the east-run region is the best, and the comprehensive evaluation coefficient of the yinchuan city is the lowest, that is, the explorable geothermal potential of the yinchuan city is the worst.
Having described embodiments of the present invention, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.
Claims (8)
1. A comprehensive evaluation screening method for a geothermal field is characterized by comprising the following steps:
obtaining a plurality of indexes influencing the evaluation of geothermal field resources, wherein the indexes comprise underground indexes, ground indexes and economic indexes, and the underground indexes, the ground indexes and the economic indexes all comprise a plurality of subdivision parameters;
respectively carrying out normalization processing on a plurality of subdivision parameters of a plurality of regions to obtain a normalization coefficient of each subdivision parameter of each region;
acquiring the comprehensive weight of each subdivision parameter of each region;
obtaining a comprehensive evaluation coefficient of each region based on the comprehensive weight and the normalization coefficient of each subdivision parameter of each region;
and screening the geothermal fields of the plurality of regions based on the comprehensive evaluation coefficient of each region.
2. The comprehensive evaluation screening method for geothermal fields according to claim 1, wherein the underground index comprises the following subdivision parameters: well depth, water temperature, water quantity, production-irrigation ratio, formation pressure, fluid mineralization degree and risk additional factors; the ground index comprises subdivision parameters as follows: days of heating, outdoor temperature; the economic index comprises the following subdivision parameters: heating price, supporting facility fee, water resource tax, subsidy policy, resident electricity price and comprehensive charge rate;
and respectively sequencing a plurality of subdivision parameters contained in the underground index, the ground index and the economic index.
3. The comprehensive evaluation screening method for geothermal fields according to claim 2, wherein the normalized coefficients of water temperature, water quantity, irrigation and extraction ratio, heating price, subsidy policy, comprehensive charge rate, outdoor temperature and heating days are obtained by the following formulas:
the normalized coefficients of well depth, fluid mineralization, supporting facility fee, water resource tax and resident electricity price are obtained by the following formulas:
the normalized coefficient of formation pressure is obtained using the following formula:
wherein r is a normalization coefficient, xijThe data of the i subdivision parameter of the j region, n is the number of the comprehensive evaluation and screening geothermal fields, ajIs the formation pressure reference.
4. The comprehensive evaluation screening method for geothermal fields according to claim 3, wherein the obtaining of the comprehensive weight of each subdivision parameter of each region comprises:
obtaining the class weight of each index;
obtaining the classification weight of each subdivision parameter of each region;
and obtaining the comprehensive weight of each subdivision parameter of each region based on the class weight and the classification weight.
5. The comprehensive evaluation screening method for geothermal fields according to claim 4, wherein the comprehensive weight of each subdivision parameter of each region is a product of a class weight of an index to which the subdivision parameter belongs and a classification weight of the subdivision parameter.
6. The comprehensive evaluation screening method for geothermal fields according to claim 4, wherein the obtaining of the class weight of each index comprises:
establishing a first-level index quantity comparison judgment matrix according to three indexes by combining a Suddy relative importance index table according to an analysis result of expert research on each region; and taking the characteristic vector of the first-level index quantity comparison judgment matrix as the class weight of the index.
7. The comprehensive evaluation screening method for geothermal fields according to claim 4, wherein the obtaining of the classification weight of each subdivision parameter of each region comprises:
and combining the Suddy relative importance scale table with the actual data of each subdivision parameter of each region to obtain the classification weight of each subdivision parameter of each region.
8. The comprehensive evaluation screening method for geothermal fields according to claim 5, wherein the obtaining of the comprehensive evaluation coefficient for each region based on the comprehensive weight and the normalization coefficient for each subdivision parameter of each region comprises:
calculating the product of the comprehensive weight of each subdivision parameter of each region and the normalization coefficient to obtain the final comprehensive index of each subdivision parameter of each region;
and adding the final comprehensive indexes of all the subdivision parameters of each region to obtain a comprehensive evaluation coefficient of each region.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011175032.7A CN114418252A (en) | 2020-10-28 | 2020-10-28 | Comprehensive evaluation screening method for geothermal field |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011175032.7A CN114418252A (en) | 2020-10-28 | 2020-10-28 | Comprehensive evaluation screening method for geothermal field |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114418252A true CN114418252A (en) | 2022-04-29 |
Family
ID=81260633
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011175032.7A Pending CN114418252A (en) | 2020-10-28 | 2020-10-28 | Comprehensive evaluation screening method for geothermal field |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114418252A (en) |
-
2020
- 2020-10-28 CN CN202011175032.7A patent/CN114418252A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109102180B (en) | Comprehensive parameter evaluation method for double-dessert evaluation of tight sandstone reservoir | |
| Coppola Jr et al. | A neural network model for predicting aquifer water level elevations | |
| CN107463730B (en) | A kind of streamflow change attribution recognition methods considering Spatio-temporal Evolution of Land Use | |
| CN109214026A (en) | Shale gas horizontal well initial-stage productivity prediction method | |
| CN104636612A (en) | Karst tunnel water outburst and mud outburst overall process gradual dynamic risk assessment method | |
| CN105868508A (en) | Productivity quantitative prediction method based on gas logging information | |
| CN112308269A (en) | Yield prediction method and device for low-permeability oil and gas reservoir | |
| CN114971301A (en) | Ecological interference risk identification and evaluation method based on automatic parameter adjustment optimization model | |
| CN111476472A (en) | Sulfur-iron mine geological environment evaluation method | |
| CN105787642A (en) | Potential commercial district optimal selection method in oil gas exploration | |
| Zarrouk et al. | A review of geothermal resource estimation methodology | |
| CN111861277A (en) | Oil and gas resource economy evaluation method | |
| CN114357678A (en) | Novel optimization design method for regional underground water level monitoring network | |
| CN116384618A (en) | Method and system for profile control and flooding well selection of large well spacing oil reservoir | |
| CN114418252A (en) | Comprehensive evaluation screening method for geothermal field | |
| CN109583672B (en) | Risk exploration decision method and system | |
| Pauling et al. | Geothermal Play Fairway Analysis Best Practices | |
| CN111485868B (en) | Development scheme-based reserve estimation method for coal bed gas field | |
| Bezelgues-Courtade et al. | Geothermal potential of shallow aquifers: decision-aid tool for heat-pump installation | |
| Galgaro et al. | New tools to support the designing of efficient and reliable ground source heat exchangers: the Cheap-GSHPs databases and maps | |
| CN111080167A (en) | Underground space resource quality assessment method for urban planning | |
| CN106326620A (en) | Optimized selection method for diagenetic coefficient model of exploration target distribution range | |
| Roshni et al. | Clustering of groundwater wells and spatial variation of groundwater recharge in Sina basin, India | |
| CN115619788B (en) | Automatic quantitative evaluation method for quality of three-dimensional geological model | |
| CN117541082B (en) | Comprehensive evaluation method based on oil reservoir-shaft-equipment evaluation index integration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |