A method and system for site selection of carbon dioxide geological storage in deep mining space

Abstract

The application discloses a deep mining space carbon dioxide geological storage site selection method and system, belongs to the technical field of carbon dioxide geological storage, and solves the problem of lack of effective storage suitability evaluation indexes in the prior art. The method comprises the following steps: obtaining basin scale evaluation data of a plurality of candidate coal basins; performing standardization processing to obtain basin scale standardized evaluation indexes; constructing an index evaluation set based on a Pythagorean fuzzy set, and introducing triangular fuzzy numbers to optimize membership and non-membership, so as to obtain comprehensive membership and comprehensive non-membership; calculating the index score of each candidate coal basin, and constructing a basin scale decision matrix based on the index score; sorting by using CRITIC and VIKOR multi-attribute evaluation methods to determine a target coal basin; and determining a carbon dioxide geological storage area in the target coal basin. The application can improve the objectivity and stability of the carbon dioxide geological storage site selection result.

Description

Technical Field

[0001] This invention belongs to the field of carbon dioxide geological storage technology, and specifically relates to a method and system for selecting sites for carbon dioxide geological storage in deep mining spaces. Background Technology

[0002] Carbon dioxide geological sequestration technology is the most direct and effective means of permanent carbon dioxide sequestration and emission reduction. Based on the type of geological sequestration body, the main sequestration strata currently include: abandoned oil and gas reservoirs, deep saline water layers, unminable coal seams, and the ocean.

[0003] As coal mines reach the end of their service life and the "dual carbon" targets are implemented, the number of abandoned / closed coal mines in my country continues to increase. As the carrier of large-scale underground development activities, coal mines provide unique storage spaces for carbon dioxide geological sequestration in the goaf and mining-induced fractures in the roof and floor (i.e., deep mining spaces) generated during coal production.

[0004] Deep mining spaces, with their advantages of large scale and low filling pressure, are ideal locations for carbon sequestration. Fully utilizing the mining spaces in closed / abandoned deep mines to achieve secondary returns on resources and assets plays a vital role in sustainable energy development and ecological environmental protection.

[0005] Site selection evaluation for carbon dioxide geological storage is a core step in ensuring the safety, long-term stability, and engineering feasibility of carbon storage. It requires the construction of a scientific evaluation system from multiple scales and dimensions, taking into account factors such as geological characteristics, storage potential, and environmental risks.

[0006] Currently, the geological sequestration of carbon dioxide in deep mining spaces is still in the exploratory stage, and there is a lack of effective evaluation indicators for sequestration suitability. Summary of the Invention

[0007] Based on the above analysis, the embodiments of the present invention aim to provide a method and system for site selection of carbon dioxide geological storage in deep mining spaces, in order to solve the problem of the lack of effective evaluation indicators for storage suitability in the prior art.

[0008] The objective of this invention is achieved as follows: On the one hand, a method for site selection of carbon dioxide geological storage in deep mining spaces is provided, including: Obtain basin-scale evaluation data for multiple candidate coal basins and construct a set of basin-scale evaluation indicators. Perform standardization processing to obtain the basin-scale standardized evaluation index for each basin-scale evaluation index in the basin-scale evaluation index set. Based on the Pythagorean fuzzy set, an evaluation set of indicators is constructed, and the membership degree and non-membership degree are optimized by introducing triangular fuzzy numbers to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation indicator. Based on the basin-scale standardized evaluation index, the comprehensive membership degree, and the comprehensive non-membership degree, calculate the index score of each candidate coal basin under each basin-scale standardized evaluation index, and construct a basin-scale decision matrix based on the index score. The CRITIC method is used to calculate the weight of each basin-scale standardized evaluation index based on multiple candidate coal basins. Based on the weight and the basin-scale decision matrix, the VIKOR multi-attribute evaluation method is used to rank the multiple candidate coal basins, and the candidate coal basin with the best ranking is determined as the target coal basin. Within the target coal basin, mine-scale evaluation data of multiple candidate coal mining areas are acquired, and a set of mine-scale evaluation indicators is constructed. Each mining area scale evaluation index in the mining area scale evaluation index set is standardized, and multiple candidate coal mining areas are ranked based on Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method to determine the carbon dioxide geological sequestration zone.

[0009] Optionally, the construction of the basin-scale evaluation index set includes: Obtain first-class evaluation data to characterize the engineering geological stability of the candidate coal basin; Obtain a second type of evaluation data to characterize the storage potential of the candidate coal basins; Obtain third-type evaluation data to characterize the economic viability of the candidate coal basins for sequestration; Based on the first type of evaluation data, the second type of evaluation data, and the third type of evaluation data, the basin-scale evaluation index set is constructed.

[0010] Optionally, the first type of evaluation data includes: structural complexity index, seismic activity index, and geothermal flow field index; wherein the structural complexity index is determined based on the active fault density, maximum fault scale, and average Curie depth within the candidate coal basin; the seismic activity index is determined based on the seismic intensity, earthquake magnitude, and upper limit of magnitude of the candidate coal basin; and the geothermal flow field index is determined based on the geothermal flow value and average geothermal gradient of the candidate coal basin. The second type of evaluation data includes the sealed volume index and the caprock sealing index; wherein, the sealed volume index is determined based on the number of closed coal mines in the candidate coal basin and the average water inflow of the mines, and the caprock sealing index is determined based on the effective thickness of the caprock, the caprock porosity and the caprock permeability of the candidate coal basin. The third type of evaluation data includes coal basin economic indicators, which are determined based on the carbon source size and distance of the candidate coal basin.

[0011] Optionally, the step of constructing an index evaluation set based on Pythagorean fuzzy sets and introducing triangular fuzzy numbers to optimize membership and non-membership degrees to obtain the comprehensive membership and comprehensive non-membership degrees of each basin-scale standardized evaluation index includes: Obtain the membership degree evaluation results and non-membership degree evaluation results of multiple experts for each of the basin-scale standardized evaluation indicators; Based on the membership evaluation results and non-membership evaluation results, construct a Pythagorean fuzzy set; Based on the differences in evaluation of different evaluation indicators by the same expert and the differences in evaluation of the same evaluation indicator by different experts, the triangular fuzzy number is introduced to correct the membership degree evaluation results and non-membership degree evaluation results, so as to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation indicator.

[0012] Optionally, the first The expert on the first The membership and non-membership evaluation values ​​given by each evaluation indicator are respectively... and And satisfy: , , ; After correction, the optimized membership degree is obtained. and optimized non-membership degree ,in: No. The comprehensive membership degree corresponding to each evaluation indicator and combined non-membership degree They are respectively: ; ; in, , indicating the expert's serial number; This indicates the total number of experts who participated in the evaluation; , indicating the evaluation indicator number; Indicates the total number of evaluation indicators; Indicates the first The expert on the first The membership evaluation value given by each evaluation indicator; Indicates the first The expert on the first The non-membership evaluation value given by each evaluation indicator; Represents the th fuzzy number after optimization. The expert on the first Membership degree of each evaluation indicator; Represents the th fuzzy number after optimization. The expert on the first Non-membership degree of each evaluation indicator; and They represent the first One expert on all The sum of the membership evaluation values ​​and the sum of the non-membership evaluation values ​​given by each evaluation indicator; and Each represents all The expert on the first The sum of the membership evaluation values ​​and the sum of the non-membership evaluation values ​​given by each evaluation indicator; Indicates the first The comprehensive membership degree corresponding to each evaluation indicator; Indicates the first The comprehensive non-membership degree corresponding to each evaluation indicator.

[0013] Optionally, the step of calculating the index score of each candidate coal basin under each basin-scale standardized evaluation index based on the basin-scale standardized evaluation index, the comprehensive membership degree, and the comprehensive non-membership degree, and constructing a basin-scale decision matrix based on the index scores, includes: For each basin-scale standardized evaluation index of each candidate coal basin, the standardized index value, the corresponding comprehensive membership degree, and the corresponding comprehensive non-membership degree of the basin-scale standardized evaluation index are fused to obtain the index score of the candidate coal basin under the basin-scale standardized evaluation index. Based on the correspondence between the candidate coal basins and the basin-scale standardized evaluation indicators, the multiple candidate coal basins are used as rows, the multiple basin-scale standardized evaluation indicators are used as columns, and the index scores of each candidate coal basin under each basin-scale standardized evaluation indicator are used as matrix elements to construct the basin-scale decision matrix; wherein, the basin-scale decision matrix is ​​used to characterize the comprehensive suitability level of each candidate coal basin under each basin-scale evaluation indicator.

[0014] Optionally, the step of using the CRITIC method to calculate the weight of each basin-scale standardized evaluation index based on the basin-scale standardized evaluation index of multiple candidate coal basins, and using the VIKOR multi-attribute evaluation method to rank the multiple candidate coal basins based on the weights and the basin-scale decision matrix, and determining the candidate coal basin with the best ranking as the target coal basin, includes: Based on basin-scale standardized evaluation indicators of multiple candidate coal basins, the degree of fluctuation of each basin-scale standardized evaluation indicator and the degree of conflict between different basin-scale standardized evaluation indicators are determined, and the weight of each basin-scale standardized evaluation indicator is calculated according to the degree of fluctuation and the degree of conflict. Based on the weights and the basin-scale decision matrix, the VIKOR multi-attribute evaluation method is used to determine the group utility value and individual regret value of each candidate coal basin relative to the ideal evaluation result, and the compromise evaluation value of each candidate coal basin is determined based on the group utility value and the individual regret value. The candidate coal basins are ranked according to the compromise evaluation value, and the candidate coal basin with the best comprehensive ranking value is determined as the target coal basin.

[0015] Optionally, before determining the carbon dioxide geological storage area, the method further includes: performing on-site sealing verification on each candidate coal mining area, and removing the corresponding candidate coal mining area when the on-site sealing discrimination index is lower than a preset sealing threshold.

[0016] Optionally, the construction of the mining area-scale evaluation index set includes: Obtain first evaluation data to characterize the engineering geological conditions of the candidate coal mine sealing project; Obtain secondary evaluation data to characterize the geological space available for sealing and storage in candidate coal mining areas; Obtain third-party evaluation data to characterize the long-term stability of candidate coal mine areas; Obtain fourth evaluation data to characterize the economic efficiency of sealing and construction in candidate coal mine areas; Based on the first evaluation data, the second evaluation data, the third evaluation data, and the fourth evaluation data, the set of evaluation indicators at the mining area scale is constructed. The geological condition indicators for the sealing project are determined based on the structural capacity dimension of the candidate coal mining area, the effective sealing depth, and the geostress state index. The geological space indicators for sealing and storing are determined based on the average mining thickness of the candidate coal mining area, the total area of ​​the goaf, the average height of the caving zone, the average height of the water-conducting fracture zone, the average depth of the floor failure zone, and the average coefficient of fragmentation. The long-term stability index of the sealed area is determined based on the total thickness of the mudstone layer above the water-conducting fracture zone of the roof of the candidate coal mine area, the porosity of the caprock, the permeability of the caprock, and the breakthrough pressure of the caprock. The economic indicators for sealing construction are determined based on the well injection construction cost of the candidate coal mine area, the quality of the fractured overburden rock mass in the mining disturbance space, the surface population density of the site selection area, and the surface building distribution density of the site selection area.

[0017] On the other hand, a site selection system for carbon dioxide geological storage in deep mining spaces is also provided, including: The acquisition unit is used to acquire basin-scale evaluation data of multiple candidate coal basins and construct a set of basin-scale evaluation indicators, and within the target coal basin, acquire mine-scale evaluation data of multiple candidate coal mining areas and construct a set of mine-scale evaluation indicators. The processing unit is used to perform standardization processing to obtain the basin-scale standardized evaluation index of each basin-scale evaluation index in the basin-scale evaluation index set, and to construct an index evaluation set based on Pythagorean fuzzy set, and to optimize the membership degree and non-membership degree by introducing triangular fuzzy number to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation index. Based on the basin-scale standardized evaluation index, the comprehensive membership degree and the comprehensive non-membership degree, the unit calculates the index score of each candidate coal basin under each basin-scale standardized evaluation index, and constructs a basin-scale decision matrix based on the index score. The site selection unit is used to calculate the weight of each basin-scale standardized evaluation index based on the basin-scale standardized evaluation index of multiple candidate coal basins using the CRITIC method, and to rank the multiple candidate coal basins using the VIKOR multi-attribute evaluation method based on the weight and the basin-scale decision matrix, and to determine the candidate coal basin with the best ranking as the target coal basin. It also performs standardization processing on each mining area-scale evaluation index in the mining area-scale evaluation index set, and ranks the multiple candidate coal mining areas based on Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method to determine the carbon dioxide geological sequestration area.

[0018] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects: By selecting basin-scale evaluation data, multiple candidate coal basins can be ranked at the basin scale. Then, based on the mining area-scale evaluation data, multiple candidate coal mining areas within the optimally ranked target coal basin are ranked at the mining area scale, creating a progressive logic from macro-level screening to local optimization in the site selection process. This reduces the scope of invalid mining area evaluations, improves site selection efficiency, and ensures that the final determined carbon dioxide geological storage coal mining area simultaneously meets the requirements of regional suitability and mining engineering feasibility. Furthermore, during the site selection process, by implementing standardization, Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method, the deep correlation between evaluation data and carbon dioxide geological storage areas can be fully explored, avoiding reliance on subjective experience or single-indicator judgments and improving the objectivity and stability of carbon dioxide geological storage site selection results.

[0019] In this invention, the above-described technical solutions can be combined with each other to achieve more preferred combinations. Other features and advantages of this invention will be set forth in the following description, and some advantages may become apparent from the description or be learned by practicing the invention. The objects and other advantages of this invention can be realized and obtained from what is particularly pointed out in the description and drawings. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings. Figure 1 This is a flowchart of a method for selecting a site for geological carbon dioxide storage in deep mining spaces, provided by the present invention. Figure 2 This is a schematic diagram of a site selection system for carbon dioxide geological storage in deep mining spaces provided by the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0022] To facilitate understanding of the embodiments of this application, further explanation and description will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of this application. In the drawings, the dimensions and relative dimensions of components may be exaggerated for clarity and / or descriptive purposes. When exemplary embodiments can be implemented differently, a specific process sequence may be performed in a different order than described. For example, two consecutively described processes may be performed substantially simultaneously or in the reverse order of their description. Furthermore, the same reference numerals denote the same components.

[0023] The terminology used herein is for the purpose of describing particular embodiments and is not intended to be limiting. As used herein, unless the context clearly indicates otherwise, the singular forms “a” and “the” are intended to include the plural forms as well. Furthermore, when the terms “comprising” and / or “including” and variations thereof are used in this specification, it indicates the presence of the stated features, integrals, steps, operations, parts, components, and / or groups thereof, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, parts, components, and / or groups thereof. It should also be noted that, as used herein, the terms “substantially,” “about,” and other similar terms are used as approximate terms rather than as terms of degree, thus explaining the inherent biases in measurements, calculated values, and / or provided values ​​that will be recognized by those skilled in the art.

[0024] As described in the background section, utilizing the mining space in deep closed / abandoned mines to achieve secondary returns on resources and assets plays an important role and has significant implications for sustainable energy development and ecological environmental protection.

[0025] In practical applications, scientific and reasonable site suitability assessment and site selection are prerequisites for achieving carbon dioxide geological sequestration. my country's coal basins have complex engineering geology, hydrogeology, and structural geology conditions, and the suitability conditions for carbon sequestration in mining spaces are still unclear. Compared with the suitability assessment of carbon dioxide sequestration in saline aquifers and depleted oil and gas reservoirs, the suitability assessment methods for carbon dioxide geological sequestration in deep mining spaces at the coal basin-mining area scale are still in the exploratory stage, and there are few existing methods.

[0026] Against this backdrop, the present invention provides a site selection scheme for carbon dioxide geological storage in deep mining spaces. It can comprehensively analyze the engineering geological conditions of carbon dioxide geological storage in coal basins and mining areas at the deep mining space scale, and combine the VIKOR multi-attribute evaluation method of triangular fuzzy optimized Pythagorean fuzzy sets to construct a suitability evaluation model for carbon storage in coal basins and mining areas at the deep mining space scale. This allows for a reasonable and scientific evaluation and site selection of coal basin mining areas suitable for carbon storage in deep mining spaces.

[0027] See Figure 1 , Figure 1 This is a flowchart of a method for site selection of deep mining space carbon dioxide geological storage provided by the present invention. Figure 1 As shown, the site selection method for deep mining space carbon dioxide geological storage may include steps S101-S107: S101: Obtain basin-scale evaluation data for multiple candidate coal basins and construct a set of basin-scale evaluation indicators.

[0028] In some embodiments, first obtain Basin-scale evaluation data for candidate coal basins, denoted as [missing information]. ,in, .

[0029] Among them, basin-scale evaluation data is used to evaluate the suitability of coal basins.

[0030] In this embodiment, step S101 may include: acquiring a first type of evaluation data to characterize the engineering geological stability of the candidate coal basin; acquiring a second type of evaluation data to characterize the sequestration potential of the candidate coal basin; acquiring a third type of evaluation data to characterize the sequestration economics of the candidate coal basin; and constructing the basin-scale evaluation index set based on the first type of evaluation data, the second type of evaluation data, and the third type of evaluation data.

[0031] Specifically, this embodiment uses a basin-scale evaluation index set with a clear hierarchical structure to evaluate candidate coal basins. This avoids the mixing and stacking of evaluation indicators, and enables subsequent standardization, fuzzy evaluation, weighting, and ranking processes to have clear data sources and evaluation objects, thereby improving the systematic nature of basin-scale evaluation.

[0032] In some embodiments, the first type of evaluation data is used to measure engineering geological stability, evaluate whether the geological environment and external dynamic conditions of the area have the potential for long-term carbon dioxide sequestration, and ensure that carbon dioxide does not leak over a long time scale.

[0033] In one example, the first type of evaluation data includes: construction complexity metrics. Seismic activity indicators and geothermal flow field indicators .

[0034] Among them, the construction complexity index It measures the impact of geological tectonic activity on regional engineering stability. Among them, the density of active faults within a basin is an important indicator of tectonic complexity. The higher the density of active faults, the more intense the tectonic activity, the higher the tectonic complexity, and the worse the engineering geological stability.

[0035] However, structural complexity is not only affected by the density of active faults, but also by the scale of active faults and the tectonic activity of the basin basement. Even if the density of active faults is very small, the scale of the faults and the average Curie depth are relatively shallow, and the tectonic activity is relatively strong.

[0036] In this embodiment, a complexity index is constructed. Determined based on the density of active faults, the maximum fault size, and the average Curie depth within the candidate coal basin.

[0037] .

[0038] in, For the first The density of active faults within each candidate coal basin is expressed in terms of faults per 1010 3 ×km 2 ; For the first The maximum fault size within each candidate coal basin, in km; For the first The average Curie depth of each candidate coal basin is expressed in km. for The density-standardized value; for The standardized value of the maximum fracture scale; for The depth-standardized value.

[0039] Seismic activity indicators These are indicators used to measure the strength of the impact of seismic activity on regional engineering stability. Among them, the intensity and magnitude of earthquakes in a basin can directly reflect the strength of the earthquake impact and can be used as indicators for evaluating seismic activity. However, different sites may be in alternating phases of seismic activity, from calm to active. Even when the current seismic intensity and magnitude are relatively low, there is still a possibility of strong earthquakes occurring in the future. Therefore, the potential upper limit of the magnitude of future earthquakes at a site can serve as a supplement to different stages of seismic activity.

[0040] In this embodiment, seismic activity index The earthquake intensity, magnitude, and upper limit of magnitude of the candidate coal basin are determined based on the density of active faults, the maximum fault size, and the average Curie depth within the candidate coal basin.

[0041] .

[0042] in, For the first Seismic intensity of candidate coal basins, dimensionless; For the first Earthquake magnitudes in candidate coal basins, dimensionless; For the first The upper limit of the earthquake magnitude for each candidate coal basin is dimensionless. for The standardized value; for The standardized value; for The upper limit of the standardized value.

[0043] Geothermal flow field indicators It measures the impact of geothermal temperature on the stability of supercritical carbon dioxide sequestration in a coal basin. The average geothermal gradient in a coal basin is related to the stability of the sequestration state after supercritical carbon dioxide injection. In addition, the geothermal heat flow value is a physical quantity that characterizes the intensity of heat transfer from the Earth's interior to the surface and is a fundamental factor in the stability of the geothermal field. Therefore, the average geothermal gradient and geothermal heat flow value in a coal basin can be used as evaluation indicators for the geothermal flow field.

[0044] In this embodiment, the geothermal flow field index Determined based on geothermal flow values ​​and average geothermal gradient of candidate coal basins.

[0045] .

[0046] in, For the first Geothermal flow values ​​for candidate coal basins, in mW·m -2 ; For the first Average geothermal gradient of candidate coal basins, in °C / 100m; for The standardized value; for The standardized value.

[0047] In some embodiments, the second type of evaluation data primarily assesses the maximum potential of a sequestration basin to safely sequester carbon dioxide.

[0048] In one example, the second type of evaluation data includes the sealed volume index. and cap layer airtightness index Among them, the sealed volume index A measure of the sealed volume of mining space at the coal basin scale; an index of caprock tightness. It is used to measure the ability of the caprock in mining spaces at the coal basin scale to prevent CO2 from leaking upwards.

[0049] Specifically, in deep mining spaces at the basin scale, the number of closed coal mines is an indicator that directly affects the size of the sequestration volume. Due to the influence of regional groundwater flow fields, if the basin hydrodynamic conditions are strong, the inflow of mine water will affect the size of the sequestration volume. Therefore, the average mine water inflow is introduced to correct the evaluation of the sequestration volume.

[0050] In this embodiment, the sealing volume index The number of closed coal mines in candidate coal basins and the average water inflow of the mines are used to determine the number of mines.

[0051] .

[0052] in, For the first The number of closed coal mines in each candidate coal basin, in units of; For the first Average water inflow of mines in candidate coal basins, in cubic meters. 3 / h; for The standardized value; for The standardized value.

[0053] Considering that mining spaces are primarily physically confined, the thickness of the caprock in a coal basin directly affects its sealing capacity; a thicker caprock results in better sealing and a greater capacity for storing mining space. Given that caprock lithology varies, leading to differences in porosity and permeability, lower porosity and permeability can prevent CO2 capillary breakthrough and molecular diffusion, thus achieving a sealing effect. Therefore, the caprock thickness is modified based on porosity and permeability to evaluate its sealing capacity.

[0054] In this embodiment, the cap layer airtightness index Determined based on the effective thickness, porosity, and permeability of the caprock in the candidate coal basin.

[0055] .

[0056] in, For the first Effective thickness of caprock in candidate coal basins, in meters; For the first Porosity of the caprock of each candidate coal basin, in % . For the first Permeability of caprock in candidate coal basins, in mD; for The standardized value; for The standardized value; for The standardized value.

[0057] In some embodiments, the third type of evaluation data primarily evaluates the socio-economic conditions for achieving carbon dioxide sequestration in coal basins, based on technical feasibility.

[0058] In one example, the third type of evaluation data includes coal basin economic indicators. .

[0059] Specifically, the carbon source in the coal basin is the long-term supply condition for carbon dioxide sequestration. Its size and distance affect the cost and transportation difficulty of carbon sequestration projects. The larger the carbon source and the closer the distance, the more favorable it is for carbon dioxide sequestration projects.

[0060] In this embodiment, the economic indicators of coal basins Determined based on the size and distance of carbon sources in candidate coal basins.

[0061] .

[0062] in, For the first The carbon source size of each candidate coal basin is expressed in millions of tons. For the first Distances between candidate coal basin carbon sources, in km; for The standardized value; for The standardized value.

[0063] S102, Perform standardization processing to obtain the basin-scale standardized evaluation index for each basin-scale evaluation index in the basin-scale evaluation index set.

[0064] In some embodiments, when determining the set of basin-scale evaluation indicators, further standardization processing can be performed to eliminate differences in the dimensions of the evaluation indicators, improve the fairness of horizontal comparisons between different candidates, and provide a unified data foundation for the subsequent construction of the decision matrix.

[0065] In this embodiment, the standardization process may include: [details of the standardization process]. The candidate coal basins were in the first The original index values ​​under the basin-scale evaluation index, and the .... The maximum and minimum values ​​of each basin-scale evaluation index are compared among all candidate coal basins, and the results are calculated based on the original index values ​​and the differences between the maximum and minimum values. The candidate coal basins were in the first Basin-scale standardized evaluation indicators under basin-scale evaluation indicators; wherein, the maximum value is the first... The basin-scale evaluation index is The maximum original index value among the candidate coal basins, wherein the minimum value is the first... The basin-scale evaluation index is The minimum original index value among the candidate coal basins.

[0066] .

[0067] in, Indicates the first The candidate evaluation object in the first Raw data under each evaluation indicator; This represents the corresponding standardized evaluation index; Indicates the first The maximum value of each evaluation indicator among all candidate evaluation objects; Indicates the first The minimum value of each evaluation indicator among all candidate evaluation objects.

[0068] S103, construct an index evaluation set based on Pythagorean fuzzy set, and introduce triangular fuzzy number to optimize membership degree and non-membership degree, so as to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation index.

[0069] In some embodiments, when determining basin-scale standardized evaluation indicators, Pythagorean fuzzy sets are constructed based on Pythagorean fuzzy mathematics theory.

[0070] Furthermore, the large workload of expert scoring scales can easily lead to confusion in judgments. To address the consistency problem in constructing Pythagorean fuzzy sets, the concept of triangular fuzzy numbers is introduced into the Pythagorean fuzzy set to obtain a triangular fuzzy optimized Pythagorean fuzzy set.

[0071] By using triangular fuzzy numbers for optimization, the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation index can be obtained.

[0072] In one example, step S103 may include: obtaining the membership degree evaluation results and non-membership degree evaluation results of multiple experts for each of the basin-scale standardized evaluation indicators; constructing a Pythagorean fuzzy set based on the membership degree evaluation results and non-membership degree evaluation results; and introducing the triangular fuzzy number to correct the membership degree evaluation results and non-membership degree evaluation results according to the evaluation differences of the same expert on different evaluation indicators and the evaluation differences of different experts on the same evaluation indicator, so as to obtain the comprehensive membership degree and comprehensive non-membership degree of each of the basin-scale standardized evaluation indicators.

[0073] In other words, based on Pythagorean fuzzy sets and triangular fuzzy numbers, the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation index are determined.

[0074] In one example, get Each expert commented on The evaluation indicators provide membership and non-membership evaluation values. Among them, the first... The expert on the first The membership and non-membership evaluation values ​​given by each evaluation indicator are denoted as follows: and ,in, , .

[0075] Furthermore, the membership evaluation value and the non-membership evaluation value satisfy: .

[0076] In other words, Pythagorean fuzzy sets Among them, membership degree Non-membership degree ,and .

[0077] By introducing the concept of triangular fuzzy numbers and Pythagorean fuzzy sets, and through correction operations, the optimized membership degrees are obtained. and optimized non-membership degree ,in: ; ; Based on this, the first The comprehensive membership degree corresponding to each evaluation indicator and combined non-membership degree They are respectively: ; ; in, , indicating the expert's serial number; This indicates the total number of experts who participated in the evaluation; , indicating the evaluation indicator number; Indicates the total number of evaluation indicators; Indicates the first The expert on the first The membership evaluation value given by each evaluation indicator; Indicates the first The expert on the first The non-membership evaluation value given by each evaluation indicator; Represents the th fuzzy number after optimization. The expert on the first Membership degree of each evaluation indicator; Represents the th fuzzy number after optimization. The expert on the first Non-membership degree of each evaluation indicator; and They represent the first One expert on all The sum of the membership evaluation values ​​and the sum of the non-membership evaluation values ​​given by each evaluation indicator; and Each represents all The expert on the first The sum of the membership evaluation values ​​and the sum of the non-membership evaluation values ​​given by each evaluation indicator; Indicates the first The comprehensive membership degree corresponding to each evaluation indicator; Indicates the first The comprehensive non-membership degree corresponding to each evaluation indicator.

[0078] By adopting the above technical solution, we can reduce the inconsistency of subjective evaluation while retaining expert experience, and improve the stability and credibility of indicator evaluation results.

[0079] S104. Based on the basin-scale standardized evaluation index, the comprehensive membership degree, and the comprehensive non-membership degree, calculate the index score of each candidate coal basin under each basin-scale standardized evaluation index, and construct a basin-scale decision matrix based on the index score.

[0080] In some embodiments, after determining the basin-scale standardized evaluation indicators and their corresponding comprehensive membership and comprehensive non-membership, a basin-scale decision matrix can be further constructed to facilitate subsequent evaluation operations.

[0081] In one example, step S104 may include: for each basin-scale standardized evaluation index of each candidate coal basin, fusing the standardized index value, corresponding comprehensive membership degree, and corresponding comprehensive non-membership degree of the basin-scale standardized evaluation index to obtain the index score of the candidate coal basin under the basin-scale standardized evaluation index; constructing the basin-scale decision matrix by taking multiple candidate coal basins as rows, multiple basin-scale standardized evaluation indexes as columns, and the index score of each candidate coal basin under each basin-scale standardized evaluation index as matrix elements, according to the correspondence between the candidate coal basins and the basin-scale standardized evaluation index; wherein, the basin-scale decision matrix is ​​used to characterize the comprehensive suitability level of each candidate coal basin under each basin-scale evaluation index.

[0082] For example, the index scores of each candidate coal basin under each basin-scale evaluation index: ; in, For the first The candidate coal basins were in the first The overall score under the evaluation indicators at the basin scale; For the first The candidate coal basins were in the first Standardized evaluation indicators under basin-scale evaluation indicators; For the first The comprehensive membership degree corresponding to each evaluation indicator; For the first The comprehensive non-membership degree corresponding to each evaluation indicator.

[0083] Next, using candidate coal basins as rows and basin-scale evaluation indicators as columns, a basin-scale decision matrix is ​​constructed: ; in, This is a basin-scale decision matrix; This represents the number of evaluation indicators at the basin scale.

[0084] In this embodiment, In this case, the basin-scale decision matrix is ​​as follows: S105, using the CRITIC method based on basin-scale standardized evaluation indicators of multiple candidate coal basins, calculate the weight of each basin-scale standardized evaluation indicator, and based on the weight and the basin-scale decision matrix, use the VIKOR multi-attribute evaluation method to rank the multiple candidate coal basins, and determine the candidate coal basin with the best ranking as the target coal basin.

[0085] In some embodiments, after constructing the basin-scale decision matrix, the CRITIC method and the VIKOR multi-attribute evaluation method are used to rank the multiple candidate coal basins. Based on the ranking results, the target coal basin can be determined.

[0086] In this embodiment, step S105 may include: determining the fluctuation degree of each basin-scale standardized evaluation index and the degree of conflict between different basin-scale standardized evaluation indices based on basin-scale standardized evaluation indices of multiple candidate coal basins, and calculating the weight of each basin-scale standardized evaluation index according to the fluctuation degree and the degree of conflict; determining the group utility value and individual regret value of each candidate coal basin relative to the ideal evaluation result using the VIKOR multi-attribute evaluation method according to the weight and the basin-scale decision matrix, and determining the compromise evaluation value of each candidate coal basin based on the group utility value and the individual regret value; ranking the multiple candidate coal basins according to the compromise evaluation value, and determining the candidate coal basin with the best comprehensive ranking value as the target coal basin.

[0087] Specifically, after obtaining the basin-scale standardized evaluation indicators and the basin-scale decision matrix, the CRITIC method is used to determine the weights of each basin-scale standardized evaluation indicator, and the VIKOR multi-attribute evaluation method is further used to rank multiple candidate coal basins.

[0088] In this embodiment, for any basin-scale standardized evaluation index, the changes in the index values ​​across multiple candidate coal basins are statistically analyzed, and these changes are used to characterize the degree of fluctuation of the basin-scale standardized evaluation index. The greater the degree of fluctuation, the stronger the ability of the basin-scale standardized evaluation index to distinguish between different candidate coal basins, and the greater its information contribution in the target coal basin selection process.

[0089] Furthermore, by calculating the correlation between any two basin-scale standardized evaluation indicators, the degree of information overlap between different basin-scale standardized evaluation indicators is characterized. The stronger the correlation between two basin-scale standardized evaluation indicators, the closer the information they reflect, and the lower the corresponding degree of conflict; conversely, the weaker the correlation, the greater the difference in the information they reflect, and the higher the corresponding degree of conflict. Therefore, the degree of conflict corresponding to each basin-scale standardized evaluation indicator can be determined based on its correlation with other basin-scale standardized evaluation indicators.

[0090] Then, the degree of index fluctuation and the degree of conflict are combined to obtain the information content of the basin-scale standardized evaluation index. The greater the degree of index fluctuation and the higher the degree of conflict, the greater the information content of the basin-scale standardized evaluation index; the smaller the degree of index fluctuation and the higher the degree of information overlap with other indicators, the smaller the information content of the basin-scale standardized evaluation index.

[0091] Subsequently, the information content of each basin-scale standardized evaluation indicator was normalized to obtain the weight of each basin-scale standardized evaluation indicator.

[0092] The resulting weights can simultaneously reflect the data dispersion of the indicators themselves and the information conflict between the indicators, thereby reducing the impact of subjective weighting on the screening results of target coal basins.

[0093] After determining the weights of the standardized evaluation indicators at the basin scale, the ideal and non-ideal evaluation results corresponding to each standardized evaluation indicator at the basin scale are determined from the basin scale decision matrix.

[0094] Furthermore, based on the difference between the index scores of each candidate coal basin under each basin-scale standardized evaluation index and the corresponding ideal evaluation result, and in conjunction with the weights of each basin-scale standardized evaluation index, the group utility value of each candidate coal basin is calculated. The group utility value characterizes the overall deviation of the candidate coal basin from all basin-scale standardized evaluation indices. The smaller the group utility value, the closer the candidate coal basin is to the ideal evaluation result at the overall evaluation level.

[0095] Meanwhile, based on the weighted deviation of each candidate coal basin under the standardized evaluation indicators at each basin scale, the individual regret value of the candidate coal basin is determined.

[0096] After obtaining the group utility value and individual regret value for each candidate coal basin, a compromise evaluation value for each candidate coal basin is calculated based on the group utility value and individual regret value.

[0097] Finally, the candidate coal basins were ranked based on their compromise evaluation values. The smaller the overall ranking value, the closer the corresponding candidate coal basin is to the ideal evaluation result, and the higher its suitability for carbon sequestration in the mining space.

[0098] The candidate coal basin with the best comprehensive ranking value is identified as the target coal basin, and the corresponding index score, index weight, group utility value, individual regret value and comprehensive ranking value of the target coal basin are output as the basis for the selection of carbon sequestration sites in mining space and subsequent engineering deployment.

[0099] For example, suppose the first The standard deviation of each evaluation indicator is , No. The evaluation index and the first The correlation coefficients among the evaluation indicators are: Then the first The information content of each evaluation indicator is: No. The weights of each evaluation indicator are: And satisfy: in, Indicates the first The amount of information in each evaluation indicator; Indicates the first The degree of data dispersion of each evaluation indicator; Indicates the first The evaluation index and the first Correlation coefficients among the evaluation indicators; Indicates the first The weight of each evaluation indicator.

[0100] In this embodiment, when performing basin-scale evaluation: .

[0101] Next, the VIKOR multi-attribute evaluation method was used to evaluate... The candidate coal basins were ranked.

[0102] Assume the first The optimal and worst values ​​of the basin-scale evaluation index are as follows: and .

[0103] Then the first The group utility value of each candidate coal basin is: No. The individual regret value for each candidate coal basin is: In this case: , , , .

[0104] Then the first The compromise evaluation value for the candidate coal basins is: in, Indicates the first The group utility value of each candidate coal basin; Indicates the first Individual regret value for each candidate coal basin; Indicates the first Compromise evaluation values ​​for candidate coal basins; The decision-making mechanism coefficient represents the degree of preference of decision-makers for group utility. .

[0105] Finally, according to Multiple candidate coal basins are sorted in ascending order, and the candidate coal basin with the best ranking is determined as the target coal basin.

[0106] S106. Within the target coal basin, acquire mining area-scale evaluation data for multiple candidate coal mining areas and construct a set of mining area-scale evaluation indicators.

[0107] In some embodiments, when identifying the target coal basin, mining-scale evaluation data is acquired. Based on the selected mining-scale evaluation data, the optimal carbon dioxide geological sequestration zone is selected.

[0108] In this embodiment, step S106 may include: obtaining first evaluation data to characterize the engineering geological conditions of the candidate coal mine area for sealing; obtaining second evaluation data to characterize the geological space available for sealing in the candidate coal mine area; obtaining third evaluation data to characterize the long-term stability of the candidate coal mine area for sealing; obtaining fourth evaluation data to characterize the economic efficiency of the candidate coal mine area for sealing construction; and constructing the set of evaluation indicators at the mine area scale based on the first evaluation data, the second evaluation data, the third evaluation data, and the fourth evaluation data.

[0109] Specifically, this embodiment uses a mining-scale evaluation dataset with a clear hierarchical structure to evaluate candidate coal basins. This achieves a scale transformation from macroscopic target coal basins to specific candidate coal mining areas, ensuring that the finally determined sealed coal mining areas are not only located within suitable basins but also possess mining-scale engineering feasibility.

[0110] In this embodiment, the geological condition indicators of the sealed engineering project are preserved. It measures the impact of engineering geological conditions in the prospective mining area on the suitability of carbon dioxide geological sequestration. Since the mining area is smaller in scale than the basin, the tectonic conditions are clearer. The tectonic capacity dimension is selected as one of the indicators to reflect the engineering geological conditions of coal mine sequestration, which has physical significance in reflecting the degree of fragmentation and continuity of the overlying rock mass.

[0111] Furthermore, since the critical pressure of carbon dioxide is 7.38 MPa and the critical temperature is 31.1℃, carbon dioxide sequestration in coal mining areas requires ensuring that the carbon dioxide is in a supercritical state. The sequestration depth within the mining space is crucial. However, after mining disturbances, the roof overburden develops mining-induced fractures. The effective sequestration depth after carbon dioxide injection is actually the difference between the mining depth and the maximum water-conducting fracture zone. Therefore, the effective sequestration depth is selected as one of the geological conditions indicators for coal mining sequestration engineering. In addition, the geostress state index can characterize the differences in the geostress environment of the rock mass and accurately describe the stress state of the surrounding rock mass in the mining space before supercritical carbon dioxide injection, reflecting the stability of the rock mass in the geological conditions of the sequestration engineering.

[0112] In other words, geological condition indicators of the sealing project The determination is based on the tectonic capacity dimension, effective sealing depth, and geostress state index of the candidate coal mining area.

[0113] in, For the first The structural capacity dimension of each candidate coal mining area; For the first The effective sealing depth of each candidate coal mining area is shown in meters. For the first The geostress state index of each candidate coal mining area is dimensionless. for The standardized value; for The standardized value; for The standardized value.

[0114] Sequestration of Geological Space Indicators It is an indicator for measuring the supercritical carbon dioxide storage capacity of a prospective ore deposit. It is determined by the size of the channels and fissures within the goaf, caving zone, water-conducting fracture zone, and floor failure zone formed by excavation. As the goaf advances, the disturbed rock strata collapse and fragment.

[0115] Based on this, the geological space index for sealing and storing The parameters are determined based on the average mining thickness, total area of ​​goaf, average caving zone height, average water-conducting fracture zone height, average floor failure zone depth, and average fragmentation coefficient of the candidate coal mining area.

[0116] in, For the first The average mining thickness of each candidate coal mining area is in meters. For the first The total area of ​​the goaf in each candidate coal mining area, in m². 2 ; For the first The average caving zone height of each candidate coal mining area is shown in meters. For the first The average height of the water-conducting fracture zone in each candidate coal mining area is given in meters. For the first The average depth of the floor failure zone in each candidate coal mining area, in meters; For the first The average fragmentation coefficient of each candidate coal mining area is dimensionless. for The standardized value; for The standardized value; for The standardized value; for The standardized value; for The standardized value; for The standardized value.

[0117] Long-term stability indicators of storage This indicator measures the long-term stability of supercritical carbon dioxide storage in a prospective mining area. It is closely related to the trapping and storage capacity of the overburden layer in the mining space, and is influenced by the properties, effective thickness, and breakthrough pressure of the overburden layer. Combining the caprock tightness index f5 at the basin scale, this invention introduces caprock breakthrough pressure at the coal mining area scale to further evaluate the long-term stability of supercritical carbon dioxide storage in the mining area.

[0118] In this embodiment, the long-term stability index of the seal is stored. The determination was based on the total thickness of the mudstone layer above the water-conducting fracture zone in the roof of the candidate coal mine area, the porosity of the caprock, the permeability of the caprock, and the breakthrough pressure of the caprock.

[0119] in, For the first The total thickness of the mudstone layer above the water-conducting fracture zone in the roof of each candidate coal mining area is expressed in meters. For the first Porosity of the caprock in each candidate coal mining area; For the first Permeability of the caprock in each candidate coal mining area; For the first The overburden breakthrough pressure of each candidate coal mining area is expressed in MPa. for The standardized value; for The standardized value; for The standardized value; for The standardized value.

[0120] Economic indicators of sealing construction These are economic indicators for measuring the feasibility of supercritical carbon dioxide storage in a prospective mining area. Among them, the construction cost of injection wells is the most direct indicator for measuring the economic feasibility of supercritical carbon dioxide storage in a coal mine area. Considering that the mining-induced overburden formed after the coal resources are mined out will greatly increase the probability of accidents during the construction of injection wells, the quality of the fractured overburden in the mining disturbance space also has a certain impact on the construction cost of injection wells. In addition, the distribution of the surface population and buildings in the site selection area also have an important impact on the economics of storage construction. The higher the population density and the more buildings there are, the higher the direct economic loss caused by relocation, and the worse the economics of storage construction.

[0121] In this embodiment, the economic indicators of the sealed construction are preserved. The determination is based on the well injection construction cost of the candidate coal mine area, the quality of the fractured overburden rock mass in the mining disturbance space, the surface population density of the site selection area, and the surface building distribution density of the site selection area.

[0122] In the formula, For the first The well injection construction cost for each candidate coal mine area is in ten thousand yuan. For the first The average BQ evaluation value of fractured overburden rock mass within the mining disturbance space of each candidate coal mining area; For the first Surface population density of candidate coal mining areas, in people / km² 2 ; For the first Density of surface buildings in the site selection area of ​​each candidate coal mining area, in units / km² 2 ; for The standardized value; for The standardized value; for The standardized value; for The standardized value.

[0123] S107, each mining area scale evaluation index in the mining area scale evaluation index set is standardized, and multiple candidate coal mining areas are sorted based on Pythagorean fuzzy set, triangular fuzzy number, CRITIC method and VIKOR multi-attribute evaluation method to determine carbon dioxide geological sequestration areas.

[0124] In some embodiments, the evaluation indicators at each mining area scale are standardized in accordance with the manner listed in steps S102 to S105, and the candidate coal mining areas are ranked based on Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method to determine the carbon dioxide geological sequestration zone.

[0125] In other words, the same method is used to process each mining area-scale evaluation indicator in the mining area-scale evaluation indicator set. The difference lies in: when conducting mining area-scale evaluation, .

[0126] In some embodiments, after obtaining candidate mining areas based on the results of the mining area-scale suitability assessment, and before determining the final site selection result for carbon dioxide geological storage, a step of on-site closure verification of the candidate mining areas is included. This step is used to conduct on-site verification of the candidate mining areas obtained from the aforementioned mining area-scale suitability assessment to determine whether there are hidden connecting passages, pressure relief passages, or risks of CO2 entering the mine water system within the mining space of the candidate mining areas.

[0127] That is, before determining the carbon dioxide geological storage area, the method further includes: performing on-site sealing verification on each candidate coal mine area, and removing the corresponding candidate coal mine area when the on-site sealing discrimination index is lower than the preset sealing threshold.

[0128] In this embodiment, the on-site sealing verification of each candidate coal mining area includes: selecting a target mining space within the candidate mining area, wherein the target mining space is at least one of a goaf, abandoned roadway, caving zone, or water-conducting fracture zone; injecting a mixture of CO2 and inert tracer gas into the target mining space, and sequentially performing pressurization injection, constant pressure maintenance, and pressure recovery at the injection stop according to at least two step injection pressures, wherein the highest step injection pressure is less than the caprock breakthrough pressure of the candidate mining area; collecting pressure decay data of the target mining space after injection stop and pressure response data of non-target mining spaces. The data includes target mining space pressure decay data, non-target mining space tracer gas concentration data, and mine water chemical response data. A pressure retention coefficient is determined based on the target mining space pressure decay data, a non-target mining space connectivity response coefficient is determined based on the non-target mining space pressure response data, a tracer gas breakthrough coefficient is determined based on the non-target mining space tracer gas concentration data, and a mine water CO2 response coefficient is determined based on the mine water chemical response data. A site sealing discrimination index is then determined based on the pressure retention coefficient, non-target space connectivity response coefficient, tracer gas breakthrough coefficient, and mine water CO2 response coefficient.

[0129] For example, the target mining space is selected from mining area areas with high geological space index for storage, sufficient effective storage depth, and good caprock sealing in the mining area scale suitability evaluation results.

[0130] After determining the target mining area, injection holes are arranged within the target mining area, and non-target monitoring points are arranged around the target mining area. These non-target monitoring points include at least one of the following: adjacent goaf monitoring points, abandoned roadway monitoring points, monitoring points near faults, monitoring points in overlying aquifers, monitoring points in water-conducting fracture zones, and mine water drainage points. Pressure changes, tracer gas concentration changes, and mine water chemical parameter changes in areas outside the target mining area are obtained through these monitoring points.

[0131] Subsequently, a mixture of CO2 and inert tracer gas is injected into the target mining space. The inert tracer gas can be one or more of helium, argon, and krypton. The injection process employs a stepped pressure pulse injection method, with at least two stepped injection pressures set, and each stepped injection pressure satisfying the following: in, Inject pressure into each step, The caprock breakthrough pressure in the candidate mining area is determined. By ensuring that the highest step injection pressure is lower than the caprock breakthrough pressure, it is possible to avoid inducing caprock damage or creating new leakage channels during on-site verification.

[0132] Each injection pressure step includes a pressure-increasing injection phase, a constant pressure holding phase, and a pressure recovery phase. In the pressure-increasing injection phase, the pressure in the target mining space is increased to the corresponding injection pressure step. In the constant pressure holding phase, the target mining space is maintained at the corresponding injection pressure step for a preset time. In the pressure recovery phase, injection is stopped and the pressure decay change in the target mining space over time is recorded.

[0133] During the pressure recovery phase after injection is stopped, a pressure retention coefficient is determined based on the pressure decay data of the target mining space. This pressure retention coefficient characterizes the target mining space's ability to maintain the injected gas pressure.

[0134] The pressure retention coefficient is determined as follows: .

[0135] in, The pressure retention coefficient, After a preset time has elapsed since the betting was stopped The pressure within the target mining space at that time, To inject initial pressure into the target mining space before injection. Inject pressure into the corresponding steps.

[0136] It should be noted that a high pressure retention coefficient indicates that the pressure decays slowly after the injection in the target mining space is stopped, indicating good sealing. A low pressure retention coefficient indicates that the target mining space may have a pressure relief channel or be connected to the external space.

[0137] Simultaneously, pressure response data of non-target mining spaces are collected during the injection and de-injection processes. These non-target mining spaces include adjacent goaf areas, abandoned roadways, water-conducting fracture zones, fault-affected areas, or overlying aquifers outside the target mining space. The connectivity response coefficient of the non-target mining spaces is determined based on the pressure response data.

[0138] The non-target space connectivity response coefficients are determined as follows: .

[0139] in, For non-target space connectivity response coefficients, For the first Pressure increment at non-target monitoring points Inject pressure increments into the target mining space. For the first The lag time in pressure response at non-target monitoring points This is the preset time normalization coefficient.

[0140] It should be noted that if the pressure response amplitude of a non-target monitoring point is large and the response lag time is short, it indicates that there is a strong connection between the target mining space and the non-target space, and the risk of CO2 escape is high.

[0141] Furthermore, gas samples were collected at non-target monitoring points, and the concentration of inert tracer gas was detected. The tracer gas breakthrough coefficient was determined based on the tracer gas concentration data of the non-target mining space.

[0142] The tracer gas breakthrough coefficient is determined as follows: .

[0143] in, The breakthrough coefficient for tracer gas. For the first Non-target monitoring points The concentration of tracer gas at any given time. For the first Non-target monitoring points Gas flow rate at any given time The concentration of tracer gas injected into the mixed gas. To inject the total volume of the mixed gas, This represents the number of non-target monitoring points.

[0144] The larger the tracer gas breakthrough coefficient, the higher the proportion of tracer gas entering the non-target space, and the worse the sealing of the target mining space.

[0145] Simultaneously, mine water chemical response data were collected. This data included at least one of the following: pH value, bicarbonate concentration, conductivity, calcium ion concentration, and magnesium ion concentration before and after injection. The mine water CO2 response coefficient was determined based on the mine water chemical response data.

[0146] When the CO2 response coefficient of mine water is high, it indicates that CO2 or its dissolved products may enter the mine water system, and there is a risk that the target mining space is connected to the hydraulic channel.

[0147] After obtaining the pressure retention coefficient, non-target space connectivity response coefficient, tracer gas breakthrough coefficient, and mine water CO2 response coefficient, the on-site sealing discrimination index is determined. The on-site sealing discrimination index is determined as follows: .

[0148] in, As an index for determining the closure of the site, The pressure retention coefficient, For non-target space connectivity response coefficients, The breakthrough coefficient for tracer gas. The CO2 response coefficient of mine water.

[0149] In one alternative implementation, if all target mining spaces within a candidate mining area fail the on-site closure verification, the candidate mining area is removed from the final carbon dioxide geological storage site selection results; if at least one target mining space within a candidate mining area passes the on-site closure verification, the target mining space that passes the verification is taken as the preferred storage space within the candidate mining area, and the final carbon dioxide geological storage site selection results are determined in conjunction with the aforementioned mining area scale suitability evaluation ranking results.

[0150] In this way, the original coal basin-mining area scale suitability evaluation results are combined with the field pressure response, tracer gas response and mine water chemical response. This makes the final site selection result not only dependent on static geological data and evaluation indicators, but also subject to field closure verification, thereby improving the reliability of the site selection for carbon dioxide geological sequestration in deep mining spaces.

[0151] The following example will illustrate this in detail.

[0152] First, data on the suitability assessment of coal basin-level carbon dioxide geological storage were collected, as shown in Table 1.

[0153] Table 1. Data on the suitability assessment of carbon dioxide geological sequestration in coal basins. The above indicators can be used to obtain the suitability evaluation index for carbon dioxide geological sequestration at the coal basin scale, as shown in Table 2.

[0154] Table 2. Suitability Evaluation Indicators for Coal Basin-Level Carbon Dioxide Geological Sequestration Based on Pythagorean fuzzy mathematics theory, and through scoring by four experts, the Pythagorean fuzzy set is constructed as follows: Table 3 Pythagorean fuzzy sets of carbon dioxide geological sequestration in coal basins Introducing the concept of triangular fuzzy number into the Pythagorean fuzzy set, and based on relevant calculation formulas, the triangular fuzzy optimized Pythagorean fuzzy set is shown in Table 4: Table 4. Triangular Fuzzy Optimization of Pythagorean Fuzzy Set for Coal Basin-Level Carbon Dioxide Geological Sequestration Based on the triangular fuzzy optimization of the Pythagorean fuzzy set, the score function of each indicator for the four coal-selecting basins is shown in Table 5.

[0155] Table 5. Statistics of Scoring Functions for Candidate Basins Next, the comprehensive weights of each indicator can be obtained using the CRITIC method, as shown in Table 6.

[0156] Table 6 shows the comprehensive weights of each indicator obtained using the CRITIC method. Substituting the weights of each indicator into the scores of each indicator in the four coal-selecting basins, a multi-attribute decision matrix was constructed. The calculation results of group utility Si and individual regret Ri are shown in Table 7. Assuming the decision mechanism coefficient is 0.9, the VIKOR value was calculated based on the data and is shown in Table 7.

[0157] Table 7 Weights of various indicators for carbon dioxide geological sequestration in coal basins As shown in Table 7, coal basin B has the highest Q value at 0.9483, followed by coal basin A, while coal basin D has the lowest at 0. Therefore, coal basin B is clearly superior to the other coal basins and is selected as a potential suitable coal basin for carbon sequestration in deep mining spaces.

[0158] Next, data on the suitability assessment of carbon dioxide geological sequestration in five coal mining areas of Coal Basin B were collected, as shown in Table 8.

[0159] Table 8. Data on the suitability assessment of carbon dioxide geological sequestration in coal basins. Based on the above indicators and the data processing method in the aforementioned embodiments, the suitability evaluation index for carbon dioxide geological sequestration at the coal basin scale can be calculated, as shown in Table 9.

[0160] Table 9. Suitability Evaluation Indicators for Coal Basin-Level Carbon Dioxide Geological Sequestration Based on Pythagorean fuzzy mathematics theory, and through scoring by four experts, the Pythagorean fuzzy set is constructed as follows: Table 10 Pythagorean Fuzzy Sets for Carbon Dioxide Geological Sequestration at the Coal Mine Area Level Introducing the concept of triangular fuzzy number in the Pythagorean fuzzy set, and based on relevant calculation formulas, the triangular fuzzy optimized Pythagorean fuzzy set is shown in Table 11: Table 11. Triangular Fuzzy Optimization Pythagorean Fuzzy Set for Coal Mine Area-Level Carbon Dioxide Geological Sequestration Based on the triangular fuzzy optimization of the Pythagorean fuzzy set, the score function of each indicator for the five candidate mining areas is shown in Table 12.

[0161] Table 12 Statistics of Indicator Scoring Functions for Mineral Processing Areas Next, the comprehensive weights of each indicator can be obtained using the CRITIC method, as shown in Table 13.

[0162] Table 13 Weights of various indicators for carbon dioxide geological sequestration in coal basins Substituting the weights of each indicator into the scores of each indicator in the five candidate coal mining areas, a multi-attribute decision matrix was constructed. The calculation results of group utility Si and individual regret Ri are shown in Table 14.

[0163] Assuming the decision-making mechanism coefficient is 0.5, the VIKOR value calculated based on the data is shown in Table 14.

[0164] Table 14 Weights of Indicators for Coal Basin-Level Carbon Dioxide Geological Sequestration As shown in Table 14, coal mining area b3 has the highest Q value at 1.0, followed by coal mining area b2 at 0.6231, and coal mining area b1 has the lowest at 0. Therefore, coal mining area b3 is clearly superior to the other coal mining areas and is selected as a potential suitable coal mining area for carbon sequestration in deep mining spaces.

[0165] Based on the above calculation results, the optimal potential site for carbon dioxide sequestration in deep mining spaces is coal mining area b3 in coal basin B.

[0166] The above description, in conjunction with embodiments, illustrates the site selection method for geological storage of carbon dioxide. To facilitate understanding and implementation by those skilled in the art, the system structure corresponding to the method is further described below.

[0167] See Figure 2 , Figure 2 This is a schematic diagram of a site selection system for carbon dioxide geological storage in deep mining spaces provided by the present invention. Figure 2 As shown, the deep mining space carbon dioxide geological storage site selection system 200 may include: The acquisition unit 210 is used to acquire basin-scale evaluation data of multiple candidate coal basins and construct a set of basin-scale evaluation indicators, and within the target coal basin, acquire mine-scale evaluation data of multiple candidate coal mining areas and construct a set of mine-scale evaluation indicators. Processing unit 220 is used to perform standardization processing to obtain the basin-scale standardized evaluation index of each basin-scale evaluation index in the basin-scale evaluation index set, and to construct an index evaluation set based on Pythagorean fuzzy set, and to introduce triangular fuzzy number to optimize the membership degree and non-membership degree to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation index. Based on the basin-scale standardized evaluation index, the comprehensive membership degree and the comprehensive non-membership degree, the unit calculates the index score of each candidate coal basin under each basin-scale standardized evaluation index, and constructs a basin-scale decision matrix based on the index score. The site selection unit 230 is used to calculate the weight of each basin-scale standardized evaluation index based on the basin-scale standardized evaluation index of multiple candidate coal basins using the CRITIC method, and to rank the multiple candidate coal basins using the VIKOR multi-attribute evaluation method based on the weight and the basin-scale decision matrix, and to determine the candidate coal basin with the best ranking as the target coal basin. It also performs standardization processing on each mining area-scale evaluation index in the mining area-scale evaluation index set, and ranks the multiple candidate coal mining areas based on Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method to determine the carbon dioxide geological sequestration area.

[0168] For further details regarding the acquisition unit 210, the processing unit 220, and the addressing unit 230, please refer to the foregoing examples.

[0169] It is understandable that the above division of units is only a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, the above units can be implemented by the processor calling software.

[0170] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above description is only a specific embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for site selection of deep mining space carbon dioxide geological storage, characterized in that, include: Obtain basin-scale evaluation data for multiple candidate coal basins and construct a set of basin-scale evaluation indicators. Perform standardization processing to obtain the basin-scale standardized evaluation index for each basin-scale evaluation index in the basin-scale evaluation index set. Based on the Pythagorean fuzzy set, an evaluation set of indicators is constructed, and the membership degree and non-membership degree are optimized by introducing triangular fuzzy numbers to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation indicator. Based on the basin-scale standardized evaluation index, the comprehensive membership degree, and the comprehensive non-membership degree, calculate the index score of each candidate coal basin under each basin-scale standardized evaluation index, and construct a basin-scale decision matrix based on the index score. The CRITIC method is used to calculate the weight of each basin-scale standardized evaluation index based on multiple candidate coal basins. Based on the weight and the basin-scale decision matrix, the VIKOR multi-attribute evaluation method is used to rank the multiple candidate coal basins, and the candidate coal basin with the best ranking is determined as the target coal basin. Within the target coal basin, mine-scale evaluation data of multiple candidate coal mining areas are acquired, and a set of mine-scale evaluation indicators is constructed. Each mining area scale evaluation index in the mining area scale evaluation index set is standardized, and multiple candidate coal mining areas are ranked based on Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method to determine the carbon dioxide geological sequestration zone.

2. The method for selecting a site for carbon dioxide geological storage according to claim 1, characterized in that, The constructed basin-scale evaluation index set includes: Obtain first-class evaluation data to characterize the engineering geological stability of the candidate coal basin; Obtain a second type of evaluation data to characterize the storage potential of the candidate coal basins; Obtain third-type evaluation data to characterize the economic viability of the candidate coal basins for sequestration; Based on the first type of evaluation data, the second type of evaluation data, and the third type of evaluation data, the basin-scale evaluation index set is constructed.

3. The method for selecting a site for carbon dioxide geological storage according to claim 2, characterized in that, The first type of evaluation data includes: structural complexity index, seismic activity index, and geothermal flow field index; wherein the structural complexity index is determined based on the active fault density, maximum fault scale, and average Curie depth within the candidate coal basin; the seismic activity index is determined based on the seismic intensity, earthquake magnitude, and upper limit of magnitude of the candidate coal basin; and the geothermal flow field index is determined based on the geothermal flow value and average geothermal gradient of the candidate coal basin. The second type of evaluation data includes the sealed volume index and the caprock sealing index; wherein, the sealed volume index is determined based on the number of closed coal mines in the candidate coal basin and the average water inflow of the mines, and the caprock sealing index is determined based on the effective thickness of the caprock, the caprock porosity and the caprock permeability of the candidate coal basin. The third type of evaluation data includes coal basin economic indicators, which are determined based on the carbon source scale and carbon source distance of the candidate coal basin.

4. The method for selecting a site for carbon dioxide geological storage according to claim 1, characterized in that, The method involves constructing an evaluation set of indicators based on Pythagorean fuzzy sets and introducing triangular fuzzy numbers to optimize membership and non-membership, thereby obtaining the comprehensive membership and comprehensive non-membership of each basin-scale standardized evaluation indicator, including: Obtain the membership degree evaluation results and non-membership degree evaluation results of multiple experts for each of the basin-scale standardized evaluation indicators; Based on the membership evaluation results and non-membership evaluation results, construct a Pythagorean fuzzy set; Based on the differences in evaluation of different evaluation indicators by the same expert and the differences in evaluation of the same evaluation indicator by different experts, the triangular fuzzy number is introduced to correct the membership degree evaluation results and non-membership degree evaluation results, so as to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation indicator.

5. The method for selecting a site for carbon dioxide geological storage according to claim 4, characterized in that, No. The expert on the first The membership and non-membership evaluation values ​​given by each evaluation indicator are respectively and And satisfy: , , ; After correction, the optimized membership degree is obtained. and optimized non-membership degree ,in: No. The comprehensive membership degree corresponding to each evaluation indicator and combined non-membership degree They are respectively: ; ; in, , indicating the expert's serial number; This indicates the total number of experts who participated in the evaluation; , indicating the evaluation indicator number; Indicates the total number of evaluation indicators; Indicates the first The expert on the first The membership evaluation value given by each evaluation indicator; Indicates the first The expert on the first The non-membership evaluation value given by each evaluation indicator; Represents the th fuzzy number after optimization. The expert on the first Membership degree of each evaluation indicator; Represents the th fuzzy number after optimization. The expert on the first Non-membership degree of each evaluation indicator; and They represent the first One expert on all The sum of the membership evaluation values ​​and the sum of the non-membership evaluation values ​​given by each evaluation indicator; and Each represents all The expert on the first The sum of the membership evaluation values ​​and the sum of the non-membership evaluation values ​​given by each evaluation indicator; Indicates the first The comprehensive membership degree corresponding to each evaluation indicator; Indicates the first The comprehensive non-membership degree corresponding to each evaluation indicator.

6. The method for selecting a site for carbon dioxide geological storage according to claim 1, characterized in that, The step involves calculating the index score of each candidate coal basin under each basin-scale standardized evaluation index based on the basin-scale standardized evaluation index, the comprehensive membership degree, and the comprehensive non-membership degree, and constructing a basin-scale decision matrix based on the index scores, including: For each basin-scale standardized evaluation index of each candidate coal basin, the standardized index value, the corresponding comprehensive membership degree, and the corresponding comprehensive non-membership degree of the basin-scale standardized evaluation index are fused to obtain the index score of the candidate coal basin under the basin-scale standardized evaluation index. Based on the correspondence between the candidate coal basins and the basin-scale standardized evaluation indicators, the multiple candidate coal basins are used as rows, the multiple basin-scale standardized evaluation indicators are used as columns, and the index scores of each candidate coal basin under each basin-scale standardized evaluation indicator are used as matrix elements to construct the basin-scale decision matrix; wherein, the basin-scale decision matrix is ​​used to characterize the comprehensive suitability level of each candidate coal basin under each basin-scale evaluation indicator.

7. The method for selecting a site for carbon dioxide geological storage according to claim 1, characterized in that, The step involves using the CRITIC method to calculate the weight of each basin-scale standardized evaluation index based on multiple candidate coal basins, and then using the VIKOR multi-attribute evaluation method to rank the multiple candidate coal basins based on the weights and the basin-scale decision matrix. The candidate coal basin with the best ranking is then determined as the target coal basin. This includes: Based on basin-scale standardized evaluation indicators of multiple candidate coal basins, the degree of fluctuation of each basin-scale standardized evaluation indicator and the degree of conflict between different basin-scale standardized evaluation indicators are determined, and the weight of each basin-scale standardized evaluation indicator is calculated according to the degree of fluctuation and the degree of conflict. Based on the weights and the basin-scale decision matrix, the VIKOR multi-attribute evaluation method is used to determine the group utility value and individual regret value of each candidate coal basin relative to the ideal evaluation result, and the compromise evaluation value of each candidate coal basin is determined based on the group utility value and the individual regret value. The candidate coal basins are ranked according to the compromise evaluation value, and the candidate coal basin with the best comprehensive ranking value is determined as the target coal basin.

8. The method for selecting a site for carbon dioxide geological storage according to claim 1 or 7, characterized in that, Before determining the carbon dioxide geological storage area, the method further includes: performing on-site sealing verification on each candidate coal mining area, and removing the corresponding candidate coal mining area when the on-site sealing discrimination index is lower than a preset sealing threshold.

9. The method for selecting a site for carbon dioxide geological storage according to claim 1, characterized in that, The set of evaluation indicators at the mining area scale includes: Obtain first evaluation data to characterize the engineering geological conditions of the candidate coal mine sealing project; Obtain secondary evaluation data to characterize the geological space available for sealing and storage in candidate coal mining areas; Obtain third-party evaluation data to characterize the long-term stability of candidate coal mine areas; Obtain fourth evaluation data to characterize the economic efficiency of sealing and construction in candidate coal mine areas; Based on the first evaluation data, the second evaluation data, the third evaluation data, and the fourth evaluation data, the set of evaluation indicators at the mining area scale is constructed. The geological condition indicators for the sealing project are determined based on the structural capacity dimension of the candidate coal mining area, the effective sealing depth, and the geostress state index. The geological space indicators for sealing and storing are determined based on the average mining thickness of the candidate coal mining area, the total area of ​​the goaf, the average height of the caving zone, the average height of the water-conducting fracture zone, the average depth of the floor failure zone, and the average coefficient of fragmentation. The long-term stability index of the sealed area is determined based on the total thickness of the mudstone layer above the water-conducting fracture zone of the roof of the candidate coal mine area, the porosity of the caprock, the permeability of the caprock, and the breakthrough pressure of the caprock. The economic indicators for sealing construction are determined based on the well injection construction cost of the candidate coal mine area, the quality of the fractured overburden rock mass in the mining disturbance space, the surface population density of the site selection area, and the surface building distribution density of the site selection area.

10. A site selection system for deep mining space carbon dioxide geological storage, characterized in that, include: The acquisition unit is used to acquire basin-scale evaluation data of multiple candidate coal basins and construct a set of basin-scale evaluation indicators, and within the target coal basin, acquire mine-scale evaluation data of multiple candidate coal mining areas and construct a set of mine-scale evaluation indicators. The processing unit is used to perform standardization processing to obtain the basin-scale standardized evaluation index of each basin-scale evaluation index in the basin-scale evaluation index set, and to construct an index evaluation set based on Pythagorean fuzzy set, and to optimize the membership degree and non-membership degree by introducing triangular fuzzy number to obtain the comprehensive membership degree and comprehensive non-membership degree of each basin-scale standardized evaluation index. Based on the basin-scale standardized evaluation index, the comprehensive membership degree and the comprehensive non-membership degree, the unit calculates the index score of each candidate coal basin under each basin-scale standardized evaluation index, and constructs a basin-scale decision matrix based on the index score. The site selection unit is used to calculate the weight of each basin-scale standardized evaluation index based on the basin-scale standardized evaluation index of multiple candidate coal basins using the CRITIC method, and to rank the multiple candidate coal basins using the VIKOR multi-attribute evaluation method based on the weight and the basin-scale decision matrix, and to determine the candidate coal basin with the best ranking as the target coal basin. It also performs standardization processing on each mining area-scale evaluation index in the mining area-scale evaluation index set, and ranks the multiple candidate coal mining areas based on Pythagorean fuzzy sets, triangular fuzzy numbers, the CRITIC method, and the VIKOR multi-attribute evaluation method to determine the carbon dioxide geological sequestration area.

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