A screening method for carbon dioxide storage geological monitoring technology based on coefficient reduction

Abstract

The application relates to the field of greenhouse gas emission reduction environmental management, and specifically discloses a carbon dioxide storage geological monitoring technology screening method based on coefficient reduction, which comprises the following steps: establishing a carbon dioxide storage monitoring technology list; carrying out fuzzy comprehensive evaluation based on layer analysis on the monitoring technologies in the carbon dioxide storage monitoring technology list to obtain general scores of the monitoring technologies; calculating project-specific scores of the monitoring technologies by using a reduction coefficient method based on monitoring requirements, site conditions and engineering conditions of a to-be-monitored project; calculating application scores of the monitoring technologies in the site by using the general scores and the project-specific scores; and screening and sorting the application scores of different monitoring technologies in the site to obtain optimal monitoring technologies. The application can be used for the preliminary screening and sorting of monitoring technologies of specific carbon storage projects, and a monitoring technology combination with low cost, high efficiency and high adaptability can be obtained.

Description

Technical Field

[0001] This application relates to the field of greenhouse gas emission reduction and environmental management, and in particular to a screening method for geological monitoring technology of carbon dioxide sequestration based on coefficient reduction. Background Technology

[0002] Carbon dioxide sequestration is an industrial process that injects carbon dioxide into the geological strata to isolate it from the atmosphere for a long period of time and / or generate incidental benefits. It is of great significance for building zero-carbon energy systems, promoting low-carbon industries, and providing negative carbon solutions.

[0003] In the process of carbon dioxide geological sequestration, geological monitoring is an effective means of carbon accounting and environmental risk management. Although my country has carried out demonstrations and applications of carbon sequestration, there is still a lack of systematic methods for screening monitoring technologies. Therefore, ranking and screening monitoring technologies based on their characteristics and adaptability to projects will yield a high-performance, low-cost technology combination, providing reliable technical support for the large-scale utilization of carbon sequestration. Summary of the Invention

[0004] In order to evaluate and prioritize various monitoring technologies for carbon dioxide sequestration and obtain low-cost, high-performance, and feasible monitoring technologies, this application provides a screening method for geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction.

[0005] The carbon dioxide sequestration geological monitoring technology screening method based on coefficient reduction provided in this application adopts the following technical solution:

[0006] A screening method for geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction includes the following steps:

[0007] Establish a list of carbon dioxide storage monitoring technologies;

[0008] A fuzzy comprehensive evaluation based on analytic hierarchy process was conducted on the monitoring technologies in the carbon dioxide storage monitoring technology list to obtain a general score for the monitoring technologies.

[0009] Based on the monitoring needs, site conditions, and engineering conditions of the project to be monitored, the project specificity score of the monitoring technology is calculated using the reduction factor method.

[0010] The application score of the monitoring technology at the site is calculated based on the general score and the project-specific score of the monitoring technology.

[0011] The application scores of different monitoring technologies at the site were used to screen and rank them to obtain the preferred monitoring technologies.

[0012] Furthermore, the monitoring technologies in the carbon dioxide storage monitoring technology list include a variety of characteristic elements, including monitoring purpose, technology maturity, coverage, reliability, accuracy, frequency, dimension, unit cost, and time required to obtain data; the monitoring purpose includes monitoring of storage volume, sealing performance, consistency, injection, and closure.

[0013] Furthermore, a method for obtaining a general score for monitoring technologies includes the following steps:

[0014] A hierarchical indicator system is established, which adopts a hierarchical structure, including a target layer, a criterion layer, and an indicator layer; the criterion layer includes a benefit layer and a cost layer, and each of the benefit layer and the cost layer contains multiple indicators, all of which constitute the indicator layer;

[0015] For a specific monitoring technology, pairwise comparisons are performed on each indicator in the benefit layer to establish an importance comparison matrix, and pairwise comparisons are also performed on each indicator in the cost layer to establish an importance comparison matrix. After performing a consistency check on the importance comparison matrices, the weight W of each indicator is calculated. m , where m is the index number;

[0016] For a specific indicator, pairwise comparisons are made between different monitoring technologies to establish an advantage comparison matrix. After performing a consistency test on the advantage comparison matrix, the score A of the indicator in different monitoring technologies is calculated. i Where i is the monitoring technology number;

[0017] Calculate the general score F of monitoring technology i i :F i =ΣW m ×A i .

[0018] Furthermore, the indicators under the benefit layer include the number of monitoring targets, technological maturity, coverage, reliability, accuracy, frequency, and dimensions, while the indicators under the cost layer include total cost and the time required to obtain data.

[0019] Furthermore, the method for calculating the item-specific score of monitoring technology using the reduction factor method includes the following steps:

[0020] Calculate the demand coefficient: Assign values ​​to the demand of each monitoring objective based on the degree of demand of the project to be monitored for different monitoring objectives; calculate the sum of the assigned values ​​for a certain monitoring technology to meet the monitoring objective requirements of the project, and obtain the demand coefficient of the monitoring technology after normalization;

[0021] Calculate the site condition adaptability coefficient: Based on the applicability of the monitoring technology to different site conditions and its application in similar site conditions, assign values ​​to the applicability of the monitoring technology to different site conditions; calculate the sum of the applicability values ​​of the monitoring technology under all site conditions, and normalize it to obtain the site condition adaptability coefficient of the monitoring technology.

[0022] Calculate the CO2 identifiability coefficient: Based on whether the monitoring technology meets the resolution and coverage requirements of the CO2 plume distribution monitoring project, assign a value to the applicability of the monitoring technology to obtain the CO2 identifiability coefficient of the monitoring technology;

[0023] Calculate the project specificity score: Calculate the project specificity score of the monitoring technology based on the demand coefficient, site condition adaptability coefficient, and CO2 identifiability coefficient of the monitoring technology.

[0024] Furthermore, the method for calculating the demand factor includes the following steps:

[0025] Assign values ​​to each monitoring objective based on the degree of need for different monitoring purposes by the project to be monitored;

[0026] Calculate the total score for a given monitoring technology in meeting the monitoring objectives of the project. Where j is the monitoring target number, This represents the demand score for monitoring objective j, where n is the total number of monitoring objectives;

[0027] The demand coefficient X for monitoring technology i i The calculation formula is:

[0028]

[0029] Where i represents the monitoring technology number, and j represents the monitoring objective number. denoted by , i represents the score of monitoring technology i satisfying monitoring objective j, and n represents the total number of monitoring objectives.

[0030] Furthermore, the method for calculating the site condition adaptation factor includes the following steps:

[0031] Based on the applicability of the monitoring technology to different site conditions, a value is assigned to the applicability of the monitoring technology to different site conditions;

[0032] Site adaptability coefficient D of monitoring technology i i The calculation formula is:

[0033]

[0034] Where i represents the monitoring technology number and j represents the site condition number. This represents the applicability score of monitoring technology i under site condition j, where n is the total number of site conditions.

[0035] Furthermore, the method for calculating the CO2 identifiability coefficient is as follows: based on whether the monitoring technology meets the resolution and coverage requirements of the CO2 plume distribution monitoring in the project to be monitored, the applicability of the monitoring technology is assigned a value, and the applicability assignment is the CO2 identifiability coefficient Ci of the monitoring technology.

[0036] Furthermore, the project-specific score T of monitoring technology i i The calculation formula is T i =X i ×D i ×C i .

[0037] Furthermore, the application score of monitoring technology in the site is S. i The calculation formula is S i =F i ×T i .

[0038] In summary, this application includes at least one of the following beneficial technical effects:

[0039] 1. This application uses the analytic hierarchy process to establish a hierarchical index system, which evaluates the general properties of monitoring technology from both cost and benefit perspectives, and helps to deepen the understanding of monitoring technology;

[0040] 2. This application conducts an adaptability assessment of the technology to the project to be monitored based on the purpose, site conditions, and project conditions, and conducts a comprehensive assessment in combination with the general characteristics of the technology. It can be used for the preliminary screening and ranking of monitoring technologies for specific carbon sequestration projects, resulting in a combination of monitoring technologies that are low-cost, efficient, and highly adaptable.

[0041] 3. The results obtained from the analytic hierarchy process and coefficient reduction method for carbon dioxide sequestration monitoring technology screening in this application can provide ideas for future carbon sequestration accounting and risk assessment, and provide guidance for enterprise project implementation. Attached Figure Description

[0042] Figure 1 This is a flowchart of an embodiment of this application;

[0043] Figure 2 This is the method implementation route in the embodiments of this application;

[0044] Figure 3 This is a schematic diagram of the hierarchical index system in the embodiments of this application;

[0045] Figure 4 This is a graph showing the general scoring results of monitoring technologies under different scenarios in the embodiments of this application. Detailed Implementation

[0046] The following is in conjunction with the appendix Figure 1-4 This application will be described in further detail.

[0047] This application discloses a method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction. (Refer to...) Figure 1 and Figure 2 The screening method for geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction includes the following steps:

[0048] S1. Establish a list of carbon dioxide storage monitoring technologies;

[0049] Specifically, the monitoring technologies listed in the carbon dioxide sequestration monitoring technology list include: injection wells, observation wells, groundwater observation wells, cement sheath recording, time-lapse ultrasonic casing imaging, time-lapse electromagnetic emission casing imaging, time-lapse multi-wall caliper, annular pressure monitoring, injection rate measurement, wellhead pressure and temperature measuring instruments, operational integrity assurance systems, bottom hole pressure and temperature measuring instruments, mechanical wellbore integrity pressure testing, wellhead CO2 detectors, tracer injection, gamma logging, time-lapse saturation logging, time-lapse temperature logging, time-lapse circulation noise logging, time-lapse density logging, time-lapse acoustic logging, fiber-optic distributed temperature logging, fiber-optic distributed pressure logging, real-time casing imaging, fiber-optic distributed acoustic logging, pressure interference testing, pressure drop testing, water chemistry monitoring, bottom hole conductivity monitoring, bottom hole pH monitoring, artificial tracer monitoring, and natural tracer monitoring. U-tube fluid sampling, isotope fluid sampling, groundwater gas composition analysis, soil CO2 gas flux detection, soil gas concentration monitoring, soil pH survey, soil salinity survey, time-shifted vertical seismic profile, time-shifted three-dimensional surface seismic, time-shifted two-dimensional surface seismic, time-shifted well-to-well seismic, surface microseismic monitoring, well bottom microseismic monitoring, time-shifted surface microgravity survey, time-shifted well bottom microgravity survey, time-shifted controlled-source electromagnetic emission from the surface, magnetotelluric method, time-shifted controlled-source electromagnetic emission from wells, InSAR synthetic aperture radar interferometry, GPS global positioning system, surface inclinometer, well bottom inclinometer, dual-differential absorption lidar, linear back-to-back gas flux measurement, atmospheric eddy covariance method, airborne infrared laser gas analyzer, handheld infrared laser gas analyzer, satellite, airborne multispectral imaging analyzer, ecosystem research.

[0050] Furthermore, the monitoring technologies in the list of carbon dioxide storage monitoring technologies include a variety of characteristic elements, including monitoring purpose, technology maturity, coverage, reliability, accuracy, frequency, dimensions, unit cost, and time required to obtain data; specifically, the monitoring purpose includes monitoring of storage volume, sealing performance, consistency, injection, and closure.

[0051] Among them, the monitoring of the sealed volume includes monitoring the injection pressure of each well, monitoring the injection rate of each well, monitoring the injection volume of each well, and monitoring the total injection volume.

[0052] Sealing monitoring includes monitoring the migration of CO2 or saline water along abandoned wells, monitoring the migration of CO2 or saline water along monitoring wells, monitoring the migration of CO2 or saline water along injection wells, monitoring the migration of CO2 or saline water along simulated paths, monitoring the migration of CO2 or saline water along fault paths, monitoring fault activation, monitoring fracture activation, and monitoring the migration of CO2 or saline water caused by third-party activities.

[0053] Consistency monitoring includes monitoring CO2 migration in the reservoir and monitoring pressure migration in the reservoir.

[0054] Injection monitoring includes monitoring the injection pressure and injection rate of each well.

[0055] Closed-loop monitoring includes monitoring changes in CO2 transport, monitoring whether CO2 will leak into seawater, monitoring the impact of CO2 on seawater properties, and monitoring the impact of CO2 on marine biological communities.

[0056] The list of carbon dioxide sequestration monitoring technologies established in this embodiment is shown in Table 1. "√" indicates that the monitoring technology can meet the corresponding monitoring purpose. Table 1 only selects some monitoring technologies (time-lapse three-dimensional surface seismic, time-lapse two-dimensional surface seismic, time-lapse vertical seismic profile, well bottom microseismic monitoring, time-lapse surface microgravity survey, and time-lapse surface controlled source electromagnetic emission) as application descriptions of the method, and does not include all monitoring technologies.

[0057] Table 1. List of Monitoring Technologies (Partial)

[0058]

[0059] S2. Conduct a fuzzy comprehensive evaluation based on analytic hierarchy process (AHP) for the monitoring technologies listed in the carbon dioxide sequestration monitoring technology list to obtain a general score for the monitoring technologies, as follows:

[0060] S2-1. Establish a hierarchical indicator system;

[0061] like Figure 3 As shown, the hierarchical indicator system adopts a hierarchical structure, including the target layer, the criterion layer, and the indicator layer. The criterion layer includes the benefit layer and the cost layer, each containing multiple indicators, and all indicators constitute the indicator layer. Specifically, the indicators under the benefit layer include the number of monitoring objectives, technological maturity, coverage, reliability, accuracy, frequency, and dimensions, while the indicators under the cost layer include total cost and the time required to obtain data.

[0062] S2-2. For a given monitoring technology, pairwise comparisons are performed on costs and benefits in the criterion layer to establish an importance comparison matrix; pairwise comparisons are also performed on each indicator in the benefit layer to establish an importance comparison matrix; and pairwise comparisons are also performed on each indicator in the cost layer to establish an importance comparison matrix. After performing a consistency check on the importance comparison matrices, the largest eigenvalue and the corresponding eigenvector of the importance comparison matrix are calculated. The obtained eigenvectors are then normalized column-wise to obtain the weight W of each indicator. m Where m is the index number; the specific method is as follows:

[0063] Importance comparisons were performed using Saaty's 1-9 scale, as shown in Table 2:

[0064] Table 2. Importance Reference Table for Scale 1-9

[0065]

[0066] For the criteria layer, as shown in Table 3, different scenarios can be designed for evaluation based on different levels of importance, such as the benefit-first scenario (X=1 / 9), the cost-first scenario (X=9), and the cost-benefit balance scenario (X=1).

[0067] Table 3. Importance Comparison Matrix of Criterion Layer

[0068]

[0069] Taking the various indicators under the benefit layer as examples, the importance comparison matrix is ​​shown in Table 4:

[0070] Table 4. Importance Comparison Matrix of Benefit Layer

[0071]

[0072] The method for performing consistency checks on the importance comparison matrix is ​​as follows:

[0073] Calculate the consistency index ,in, is the largest eigenvalue of the importance comparison matrix, and n is the number of evaluation indicators;

[0074] Find the corresponding average random consistency index RI (Table 5):

[0075] Table 5. Average Random Consistency Index (RI)

[0076]

[0077] Calculate the consistency ratio ,if If the value is less than 0.1, the consistency of the importance comparison matrix is ​​considered acceptable; otherwise, the importance comparison matrix needs to be modified.

[0078] A consistency test was performed on the importance comparison matrix of each indicator under the benefit level in Table 4, and λ was calculated. max =7.2327, CR=0.0285<0.1, the consistency test is acceptable.

[0079] Calculate the maximum eigenvalue and corresponding eigenvector of the importance comparison matrix of each indicator under the benefit layer in Table 4. Normalize the obtained eigenvectors column-wise to obtain the weight W of each indicator. m As shown in Table 6:

[0080] Table 6. Weights W of each indicator under the benefit layer m

[0081]

[0082] S2-3. For a specific indicator, conduct pairwise comparisons of different monitoring technologies and establish an advantage comparison matrix. After performing a consistency test on the advantage comparison matrix, calculate the score A of the indicator across different monitoring technologies. i Where i represents the monitoring technology number; the specific method is as follows:

[0083] Taking the quantitative indicators of monitoring objectives as an example, the advantages of different monitoring technologies for this indicator are determined, as shown in Table 7, using Saaty's 1-9 scale method:

[0084] Table 7 Comparison Matrix of the Advantages of Quantitative Indicators for Monitoring Objectives

[0085]

[0086] λ is calculated max =6.5074, CR=0.0805<0.1, which meets the consistency test.

[0087] Calculate the largest eigenvalue and the corresponding eigenvector of the advantage comparison matrix of the quantitative indicators of the monitoring objectives in Table 7. Normalize the obtained eigenvectors column-wise to obtain the scores A of the quantitative indicators of the monitoring objectives in different monitoring technologies. i As shown in Table 8:

[0088] Table 8 Scores of Quantitative Indicators of Monitoring Objectives in Different Monitoring Technologies (A) i

[0089]

[0090] S2-4, Calculate the general score F of monitoring technology i. i :F i =ΣW m ×A i , Figure 4The general scores of each monitoring technology are presented under three scenarios: benefit-first, cost-first, and benefit-cost balance.

[0091] S3. Based on the monitoring needs, site conditions, and engineering conditions of the project to be monitored, the project specificity score of the monitoring technology is calculated using the reduction factor method, as follows:

[0092] S3-1. Calculate the demand factor:

[0093] S3-1-1. Assign values ​​of 1-5 to each monitoring objective based on the degree of need for different monitoring objectives of the project to be monitored, from low to high.

[0094] S3-1-2 Calculate the total score for a monitoring technology that meets the monitoring objectives of the project. Where j is the monitoring target number, This represents the demand score for monitoring objective j, where n is the total number of monitoring objectives;

[0095] S3-1-3. After normalization, the demand coefficient X of this monitoring technology is obtained. i :

[0096]

[0097] Where i represents the monitoring technology number, and j represents the monitoring objective number. denoted by , i represents the score of monitoring technology i satisfying monitoring objective j, and n represents the total number of monitoring objectives.

[0098] The results of the demand coefficient calculation are shown in Table 9:

[0099] Table 9 Demand Coefficient Calculation Table

[0100]

[0101] Note: Monitoring needs are assigned values ​​from 1 to 5, from low to high: 1 - very low, 2 - low, 3 - medium, 4 - high, and 5 - very high.

[0102] S3-2, Calculate the site condition adaptability coefficient:

[0103] S3-2-1. Based on the applicability of the monitoring technology to different site conditions and its application in similar site conditions, assign values ​​to the applicability of the monitoring technology to different site conditions, as follows:

[0104] When the site conditions do not meet the applicable requirements of the monitoring technology, the applicability of the monitoring technology under the site conditions is assigned a value of 0; when the site conditions meet the applicable requirements of the monitoring technology, the applicability of the monitoring technology under the site conditions is assigned a value of 1.

[0105] When determining whether site conditions meet the applicability requirements of monitoring technology, a similar case comparison method can be used. If the monitoring technology has been applied in similar site conditions with good results, then the site conditions are considered to meet the applicability requirements of the monitoring technology, and the applicability of the monitoring technology in the site conditions is assigned a value of 1.

[0106] S3-2-2. Calculate the sum of the applicability values ​​of this monitoring technology under all site conditions, and obtain the site condition adaptability coefficient D of the monitoring technology after normalization. i :

[0107]

[0108] Where i represents the monitoring technology number and j represents the site condition number. This represents the applicability score of monitoring technology i under site condition j, where n is the total number of site conditions.

[0109] In this embodiment, n=12, and the 12 site conditions include: onshore / offshore, topography, land use type, seawater depth, reservoir depth, thickness, chemical characteristics, porosity, permeability, formation pressure, overlying strata characteristics, and fault characteristics.

[0110] The site condition adaptability coefficient D of different monitoring technologies was calculated. i The scores are shown in Table 10:

[0111] Table 10 Site adaptability coefficient D for different monitoring technologies i Score

[0112]

[0113] S3-3, Calculate the CO2 identifiability coefficient:

[0114] The applicability of the monitoring technology is assigned a value based on whether it meets the resolution and coverage requirements for CO2 plume distribution monitoring in the project to be monitored, as follows:

[0115] When a monitoring technology simultaneously meets the resolution and coverage requirements of CO2 plume distribution monitoring in the project to be monitored, the applicability of the monitoring technology is assigned a value of 1 (applicable).

[0116] When the monitoring technology meets the resolution or coverage requirements of the CO2 plume distribution monitoring in the project to be monitored, the applicability of the monitoring technology is assigned a value of 0.5 (partially applicable).

[0117] If the monitoring technology does not meet the resolution and coverage requirements of the CO2 plume distribution monitoring in the project to be monitored, the applicability of the monitoring technology is assigned to 0 (not applicable).

[0118] The applicability assignment is the CO2 identifiability coefficient Ci of this monitoring technology.

[0119] Taking a small-scale pilot monitoring project as an example, its maximum horizontal sweep radius of the CO2 plume throughout its entire life cycle is approximately 2 km, and its vertical thickness is approximately 5 meters. Based on this, the CO2 identifiability coefficient C of each monitoring technology can be obtained. i As shown in Table 11.

[0120] Table 11 CO2 Identifiability Coefficient

[0121]

[0122] S3-4. Calculate the project specificity score: based on the demand coefficient X of the monitoring technology. i Site adaptability coefficient D i And CO2 identifiability coefficient C i Calculate the project specificity score T for this monitoring technology. i The calculation formula is T i =X i ×D i ×C i .

[0123] In this embodiment, the item-specific score T for each monitoring technology i As shown in Table 12:

[0124] Table 12 Item Specificity Scores (T) for Each Monitoring Technology i calculate

[0125]

[0126] S4. Based on the general scoring F of monitoring technology i Project-specific score T i The application score S of the monitoring technology in the site was calculated. i The calculation formula is S i =F i ×T i .

[0127] In this embodiment, the application score S of each monitoring technology on the site i As shown in Table 13:

[0128] Table 13 Score for the application of each monitoring technology at the site (S) i

[0129]

[0130] S5. The application scores of different monitoring technologies in the site are screened and ranked, as shown in Table 14, to obtain the preferred monitoring technologies.

[0131] Table 14 Ranking of the application of different monitoring technologies in the site

[0132]

[0133] Based on the above ranking, it can be concluded that under the scenarios of prioritizing benefits, prioritizing costs, and balancing benefits and costs, time-lapse three-dimensional surface seismic, time-lapse two-dimensional surface seismic, and time-lapse controlled-source electromagnetic emission from the Earth's surface are ranked higher and are the preferred monitoring technologies.

[0134] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction, characterized in that: Includes the following steps: Establish a list of carbon dioxide storage monitoring technologies; A fuzzy comprehensive evaluation based on analytic hierarchy process (AHP) is conducted on the monitoring technologies listed in the carbon dioxide sequestration monitoring technology inventory to obtain a general score for each technology. The evaluation includes the following steps: establishing a hierarchical index system, which adopts a hierarchical structure including a target layer, a criterion layer, and an indicator layer; the criterion layer includes a benefit layer and a cost layer, each containing multiple indicators, with all indicators forming the indicator layer; for a specific monitoring technology, pairwise comparisons are performed on each indicator in the benefit layer to establish an importance comparison matrix, and pairwise comparisons are also performed on each indicator in the cost layer to establish an importance comparison matrix; after a consistency check of the importance comparison matrices, the weight W of each indicator is calculated. m Where m is the indicator number; for a given indicator, pairwise comparisons are made between different monitoring technologies to establish an advantage comparison matrix. After performing a consistency check on the advantage comparison matrix, the score A of the indicator in different monitoring technologies is calculated. i Where i is the monitoring technology number; calculate the general score F for monitoring technology i. i :F i =ΣW m ×A i ; Based on the monitoring needs, site conditions, and engineering conditions of the project to be monitored, a project-specific score for the monitoring technology is calculated using the reduction factor method. The reduction factor method includes calculating a requirement coefficient X, which characterizes the degree to which the monitoring technology meets the project's monitoring needs. i Calculate the site condition adaptability coefficient D, which characterizes the degree to which the monitoring technology adapts to the site conditions. i And the CO2 identifiability coefficient C, which is used to characterize and monitor the ability of CO2 plume to be identified. i The project-specific score T i From the demand coefficient X i Site adaptability coefficient D i And CO2 identifiability coefficient C i Multiplying them together gives us T. i = X i ×D i ×C i ; The general score F of the monitoring technology i Project Specificity Score T i Multiply by the product to obtain the application score S of the monitoring technology at the site. i S i =F i ×T i ; Score for the application of different monitoring technologies at the site i The optimal monitoring technology is obtained by screening and sorting.

2. The method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction according to claim 1, characterized in that: The monitoring technologies in the list of carbon dioxide storage monitoring technologies include a variety of characteristic elements, including monitoring purpose, technology maturity, coverage, reliability, accuracy, frequency, dimension, unit cost, and time required to obtain data; the monitoring purpose includes monitoring the amount of carbon dioxide stored, monitoring the sealing performance, monitoring the consistency, monitoring the injection, and monitoring the closure.

3. The method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction according to claim 1, characterized in that: The indicators under the benefit layer include the number of monitoring targets, technological maturity, coverage, reliability, accuracy, frequency, and dimensions. The indicators under the cost layer include total cost and the time required to obtain data.

4. The method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction according to claim 3, characterized in that: The method for calculating the item-specific score of monitoring technology using the reduction factor method includes the following steps: Calculate the demand coefficient: Assign values ​​to the demand of each monitoring objective based on the degree of demand of the project to be monitored for different monitoring objectives; calculate the sum of the assigned values ​​for a certain monitoring technology to meet the monitoring objective requirements of the project, and obtain the demand coefficient of the monitoring technology after normalization; Calculate the site condition adaptability coefficient: Based on the applicability of the monitoring technology to different site conditions and its application in similar site conditions, assign values ​​to the applicability of the monitoring technology to different site conditions; calculate the sum of the applicability values ​​of the monitoring technology under all site conditions, and normalize it to obtain the site condition adaptability coefficient of the monitoring technology. Calculate the CO2 identifiability coefficient: Based on whether the monitoring technology meets the resolution and coverage requirements of the CO2 plume distribution monitoring project, assign a value to the applicability of the monitoring technology to obtain the CO2 identifiability coefficient of the monitoring technology; Calculate the project specificity score: Calculate the project specificity score of the monitoring technology based on the demand coefficient, site condition adaptability coefficient, and CO2 identifiability coefficient of the monitoring technology.

5. The method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction according to claim 4, characterized in that: The method for calculating the demand factor includes the following steps: Based on the degree of need for different monitoring objectives by the project to be monitored, assign values ​​to the needs of each monitoring objective; Calculate the total score for a given monitoring technology in meeting the monitoring objectives of the project. Where j is the monitoring target number, This represents the demand score for monitoring objective j, where n is the total number of monitoring objectives; The demand coefficient X for monitoring technology i i The calculation formula is: Where i represents the monitoring technology number, and j represents the monitoring objective number. denoted by , i represents the score of monitoring technology i satisfying monitoring objective j, and n represents the total number of monitoring objectives.

6. The method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction according to claim 5, characterized in that: The method for calculating the site condition adaptability factor includes the following steps: Based on the applicability of the monitoring technology to different site conditions, a value is assigned to the applicability of the monitoring technology to different site conditions; Site adaptability coefficient D of monitoring technology i i The calculation formula is: Where i represents the monitoring technology number and j represents the site condition number. This represents the suitability score of monitoring technology i for site condition j, where n is the total number of site conditions.

7. The method for screening geological monitoring technologies for carbon dioxide sequestration based on coefficient reduction according to claim 6, characterized in that: The method for calculating the CO2 identifiability coefficient is as follows: Based on whether the monitoring technology meets the resolution and coverage requirements of the CO2 plume distribution monitoring project, an applicability value is assigned to the monitoring technology. This applicability value is the CO2 identifiability coefficient C of the monitoring technology. i .

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