A heterogeneous paste rock cap layer sealing performance coupling evaluation method and system thereof
By combining the analytic hierarchy process (AHP), entropy weight method, and coefficient of variation method to calculate weights, a performance evaluation system for the sealing of heterogeneous gypsum caprock is constructed. This solves the problem of evaluation result bias in existing technologies, achieves a more scientific and objective evaluation of sealing performance, and supports the safe operation of gas storage facilities.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SOUTHWEST PETROLEUM UNIV
- Filing Date
- 2026-05-18
- Publication Date
- 2026-07-21
AI Technical Summary
In existing technologies, there is a lack of systematic and quantitative evaluation methods for the sealing performance of heterogeneous gypsum caprock. Traditional methods are mostly based on a single factor, which leads to biased evaluation results and makes it difficult to comprehensively consider the influence of multiple factors such as mechanical properties, physical properties and mineral composition parameters.
By combining the analytic hierarchy process (AHP), entropy weighting method, and coefficient of variation method, the weights of evaluation indicators are calculated through multiple weighting methods, and dynamic adjustment of undetermined weight coefficients is introduced to construct a coupled evaluation system for the sealing performance of heterogeneous gypsum caprock, including an indicator hierarchical structure system, weight calculation, and sealing performance grading index.
This improves the objectivity and scientific rigor of the evaluation, reduces subjectivity, and provides a systematic method to comprehensively evaluate the sealing performance of heterogeneous gypsum caprock, supporting the safe operation of gas storage facilities.
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Abstract
Description
Technical Field
[0001] This invention relates to the field of caprock sealing performance evaluation technology, specifically to a coupled evaluation method and system for the sealing performance of heterogeneous gypsum caprock. Background Technology
[0002] Evaluation of caprock sealing performance is crucial for the long-term safe operation of gas storage facilities. Currently, research on the sealing performance of heterogeneous gypsum caprock during the long-term operation of underground gas storage facilities is relatively lacking. Therefore, there is an urgent need to establish a scientific and systematic coupled evaluation method and system for the sealing performance of heterogeneous gypsum caprock to ensure the long-term safe operation of gas storage facilities.
[0003] The sealing performance of the caprock is affected by a combination of factors. Traditional evaluation methods are mostly based on a single influencing factor to evaluate the sealing performance of the caprock. Although they can obtain certain evaluation results, the evaluation methods have poor universality and certain limitations.
[0004] In existing technologies, the evaluation of the sealing performance of gas storage caprocks relies heavily on empirical judgment and qualitative analysis, lacking systematic and quantitative assessment methods. Existing evaluation methods struggle to comprehensively consider multiple factors such as mechanical properties, physical characteristics, and mineral composition parameters. Furthermore, the selection of evaluation indicators and the determination of their weights often lack unified standards and scientific methods, potentially leading to biased evaluation results. Summary of the Invention
[0005] To address the aforementioned technical problems, this invention proposes a coupled evaluation method and system for the sealing performance of heterogeneous gypsum caprock.
[0006] This invention is achieved through the following technical solution:
[0007] A coupled evaluation method for the sealing performance of heterogeneous gypsum caprock includes:
[0008] Multiple characteristic parameters of heterogeneous gypsum caprock in the study area were obtained, and a hierarchical index system for coupled evaluation of caprock sealing performance was constructed based on the characteristic parameters.
[0009] The weights of each evaluation index in the hierarchical structure system of the index are calculated using at least three weighting methods to obtain at least three basic weights.
[0010] At least three of the aforementioned basic weights are coupled to obtain the coupled weights for each evaluation index;
[0011] Based on the coupling weights, a grading index for closure performance is calculated, and the grading index is used to evaluate and classify the closure performance of the cap layer in the study area.
[0012] As an optimization, the multi-type characteristic parameters include mechanical property parameters, physical property parameters, and mineral composition parameters.
[0013] As an optimization, the mechanical property parameters include uniaxial compressive strength, elastic modulus, and Poisson's ratio; the physical property parameters include permeability and the degree of pore and fracture development; the mineral composition parameters include gypsum content and crystal morphology; and the evaluation indicators include uniaxial compressive strength, elastic modulus, Poisson's ratio, permeability, the degree of pore and fracture development, gypsum content, and crystal morphology.
[0014] As an optimization, at least three weighting methods are used, including the analytic hierarchy process (AHP), the entropy weight method, and the coefficient of variation method. Among them, the AHP is used to obtain the subjective weight of the evaluation index, the entropy weight method is used to obtain the first objective weight of the evaluation index, and the coefficient of variation method is used to obtain the second objective weight of the evaluation index.
[0015] As an optimization, the process of analyzing the hierarchical structure of the indicators using the Analytic Hierarchy Process (AHP) includes:
[0016] Based on the aforementioned hierarchical structure of indicators, a judgment matrix is constructed;
[0017] The judgment matrix is calculated using the sum-product method to obtain the weights of each level of indicators, and the consistency of the judgment matrix is checked to finally obtain the subjective weights of the evaluation indicators.
[0018] As an optimization, the process of calculating the hierarchical structure of the indicators using the entropy weight method includes:
[0019] Normalization was used to obtain the entropy value and difference coefficient of the evaluation index;
[0020] The first objective weight is calculated based on the index entropy value.
[0021] As an optimization, the process of calculating the hierarchical structure of the indicators using the coefficient of variation method includes:
[0022] The coefficient of variation of the evaluation indicators is calculated using the standard deviation and mean of the evaluation indicators.
[0023] The second objective weight is calculated based on the coefficient of variation of the evaluation index.
[0024] As an optimization, the process of coupling the at least three basic weights to obtain the coupled weights of each evaluation index includes:
[0025] The subjective weight, the first objective weight, and the second objective weight are coupled using a linear weighting method to obtain the coupled weight. During the linear weighting, the undetermined coefficients of the subjective weight, the first objective weight, and the second objective weight are dynamically adjusted.
[0026] As an optimization, the process of calculating the blocking performance grading index includes:
[0027] The evaluation indicators are scored based on the comprehensive discrimination method of influencing factors to obtain indicator scores;
[0028] Based on the index score and the coupling weight, the blocking performance grading index is calculated;
[0029] The higher the sealing performance grading index, the better the sealing performance.
[0030] This invention also discloses a coupled evaluation method for the sealing performance of heterogeneous gypsum caprock, used to implement the aforementioned coupled evaluation method for the sealing performance of heterogeneous gypsum caprock, the system comprising:
[0031] The indicator system construction module is used to obtain multi-type characteristic parameters of the cap layer in the study area and construct an indicator hierarchical structure system for evaluating the cap layer's sealing performance.
[0032] Multiple weight calculation modules are used to calculate the weight of each evaluation index using at least three weighting methods to obtain at least three basic weights;
[0033] Multiple weight coupling modules are used to couple at least three of the basic weights to obtain the coupled weights of each evaluation index;
[0034] The evaluation module is used to calculate the blocking performance grading index based on the coupling weights, and to evaluate and grade the blocking performance of the cap layer in the study area.
[0035] Compared with the prior art, the present invention has the following advantages and beneficial effects:
[0036] This invention innovatively combines at least three weighting methods (analytic hierarchy process, entropy weighting, and coefficient of variation method) to obtain the weights of evaluation indicators through coupled analysis. It also introduces a dynamic adjustment method for the undetermined weight coefficients, enabling the weight allocation to adaptively change with the characteristics of the sample data, significantly reducing subjectivity and improving the objectivity and scientific rigor of the evaluation. Furthermore, this invention proposes a Pitting Performance Grading Index (SPI) for comprehensively evaluating the blocking performance level of heterogeneous gypsum caprock strata. The application of this evaluation system can provide important technical support for the safe operation and maintenance of gas storage facilities in heterogeneous gypsum caprock strata. Attached Figure Description
[0037] The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and form part of this application, do not constitute a limitation thereof. In the drawings:
[0038] Figure 1 This is a schematic diagram of the hierarchical structure of the evaluation indicators in an embodiment of the present invention. Detailed Implementation
[0039] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.
[0040] This embodiment 1 provides a coupled evaluation method for the sealing performance of heterogeneous gypsum caprock, including:
[0041] S1. Obtain multi-type characteristic parameters of heterogeneous gypsum caprock in the study area, and construct a hierarchical index structure system for coupled evaluation of caprock sealing performance based on the characteristic parameters.
[0042] The mechanical properties, physical characteristics, and mineral composition parameters of the heterogeneous gypsum caprock in the study area were obtained through uniaxial compression tests, triaxial compression tests, triaxial creep tests, thin section identification, SEM-EDS analysis, rock CT analysis, and permeability testing.
[0043] Among them, mechanical property parameters include uniaxial compressive strength, elastic modulus and Poisson's ratio; physical property parameters include permeability and degree of pore and fracture development; mineral composition parameters include gypsum content and crystal morphology.
[0044] Specifically, uniaxial compressive strength is the most direct manifestation of the mechanical properties of rock, and its brittleness and ductility can be evaluated based on it. Higher uniaxial compressive strength means the rock is less prone to macroscopic failure under a given stress level, but its brittleness also increases with increasing uniaxial compressive strength. Brittle rocks, once fractured, are prone to forming macroscopic fracture surfaces, which is detrimental to natural gas sealing. Conversely, lower uniaxial compressive strength indicates stronger ductility; under a given stress level, the rock is more prone to plastic deformation and less likely to form macroscopic fracture surfaces, which is beneficial for natural gas sealing. Elastic modulus is an indicator of a rock's resistance to elastic deformation. Brittle rocks have a high elastic modulus and high stiffness, making them less prone to significant deformation under a given stress level, instead undergoing brittle fracture. Ductile rocks have a low elastic modulus and low stiffness, making them prone to significant deformation under a given stress level without immediate fracture. Poisson's ratio is an elastic constant reflecting the lateral deformation of a rock, and it has a certain conversion relationship with the elastic modulus, reflecting the rock's elastic deformation performance. Brittle rocks have a low Poisson's ratio and are less prone to lateral deformation under a certain stress level, while ductile rocks have a high Poisson's ratio and are more prone to lateral deformation under a certain stress level. Permeability reflects the rock's ability to allow fluids to pass through and is a direct physical property parameter that directly affects the sealing performance of gypsum caprock in gas storage facilities. The lower the permeability, the better the sealing performance of the rock. The degree of pore and fracture development reflects the dominant seepage channels within the rock. The presence of dominant seepage channels will greatly reduce the rock's sealing performance. The weaker the pore and fracture development, the better the rock's sealing performance; the stronger the pore and fracture development, the worse the rock's sealing performance. The volumetric strain of the sample after the confining pressure loading in the triaxial creep test is a direct reflection of the degree of pore and fracture development. The smaller the volumetric strain of the sample, the weaker the pore and fracture development; the larger the volumetric strain, the stronger the pore and fracture development. The higher the gypsum content, the stronger the rock's plasticity and the lower its strength. Under a certain stress level, the rock is more prone to plastic deformation and less likely to fracture brittlely. Platy and slab-like crystals have the lowest stiffness and are extremely prone to flexural deformation under stress, exhibiting the strongest plasticity. Columnar, long columnar, and slab-columnar crystals have moderate stiffness and can flex under stress, but with a small degree of flexural deformation, exhibiting moderate plasticity. Microparticle and granular columnar crystals have the highest stiffness and hardly undergo significant flexural deformation under stress, exhibiting the weakest plasticity. In this embodiment, the evaluation indicators include: uniaxial compressive strength, elastic modulus, Poisson's ratio, permeability, degree of pore and fracture development, gypsum content, and crystal morphology. By classifying the evaluation indicators for the sealing performance of heterogeneous gypsum rock caprock, mechanical properties, physical properties, and mineral composition are divided into three main influencing factors. The hierarchical system of evaluation indicators is shown in Table 1.
[0045] Table 1
[0046]
[0047] The sealing performance of heterogeneous gypsum caprock is mainly determined by the seven influencing factors mentioned above. The contribution of each influencing factor to the graded evaluation varies greatly, and the influence of the same influencing factor on the evaluation results can also vary greatly under different conditions. Therefore, the indicators are classified into four levels according to their degree of harm, from high to low. The grading standards for the evaluation indicators are shown in Table 2.
[0048] Table 2
[0049]
[0050] Based on the above parameters, a hierarchical index structure system for coupled evaluation of the sealing performance of heterogeneous gypsum caprock is constructed. In this embodiment, the evaluation index includes: uniaxial compressive strength (…). ), elastic modulus ( Poisson's ratio ), penetration rate ( ), degree of pore and fracture development ( ), gypsum content ( ) and crystal morphology ( Its hierarchical structure is as follows: Figure 1 As shown.
[0051] S2. Calculate the weights of each evaluation index in the hierarchical structure system of the index using at least three weighting methods to obtain at least three basic weights.
[0052] In some embodiments, at least three weighting methods include the analytic hierarchy process (AHP), the entropy weight method, and the coefficient of variation method; wherein the subjective weight of the evaluation index is obtained using the AHP, the first objective weight of the evaluation index is obtained using the entropy weight method, and the second objective weight of the evaluation index is obtained using the coefficient of variation method.
[0053] Next, we will explain in detail the process of obtaining each weight.
[0054] S2.1 The process of analyzing the hierarchical structure of the indicators using the Analytic Hierarchy Process (AHP) includes:
[0055] Based on the aforementioned hierarchical structure of indicators, a judgment matrix is constructed;
[0056] The judgment matrix is calculated using the sum-product method to obtain the weights of each level of indicators, and the consistency of the judgment matrix is checked to finally obtain the subjective weights of the evaluation indicators.
[0057] After constructing the hierarchical structure of indicators, starting from the top level and using the elements of the previous level as a basis, the importance of each element in the current level is compared pairwise from top to bottom to establish a judgment matrix, which takes the following form:
[0058]
[0059] Among them, a ij The scale representing the relative importance between indicators is determined by the 1-9 scale method proposed by TLSaaty. The relative importance scaling method is shown in Table 3.
[0060] Table 3
[0061]
[0062] The judgment matrix is calculated using the sum-product method to solve for the weight vector, and a consistency check is performed on the judgment matrix. According to matrix theory, if the judgment matrix has complete consistency, its largest eigenvalue is the same as the matrix order, i.e., λ. max =n. When the consistency evaluation of the judgment matrix is not satisfied, i.e., λ max If the value is ≠ n, it indicates poor consistency of the judgment matrix, thus requiring the introduction of a consistency index (CI).
[0063]
[0064] Introducing the random consistency ratio (CR):
[0065]
[0066] In the formula: RI is the average random consistency index. The average random consistency index of matrices of order 1 to 10 can be obtained from the lookup table, as shown in Table 4.
[0067] Table 4
[0068] order 1 2 3 4 5 6 7 8 9 10 RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49
[0069] If CR < 0.1, the judgment matrix is considered to have satisfactory consistency; otherwise, the judgment matrix needs to be adjusted until it has satisfactory consistency.
[0070] Based on the hierarchical relationship of the evaluation indicators, the relative importance of the indicators is determined by the 1-9 scale method, and the first-level indicators are established as shown in Table 5, the mechanical property indicator judgment matrix is shown in Table 6, the physical property indicator judgment matrix is shown in Table 7, and the mineral composition indicator judgment matrix is shown in Table 8.
[0071] Table 5
[0072] Primary indicators <![CDATA[Mechanical property U1]]> <![CDATA[Physical property feature U2]]> <![CDATA[Mineral composition U3]]> <![CDATA[Mechanical property U1]]> 1 1 2 <![CDATA[Physical property feature U2]]> 1 1 2 <![CDATA[Mineral composition U3]]> 1 / 2 1 / 2 1
[0073] Table 6
[0074] Secondary indicators <![CDATA[Uniaxial compressive strength U 11 > <![CDATA[Modulus of Elasticity U 12 > <![CDATA[Poisson's ratio U 13 > <![CDATA[Uniaxial compressive strength U 11 > 1 3 5 <![CDATA[Modulus of Elasticity U 12 > 1 / 3 1 3 <![CDATA[Poisson's ratio U 13 > 1 / 5 1 / 3 1
[0075] Table 7
[0076] Secondary indicators <![CDATA[Permeability U 21 > <![CDATA[Degree of pore and fracture development U 22 > <![CDATA[Permeability U 21 > 1 1 <![CDATA[Degree of pore and fracture development U 22 > 1 1
[0077] Table 8
[0078] Secondary indicators <![CDATA[Gypsum content U 31 > <![CDATA[Crystal form U 32 > <![CDATA[Gypsum content U 31 > 1 1 / 2 <![CDATA[Crystal form U 32 > 2 1
[0079] The weights of each level of index were calculated using the sum-product method and CR test was performed to obtain the final weights. The weight calculation and test tables for the first-level index weights, the mechanical property index weights, the physical property index weights, the mineral composition index weights, and the comprehensive table of index weight allocation calculated by the analytic hierarchy process are shown in Tables 9 to 13, respectively.
[0080] Table 9
[0081]
[0082] Table 10
[0083]
[0084] Table 11
[0085]
[0086] Table 12
[0087]
[0088] Table 13
[0089]
[0090] S2.2 The process of calculating the hierarchical structure of the index using the entropy weight method includes:
[0091] Normalization was used to obtain the entropy value and difference coefficient of the evaluation index;
[0092] The first objective weight is calculated based on the index entropy value.
[0093] In this embodiment, the Entropy Weight Method (EWM) is an objective weighting method. Its basic idea is to use entropy values to describe the dispersion of a factor. The greater the dispersion, the greater the weight of the factor, which can reduce the influence of subjectivity on the evaluation results. The specific steps for calculating the index weights using the Entropy Weight Method are as follows:
[0094] (1) Form a judgment matrix.
[0095] If there are m objects participating in the evaluation, and each object has n indicators to be evaluated, let r be the j-th evaluation indicator of the i-th object. ij Then the judgment matrix R of the original data is (r ij )m×n (i=1, 2,…,m; j=1, 2,…,n):
[0096]
[0097] (2) Standardized judgment matrix.
[0098] To eliminate the influence of different dimensions of the evaluation indicators on the evaluation results, the judgment matrix needs to be standardized, ultimately forming a standardized judgment matrix X=(x ij ) m×n (i=1, 2, ..., m; j=1, 2, ..., n). Based on the nature of different indicators, appropriate standardization methods are adopted:
[0099] Higher is better efficiency indicators:
[0100]
[0101] Cost metrics that are smaller are better:
[0102]
[0103] In the formula: x ij For r ij Normalized value, 0≤x ij ≤1; max(r) j ) represents the maximum value of the j-th index; min(r) j ) represents the minimum value of the j-th index.
[0104] (3) Calculate the characteristic weight p of the j-th indicator of object i. ij Since 0≤x ij ≤1, therefore 0≤p ij ≤1.
[0105]
[0106] (4) Calculate the entropy value e of the j-th evaluation index. j When p ij When =0 or 1, let p ij ln(p ij )=0.
[0107]
[0108] (5) Determine the entropy weight of the index.
[0109]
[0110] In the formula: d j =1-e j The coefficient of variation of an indicator is denoted by a factor of 1. The larger the value, the greater the amount of information provided by the indicator, and the greater the weight it should be given.
[0111] To eliminate the influence of different dimensions among the indicators and facilitate scientific summarization, normalization preprocessing is required for each indicator. For the positive benefit indicator U... 13 U 31 U 32 and reverse cost type indicator U 11 U 12 U 21 U 22 The values of each index were processed using equations (5) and (6) respectively, and the range of values after processing is shown in Table 14.
[0112] Table 14
[0113] Evaluation index level <![CDATA[Uniaxial compressive strength U 11 > <![CDATA[Elastic modulus U 12 > <![CDATA[Poisson's ratio U 13 > <![CDATA[Permeability U 21 > <![CDATA[Degree of pore and fissure development U 22 > <![CDATA[Gypsum content U 31 > <![CDATA[Crystal form U 32 > I 0-0.25 0-0.25 0-0.25 0-0.25 0-0.25 0-0.25 0-0.25 II 0.25-0.5 0.25-0.5 0.25-0.5 0.25-0.5 0.25-0.5 0.25-0.5 0.25-0.5 III 0.5-0.75 0.5-0.75 0.5-0.75 0.5-0.75 0.5-0.75 0.5-0.75 0.5-0.75 IV 0.75-1 0.75-1 0.75-1 0.75-1 0.75-1 0.75-1 0.75-1
[0114] When using the entropy weight method to determine the weight of the indicators, the sealing performance of the gypsum caprock in different sections of the gas storage can be used as a reference to calculate the weight of each indicator. The data after normalization of the evaluation indicators of the sealing performance of the gypsum caprock are shown in Table 15.
[0115] Table 15
[0116]
[0117] Substitute the normalized data in the table into equations (7) and (8) to obtain the entropy value and difference coefficient of the performance evaluation index for the heterogeneous gypsum caprock. Then, substitute the obtained entropy value into equation (9) to calculate the weight value w of the performance evaluation index for the heterogeneous gypsum caprock, as shown in Table 16.
[0118] Table 16
[0119] Evaluation indicators <![CDATA[Uniaxial compressive strength U 11 > <![CDATA[Elastic modulus U 12 > <![CDATA[Poisson's ratio U 13 > <![CDATA[Permeability U 21 > <![CDATA[Degree of pore and fissure development U 22 > <![CDATA[Gypsum content U 31 > <![CDATA[Crystal form U 32 > Entropy 0.9968 0.9922 0.9388 0.9626 0.9524 0.9670 0.9642 Coefficient of difference 0.0032 0.0078 0.0612 0.0374 0.0476 0.0330 0.0358 weight value w 0.0141 0.0344 0.2710 0.1654 0.2106 0.1460 0.1584
[0120] S2.3 The process of calculating the hierarchical structure of the index using the coefficient of variation method includes:
[0121] The coefficient of variation of the evaluation indicators is calculated using the standard deviation and mean of the evaluation indicators.
[0122] The second objective weight is calculated based on the coefficient of variation of the evaluation index.
[0123] In this embodiment, since the weights obtained by the analytic hierarchy process (AHP) are highly subjective and the weights obtained by the entropy weight method lack balance, the coefficient of variation (COV) method, which uses the coefficient of variation of the differences between the characteristic values of the evaluation factors to obtain the weights, can effectively overcome the shortcomings of the AHP and the entropy weight method. The specific steps for calculating the second objective weights using the COV method are as follows:
[0124] (1) Construct an evaluation matrix.
[0125] Suppose there are m evaluation objects, and each object has n evaluation indicators. Let the j-th evaluation indicator of the i-th evaluation object be denoted as s. ij Then the judgment matrix S of the original data is S=(s ij )m×n (i=1, 2,…,m; j=1, 2,…,n):
[0126]
[0127] (2) Calculate the characteristic values of the evaluation index.
[0128]
[0129]
[0130] In the formula: denoted as the average value of the j-th evaluation index feature; D is the root mean square deviation of the j-th evaluation index feature.
[0131] (3) Calculate the coefficient of variation δ of the evaluation index j .
[0132]
[0133] (4) Calculate the weight value W of the evaluation index j .
[0134]
[0135] Based on the normalized values of each evaluation index in Table 15, the coefficient of variation was calculated, and the results are shown in Table 17.
[0136] Table 17
[0137]
[0138] S3. Couple at least three of the basic weights to obtain the coupled weights of each evaluation index.
[0139] In some embodiments, the process of S3 includes:
[0140] The subjective weight, the first objective weight, and the second objective weight are coupled using a linear weighting method to obtain the coupled weight. During the linear weighting, the undetermined coefficients of the subjective weight, the first objective weight, and the second objective weight are dynamically adjusted.
[0141] Because single subjective or objective weighting methods have systematic limitations, using a single weighting method often fails to accurately depict the relative importance of each indicator. Linear weighting (LWM), however, can combine weights obtained from multiple methods, allowing them to complement each other and maximizing the improvement over a single method. Previous studies have often used LWM to combine weights obtained from two different weighting methods, but this combination often still suffers from significant systematic limitations and fails to effectively achieve the complementary advantages of different weighting methods. Building upon previous research, this paper proposes coupling the evaluation indicator weights obtained from AHP, EWM, and COV methods to obtain true weights that reflect the information of each indicator.
[0142]
[0143] In the formula, w j These are the coupling weight coefficients; a j b is the AHP weighting coefficient for the j-th indicator; j c is the EWM weighting coefficient for the j-th indicator; j is the COV weight coefficient of the j-th indicator; k1, k2, and k3 are undetermined coefficients (k1>0, k2>0, k3>0, and k1+k2+k3=1).
[0144] The core issue of LWM lies in determining the values of the undetermined coefficients k1, k2, and k3. To address this, this invention proposes a multi-level dynamic adjustment method, including: dynamic adjustment based on expert rules, quantitative dynamic adjustment based on dispersion and consistency, and dynamic adjustment based on optimization algorithms. In practical applications, the appropriate adjustment method can be selected based on the data richness of the study area and engineering requirements.
[0145] S3.1 Dynamic adjustment based on expert rules:
[0146] Based on previous research findings and studies on the mechanical properties of heterogeneous gypsum caprock, a comprehensive analysis method is proposed to determine the undetermined weight coefficients k1, k2, and k3 of the coupled evaluation indices for the sealing performance of gypsum caprock, namely, AHP, EWM, and COV. The main contents are as follows:
[0147] (1) The relative importance of each evaluation index is ranked based on the weight values obtained from AHP, EWM and COV.
[0148] (2) If the importance of the evaluation indicators is roughly equal and it is impossible to judge the size, then k1=0, k2=k3=0.5. That is, when the maximum difference between the subjective weight values of each evaluation indicator is less than the preset threshold (such as 10%), it is determined that the importance of each evaluation indicator cannot be distinguished.
[0149] (3) If the ranking of indicators based on the weight values of AHP, EWM and COV is completely consistent with the ranking of the relative importance of the indicators, then k1=0.5, k2=k3=0.25.
[0150] (4) If the ranking of indicators determined by AHP is consistent with the ranking of relative importance, but the ranking of indicators determined by EWM and COV weights is inconsistent with the ranking of relative importance, it indicates that the weights obtained by the objective analysis method are no longer derived from the importance of the indicators themselves. In order to reduce the influence of objective factors, a weight of 0.5 is taken. <k1<1,0<k2+k3<0.5。
[0151] (5) If the ranking of indicators determined by the EWM and COV weight values is consistent with the ranking of relative importance, but the ranking of indicators determined by the AHP weight values is inconsistent with the ranking of relative importance, it indicates that the weights obtained by the subjective judgment method are no longer derived from the importance of the indicators themselves. In order to reduce the influence of subjective factors, we take 0. <k1<0.5,0.5<k2+k3<1。
[0152] (6) If one or more zeros exist in the objective weight coefficients of EWM and COV, it means that such indicators have no impact on the evaluation results. They should be removed from the evaluation indicator system first, and then the remaining indicators should be processed according to the above steps.
[0153] Based on a comparative analysis of previous research findings and studies on the mechanical properties of heterogeneous gypsum caprock, the relative importance of each indicator is ranked as follows: U 11 >U 21 >U 22 >U 32 >U 12 >U 31 >U 13 The indicators were ranked based on the weights obtained from AHP, EWM, and COV. The ranking determined by subjective weights was consistent with the ranking of relative importance, while the ranking determined by objective weights was inconsistent. Therefore, the coupling weight values were calculated primarily using subjective weights, with k1=0.7, k2=0.15, and k3=0.15. Substituting these values into Equation 15 yielded the calculated coupling weight values (Table 18). The results show that the degree of pore and fracture development has the highest impact on the sealing performance evaluation of heterogeneous gypsum caprock in gas storage facilities, followed by uniaxial compressive strength and permeability, then crystal morphology and Poisson's ratio, while gypsum content and elastic modulus have relatively minimal influence.
[0154] Table 18
[0155]
[0156] S3.2 Quantization Dynamic Adjustment Based on Discreteness and Consistency
[0157] S3.2.1 Calculate the dispersion of various weights. Use the coefficient of variation. The dispersion of the m-th class weights (m=1,2,3 corresponding to AHP, EWM, and COV respectively) across various evaluation metrics is measured as follows:
[0158] ;
[0159] in, Let m be the standard deviation of the m-th class weight across all evaluation indicators. Let be the mean of the weights of the m-th class across all evaluation metrics. Dispersion. The larger the value, the more significant the difference between different indicators, meaning the stronger the ability of this type of weight to distinguish between indicators. Therefore, it should be given higher credibility when coupling.
[0160] S3.2.2 Calculate the consistency between various weights and the reference ranking. Based on engineering experience or expert knowledge, pre-determine the reference ranking of the physical importance of each evaluation index. In this embodiment, based on the physical mechanism of the sealing performance of heterogeneous gypsum caprock, the relative importance ranking of each index is determined as follows: uniaxial compressive strength (U 11 ) > Penetration (U 21 > Pore and fracture development degree (U) 22 )> Crystal morphology (U 32 > Elastic modulus (U) 12 )> Gypsum content (U 31 Poisson's ratio (U) 13 ), denoted as the reference sorting vector R=[r1,r2,...,r n ],in is the sorting index of the j-th indicator; the smaller the value, the more important it is.
[0161] Sort the indicators according to their weight values from largest to smallest for the m-th category of weights, and obtain the weight sorting vector R. m .
[0162] R is measured using the Spearman rank correlation coefficient. m Consistency with the reference sorting vector R:
[0163] ;
[0164] in, For the j-th indicator in the weight ranking vector R m The ranking difference between the ranking and the reference ranking vector R, where n is the number of evaluation indicators.
[0165] The value range is [-1, 1]. The closer it is to 1, the more consistent the ranking of this type of weight is with the physical importance reference ranking, that is, the higher the reliability of this type of weight; The closer the result is to -1, the more reversed the order of the two values, and the lower the reliability of this type of weight. For the case of negative correlation, this embodiment takes... To ensure that the credibility factor is non-negative.
[0166] S3.2.3. Combining dispersion and consistency, calculate the credibility factor and dynamic coupling coefficient. Define the credibility factor. Then the dynamic coupling coefficient ,in, The adjustment coefficient ( This is used to balance the contribution weights of dispersion and consistency in credibility evaluation. The larger the value, the more significant the effect of dispersion. The smaller the value, the more significant the effect of consistency. In this embodiment, the value is taken based on practical engineering experience. This means that dispersion is considered to be just as important as consistency.
[0167] S3.2.4 Substitute the dynamically calculated k1, k2, and k3 into the linear weighting formula to obtain the coupling weight wⱼ of each evaluation index.
[0168] S3.3 Dynamic Adjustment Based on Optimization Algorithm
[0169] To further improve the accuracy and adaptability of dynamic adjustment, this embodiment also provides a dynamic adjustment method based on the particle swarm optimization (PSO) algorithm. When the study area has sufficient historical evaluation data or actual engineering feedback data, this optimization algorithm can be used to automatically determine the optimal undetermined coefficients.
[0170] Step 3.3.1: Using the undetermined coefficients k1, k2, and k3 as optimization variables, define the objective function as minimizing the error between the predicted blocking performance level and the actual engineering feedback.
[0171] ;
[0172] Constraints:
[0173] , ;
[0174] Where N is the sample size. Let be the predicted blocking performance grading index for the i-th sample. This is the actual engineering feedback value for the i-th sample (which can be obtained through on-site testing or expert scoring).
[0175] Step 3.3.2: Set the particle swarm size to M=50, the maximum number of iterations T=200, the learning factor c1=c2=2, and the inertia weight ω linearly decreases from 0.9 to 0.4. The position vector of each particle is X = (k1, k2, k3), and the velocity vector is V=(v1,v2,v3).
[0176] Step 3.3.3: For each particle, calculate the objective function value based on its current position, update the individual optimal position pbest and the global optimal position gbest, and update the velocity and position according to the following formula:
[0177] ;
[0178] ;
[0179] Where r1 and r2 are random numbers between [0,1].
[0180] Step 3.3.4: Stop iteration when one of the following conditions is met: (1) The maximum number of iterations is reached; (2) The global optimum value changes less than the threshold for 50 consecutive iterations. .
[0181] Step 3.3.5: Take the global optimal solution as the final undetermined coefficients k1, k2, k3, and substitute them into the linear weighting formula to obtain the coupling weights.
[0182] It should be noted that the above dynamic adjustment method is a preferred implementation. In practical applications, depending on the richness of sample data in the study area and engineering requirements, the following alternative or supplementary methods can be adopted:
[0183] (1) When there is little sample data and the experts are experienced, dynamic adjustments can be made based on expert judgment and rule reasoning (first level), which has strong interpretability;
[0184] (2) When there is sufficient sample data and a clear reference ranking, dynamic adjustment is made based on objective quantification (second level) of dispersion and consistency, without the need for historical feedback;
[0185] (3) When there is sufficient sample data and historical feedback data, dynamic adjustment is made based on the best fit (third level) of the actual feedback, which has the highest accuracy.
[0186] (4) When conducting a comprehensive evaluation of multiple regions, first use the first level for initialization, and then use the second / third level for dynamic adjustment and fine optimization.
[0187] S4. Based on the coupling weight, the blocking performance grading index is calculated, and the blocking performance of the cap layer in the study area is evaluated and graded using the blocking performance grading index.
[0188] In some embodiments, the process of calculating the plugging performance grading index includes:
[0189] The evaluation indicators are scored based on the comprehensive discrimination method of influencing factors to obtain indicator scores;
[0190] Based on the index score and the coupling weight, the blocking performance grading index is calculated;
[0191] The higher the sealing performance grading index, the better the sealing performance.
[0192] Specifically, based on the selection of evaluation indicators for the sealing performance of heterogeneous gypsum caprock in gas storage facilities, the determination of grading standards, and the calculation of the coupling weights of multiple grading evaluation indicators, a sealing performance grading index (SPI) is creatively proposed, using a comprehensive discrimination method for influencing factors. According to Equation 16, the uniaxial compressive strength (U0) selected for the sealing performance evaluation of heterogeneous gypsum caprock in gas storage facilities is... 11 ), elastic modulus (U 12 Poisson's ratio (U) 13 ), penetration rate (U 21 ) Pore and fracture development degree (U 22 ), gypsum content (U) 31 ), crystal morphology (U 32 The SPI value is calculated using seven indicators. The higher the SPI value, the better the sealing performance of the heterogeneous gypsum caprock.
[0193] (16)
[0194] in For the score of the j-th indicator, Let be the coupling weight of the j-th index.
[0195] Based on the coupling weights obtained in Table 18, the SPI in this embodiment can be:
[0196]
[0197] When scoring the seven indicators, different value ranges were assigned to each level according to the indicator grading standard: <2.5, 2.5-5.0, 5.0-7.5, and >7.5, with a maximum value of 10. Specific assignment standards are shown in Table 19. The values of each evaluation indicator for the sealing performance of heterogeneous gypsum caprock were obtained from the table, and the SPI value was calculated to determine the sealing performance level of the heterogeneous gypsum caprock. The score ranges corresponding to each level are: <2.5, 2.5-5.0, 5.0-7.5, and >7.5, corresponding to four levels: poor, average, good, and excellent, respectively.
[0198] Table 19
[0199]
[0200] In this embodiment, the zoning scheme for the sealing performance of heterogeneous gypsum caprock in the study area involves inputting the obtained performance evaluation data of heterogeneous gypsum caprock in the Huangcaoxia gas storage facility into the heterogeneous gypsum caprock sealing performance coupled evaluation system to obtain the SPI score, which is then used to evaluate the sealing performance of the Jiaer gas storage facility in the study area. 3 Subsection gypsum rock, Jia Er 2 Subsection gypsum and Jia Er 1 The sealing performance of the sub-segment gypsum caprock was evaluated (Table 20).
[0201] Table 20
[0202]
[0203] Analysis shows that the SPI values of each sample ranged from 3.864 to 7.635, indicating that the sealing performance of each sample was generally good. (Jia Er) 3 The average SPI value of the gypsum rock samples in the sub-section was 6.138, indicating a relatively good caprock sealing performance. (Jia Er) 2 The average SPI value of the gypsum rock samples in the sub-section was 5.543, indicating a good caprock sealing performance level, but with strong heterogeneity. The average SPI value of the gypsum rock samples in the Jia-2-1 sub-section was 6.522, indicating a good caprock sealing performance level.
[0204] In summary, this embodiment establishes an evaluation index system based on seven indicators: uniaxial compressive strength, elastic modulus, Poisson's ratio, permeability, degree of pore and fracture development, gypsum content, and crystal morphology. The indicators are divided into four levels: I (poor), II (average), III (good), and IV (fair) according to their different degrees of influence on the sealing performance of heterogeneous gypsum caprock.
[0205] This embodiment quantifies each indicator, obtains subjective weights based on AHP, first objective weights and second objective weights based on EWM and COV respectively, obtains coupling weight coefficients for the indicators based on LWM, and proposes a sealing performance grading index SPI based on the comprehensive discrimination method of influencing factors, thus constructing a coupled evaluation system for the sealing performance of heterogeneous gypsum caprock strata. By coupling multiple evaluation methods, a comprehensive and objective coupled evaluation system for the sealing performance of heterogeneous gypsum caprock strata in gas storage facilities is formed, improving the accuracy and reliability of the evaluation. It enables zonal evaluation of the sealing performance of heterogeneous gypsum caprock strata in gas storage facilities, providing a scientific basis for the safe operation and maintenance of gas storage facilities with heterogeneous gypsum caprock strata.
[0206] This embodiment utilizes a coupled evaluation system for the sealing performance of heterogeneous gypsum caprock to evaluate the sealing performance of the heterogeneous gypsum caprock in the Huangcaoxia gas storage facility, demonstrating the sealing performance of heterogeneous gypsum caprock at different strata.
[0207] Example 2 discloses a coupled evaluation method for the sealing performance of heterogeneous gypsum caprock, used to implement the coupled evaluation method for the sealing performance of heterogeneous gypsum caprock described in Example 1. The system includes:
[0208] The indicator system construction module is used to obtain multiple types of characteristic parameters of the caprock in the study area (including mechanical property parameters, physical property parameters and mineral composition parameters), and to construct an indicator hierarchical structure system for evaluating the caprock sealing performance.
[0209] Multiple weight calculation modules are used to calculate the weight of each evaluation index using at least three weighting methods (including but not limited to the analytic hierarchy process, entropy weight method, and coefficient of variation method) to obtain at least three basic weights (subjective weight, first objective weight, and second objective weight).
[0210] Multiple weight coupling modules are used to couple at least three of the basic weights to obtain the coupled weights of each evaluation index; the dynamic adjustment method includes a dynamic adjustment method based on dispersion and consistency, and / or a dynamic adjustment method based on optimization algorithm;
[0211] The evaluation module is used to calculate the blocking performance grading index based on the coupling weights, and to evaluate and grade the blocking performance of the cap layer in the study area.
[0212] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
Claims
1. A coupled evaluation method for the sealing performance of heterogeneous gypsum caprock, characterized in that, include: Multiple characteristic parameters of heterogeneous gypsum caprock in the study area were obtained, and a hierarchical index system for coupled evaluation of caprock sealing performance was constructed based on the characteristic parameters. The weights of each evaluation index in the hierarchical structure system of the index are calculated using at least three weighting methods to obtain at least three basic weights. At least three of the aforementioned basic weights are coupled to obtain the coupled weights for each evaluation index; Based on the coupling weights, a grading index for closure performance is calculated, and the grading index is used to evaluate and classify the closure performance of the cap layer in the study area.
2. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 1, characterized in that, The various types of characteristic parameters include mechanical property parameters, physical property parameters, and mineral composition parameters.
3. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 2, characterized in that, The mechanical property parameters include uniaxial compressive strength, elastic modulus, and Poisson's ratio; the physical property parameters include permeability and the degree of pore and fracture development; the mineral composition parameters include gypsum content and crystal morphology; and the evaluation indicators include uniaxial compressive strength, elastic modulus, Poisson's ratio, permeability, pore and fracture development, gypsum content, and crystal morphology.
4. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 1, characterized in that, At least three weighting methods are used, including the analytic hierarchy process (AHP), the entropy weight method, and the coefficient of variation method. The AHP is used to obtain the subjective weights of the evaluation indicators, the entropy weight method is used to obtain the first objective weights of the evaluation indicators, and the coefficient of variation method is used to obtain the second objective weights of the evaluation indicators.
5. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 4, characterized in that, The process of analyzing the hierarchical structure of the indicators using the Analytic Hierarchy Process (AHP) includes: Based on the aforementioned hierarchical structure of indicators, a judgment matrix is constructed; The judgment matrix is calculated using the sum-product method to obtain the weights of each level of indicators, and the consistency of the judgment matrix is checked to finally obtain the subjective weights of the evaluation indicators.
6. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 4, characterized in that, The process of calculating the hierarchical structure of the indicators using the entropy weight method includes: Normalization was used to obtain the entropy value and difference coefficient of the evaluation index; The first objective weight is calculated based on the index entropy value.
7. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 4, characterized in that, The process of calculating the hierarchical structure of the indicators using the coefficient of variation method includes: The coefficient of variation of the evaluation indicators is calculated using the standard deviation and mean of the evaluation indicators. The second objective weight is calculated based on the coefficient of variation of the evaluation index.
8. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 4, characterized in that, The process of coupling the at least three basic weights to obtain the coupled weights of each evaluation index includes: The subjective weight, the first objective weight, and the second objective weight are coupled using a linear weighting method to obtain the coupled weight. During the linear weighting, the undetermined coefficients of the subjective weight, the first objective weight, and the second objective weight are dynamically adjusted.
9. The coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in claim 1, characterized in that, The process of calculating the plugging performance rating index includes: The evaluation indicators are scored based on the comprehensive discrimination method of influencing factors to obtain indicator scores; Based on the index score and the coupling weight, the blocking performance grading index is calculated; The higher the sealing performance grading index, the better the sealing performance.
10. A coupled evaluation method for the sealing performance of heterogeneous gypsum caprock, characterized in that, The system is used to implement the coupled evaluation method for the sealing performance of heterogeneous gypsum caprock as described in any one of claims 1-9, the system comprising: The indicator system construction module is used to obtain multi-type characteristic parameters of the cap layer in the study area and construct an indicator hierarchical structure system for evaluating the cap layer's sealing performance. Multiple weight calculation modules are used to calculate the weight of each evaluation index using at least three weighting methods to obtain at least three basic weights; Multiple weight coupling modules are used to couple at least three of the basic weights to obtain the coupled weights of each evaluation index; The evaluation module is used to calculate the blocking performance grading index based on the coupling weights, and to evaluate and grade the blocking performance of the cap layer in the study area.