Energy efficiency evaluation method for gas field gathering and transportation pipe network system based on secondary station distribution strategy

Abstract

The invention provides a gas field gathering and transportation pipe network system energy efficiency evaluation method based on a secondary station distribution strategy, and belongs to the field of natural gas gathering and transportation. In order to solve the problems that gas field development enters a later stage and the technological adaptability of a gathering and transportation pipe network system becomes poor, according to the technological process of the gas field gathering and transportation pipe network system adopting a secondary station distribution strategy, main energy efficiency influence factors are selected, an energy efficiency evaluation system is constructed, and on the basis of researching an analytic hierarchy process, an entropy weight method, a fuzzy membership function method and a linear weighting method, the energy efficiency evaluation system is established. And a set of complete gas field gathering and transportation pipe network system energy efficiency evaluation algorithm model adopting a secondary station distribution strategy is constructed. The invention provides a more scientific and systematic method for energy efficiency evaluation of a gas field gathering and transportation pipe network system for realizing a secondary station distribution strategy.

Description

Technical Field

[0001] The invention belongs to the field of natural gas gathering and transportation, and in particular relates to an energy efficiency evaluation method for a gas field gathering and transportation pipeline network system adopting a secondary station layout strategy. Background Art

[0002] As gas field development enters the later stage, the process adaptability of the gathering and transportation pipeline network system deteriorates, and the production cost increases sharply. It is urgent to reduce the energy consumption cost per unit of gas production and improve the overall energy efficiency of the gas field. Therefore, it is necessary to evaluate and analyze the energy efficiency adaptability of the gas field gathering and transportation pipeline network system. By retrospectively evaluating the energy efficiency level of the gathering and transportation pipeline network system, the weak links of energy efficiency are analyzed, and targeted efficiency improvement and optimization measures are proposed accordingly.

[0003] At present, with the development of computing, methods such as analytic hierarchy process, entropy weight method, neural network and grey correlation method are also used to evaluate the energy efficiency of various facilities in the station or the oil field gathering and transportation system. However, there are still few energy efficiency evaluations for gas field gathering and transportation pipeline systems.

[0004] The energy efficiency evaluation of the gas field gathering and transportation pipeline network system is a complex process, which is affected by multiple factors and diversified indicators. Therefore, an energy efficiency evaluation index system for the gas field gathering and transportation pipeline network system covering 3 levels and 17 indicators was established, and a complete set of energy efficiency evaluation algorithm models for the gas field gathering and transportation pipeline network system based on hierarchical analysis method, entropy weight method, fuzzy membership function method and linear weighted method was proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an energy efficiency evaluation method for a gas field gathering and transportation pipeline system with a two-level station layout strategy of three links: wellhead, gas gathering station and centralized processing station. The method can effectively evaluate similar gas field gathering and transportation pipeline systems, find out the reasons for the poor energy efficiency of gas field gathering and transportation pipeline systems, and provide a basis for energy saving work of gas field gathering and transportation pipeline systems.

[0006] To achieve the above object, the technical solution adopted by the present invention is: a method for evaluating the energy efficiency of a gas field gathering and transportation pipeline system with a two-level station layout strategy, comprising the following steps:

[0007] (1) According to the process flow of the gas field gathering and transportation pipeline system adopting the two-level station layout strategy, based on the five principles of systematic principle, hierarchical principle, independence principle, operability principle and practical principle, the main influencing factors of energy efficiency in each link of the gathering and transportation pipeline system are selected, and a technical energy efficiency evaluation system for the gas field gathering and transportation pipeline system is constructed from each process unit. It consists of three levels: target layer, criterion layer and indicator layer.

[0008] (2) The analytic hierarchy process is used to obtain the subjective weights of the indicator layer (third-level indicators), and then the entropy weight method is used to obtain the objective weights of the indicator layer. Finally, the weights of the indicator layer are obtained through the composite weight calculation formula; the analytic hierarchy process is used to obtain the weights of the criterion layer (secondary indicators).

[0009] (3) Using the ridge-type fuzzy membership function, each indicator value (actual data) of the three-level indicators is calculated to obtain the indicator membership value, which is then converted into a standard quantitative value.

[0010] (4) The standard quantitative value of the third-level indicator evaluation index and the product of the weight are added together through the linear weighted method to obtain the evaluation score of each second-level indicator, and then the sum is calculated to obtain the evaluation score of the first-level indicator.

[0011] 1) The calculation process of the hierarchical analysis method is as follows:

[0012] ① Through the questionnaire survey to the experts, the scores (scale values) of multiple experts on the importance of different indicators are collected. The scale values ​​and their meanings are shown in Table 1. The judgment matrix is ​​constructed as shown in Table 2. The judgment matrix that can pass the consistency test is screened out and the subjective indicator weights are calculated.

[0013] Table 1 Scale values ​​and meanings

[0014]

[0015] a ij (i, j = 1, 2, 3... n) is the importance of index i relative to index j, then a ji is the importance of indicator j relative to i, and a ii = l,

[0016] a ij >0,a ij =l / a ji .

[0017] Table 2 Judgment Matrix

[0018]

[0019] ② Use the hierarchical analysis method to calculate the weight of the evaluation index. The formula is as follows:

[0020]

[0021] Where A——judgment matrix;

[0022] ——The nth root of the product of each row of the constructed judgment matrix;

[0023] n——judgment matrix order;

[0024] W i ——Weight of evaluation indicators for each project.

[0025] ③Consistency test of the judgment matrix is ​​performed, the formula is as follows:

[0026]

[0027] Where λ max ——The maximum eigenvalue of the matrix, that is, AW = λ max W;

[0028] CI – Judgment Matrix Consistency Index;

[0029] CR——Consistency test index;

[0030] RI——Random consistency index, obtained from Table 3.

[0031] If the CR value is less than 0.1, it means that the calculation result is credible and can be adopted; conversely, if the CR value is greater than 0.1, it means that the result is unreliable and the judgment matrix needs to be readjusted to ensure the accuracy and reliability of the analysis results.

[0032] Table 3 Average random consistency index

[0033]

[0034] 2) The calculation process of entropy weight method is as follows:

[0035] ① First, we need to construct an evaluation index matrix. Assuming there are m evaluation items and n evaluation indicators, we can construct an evaluation matrix X of the original data = (x ij ) n×m

[0036]

[0037] Where x ij ——Indicates the evaluation value of the jth evaluation item under the ith indicator.

[0038] ② Then standardize each indicator to obtain the standard matrix Y ij =(y ij ) m×n , the formula is as follows.

[0039] For the evaluation index of the “larger the value, the better the benefit” type, its calculation formula is shown in formula (8):

[0040]

[0041] For the evaluation index of the type “the smaller the value, the better the benefit”, the calculation formula is as shown in formula (9):

[0042]

[0043] Where y ij ——Indicates the standard evaluation value of the jth evaluation item under the ith indicator.

[0044] ③ Use the entropy weight method information entropy formula to calculate the entropy of each evaluation index of the gathering and transportation pipeline network system, and then calculate the entropy weight of each index. The size of the entropy weight can intuitively reflect the weak links in the energy efficiency of the gathering and transportation pipeline network system. The specific calculation steps are as follows:

[0045] The information entropy e of the jth evaluation index j The calculation formulas of weights are shown in equations (10) and (12):

[0046]

[0047] Where e j ——Information entropy of the jth evaluation index;

[0048] r ij ——The characteristic weight of each evaluation object of the ith item under the jth indicator;

[0049] ω j ——The weight of the jth evaluation indicator,

[0050] The composite weight calculation formula is shown in formula (13):

[0051] λ i =aw i +(1-a)u i (13)

[0052] Where a is a coefficient used to adjust the subjective and objective proportions of the composite weight, 0≤a≤1. When a=0, the composite weight value is the weight of the entropy weight method; when a=1, the composite weight value is the weight of the hierarchical analysis method.

[0053] 3) The calculation process of fuzzy membership and quantitative index is as follows:

[0054] ① Calculate the fuzzy membership of the evaluation index. First, determine the lower limit a and upper limit b of each index and set the quantitative range of the index. For the positive index, the optimal value is b; for the reverse index, the optimal value is a.

[0055] ② According to the nature of the evaluation index, select the type of fuzzy membership function. The ridge-type fuzzy membership function is used, which includes two types: ascending ridge-shaped distribution and descending ridge-shaped distribution. The specific selection will be determined according to the characteristics of each index.

[0056] The positive index is calculated using the ascending ridge model, as shown in formula (14):

[0057]

[0058] Where a is the lower limit of the indicator;

[0059] b——upper limit of the indicator.

[0060] The reverse index is calculated using the descending ridge model, as shown in formula (15):

[0061]

[0062] ③ By setting each indicator value x i Substitute the fuzzy membership function for calculation and get the membership value of the index f(x i ), between 0 and 1, eliminating the dimension differences between indicators and allowing different indicators to be compared uniformly. i ) is converted into a standard quantitative value (three-level indicator evaluation score), which needs to be multiplied by 100. The calculation formula is shown in formula (16).

[0063] F(x i )=f(x i )×100 (16)

[0064] In the formula, f(x i )——Indicator fuzzy membership value;

[0065] F(x i )——quantitative value of the evaluation standard of the indicator.

[0066] 4) The evaluation scores of the secondary and primary indicators are calculated by the linear weighted method:

[0067] The calculation formula of the secondary index evaluation value is shown in formula (17).

[0068]

[0069] Where U i ——Evaluation score of the ith secondary indicator;

[0070] U ij ——The quantitative value of the evaluation standard of the jth third-level indicator in the i-th second-level indicator;

[0071] ω ij ——The weight of the jth third-level indicator in the i-th second-level indicator.

[0072] The calculation formula of the first-level indicator evaluation value is shown in formula (18).

[0073]

[0074] Where U is the evaluation score of the first-level indicator;

[0075] U i ——The evaluation score of the i-th secondary indicator in the primary indicator;

[0076] ωi ——The weight of the i-th secondary indicator in the primary indicator.

[0077] The beneficial effects of the present invention are mainly reflected in:

[0078] 1. The three-level indicators of the index system of the gathering and transportation pipeline network system present complex characteristics such as variety, nonlinearity, and multi-dimensionality. The composite weight determination method of the hierarchical-entropy weight method not only ensures the expert subjective judgment of the decision-maker, but also takes into account the objectivity of the decision, providing a more scientific and reliable basis for the comprehensive evaluation results of the energy efficiency of the gathering and transportation pipeline network system.

[0079] 2. Taking into account the characteristics of the constructed energy efficiency evaluation index system of the gathering and transportation pipeline network system, which has complex levels and diverse indicators, as well as the fuzziness of the boundaries between "good" and "bad" indicators, the fuzzy membership function is used to convert different indicators into the same dimension for evaluation.

[0080] 3. Carry out energy efficiency evaluation on each link of the gas field gathering and transportation pipeline network system every month, so as to obtain the development trend of the energy efficiency of the gathering and transportation pipeline network system, discover the problems affecting the gathering and transportation pipeline network system as early as possible, take active measures to improve the efficiency of the gathering and transportation pipeline network system, and provide guidance for energy conservation and consumption reduction of the gas field gathering and transportation pipeline network system. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 Establishment of energy efficiency evaluation index system structure for gathering and transportation pipeline network system

[0082] Figure 2 Monthly scores for well site energy efficiency evaluation

[0083] Figure 3 To collect the monthly scores of pipeline energy efficiency evaluation

[0084] Figure 4 Monthly scores for gas gathering station energy efficiency evaluation

[0085] Figure 5 Monthly scores for energy efficiency evaluation of the gathering and transportation pipeline network system

[0086] Figure 6 Flow chart for comprehensive evaluation of energy efficiency of gathering and transportation pipeline network system DETAILED DESCRIPTION

[0087] Below, the content of the present invention is further described in conjunction with examples:

[0088] The present invention is a method for evaluating the energy efficiency of a gas field gathering and transportation pipeline system with a two-level station layout strategy, and the steps are as follows:

[0089] (1) According to the process flow of the gas field gathering and transportation pipeline system adopting the two-level station layout strategy, based on the five principles of systematic principle, hierarchical principle, independence principle, operability principle and practical principle, the main influencing factors of energy efficiency in each link of the gathering and transportation pipeline system are selected, and a technical energy efficiency evaluation system for the gas field gathering and transportation pipeline system is constructed from each process unit. It consists of three levels: target layer, criterion layer and indicator layer.

[0090] The X gas field gathering and transportation system adopts a set of low-pressure gathering and transportation process solutions, which include "downhole throttling, medium and low pressure gas gathering, gas-liquid mixed transportation, liquid metering, well-to-well series connection, and normal temperature separation". In terms of station layout, a two-level station layout strategy is adopted, which specifically includes three links: wellhead, gas gathering station and centralized processing station.

[0091] This article takes the part of the gathering and transportation pipeline network system of Block A of X gas field, including the natural gas processing plant, two gas gathering stations and their well sites, and related pipelines, as an example.

[0092] Taking the X gas field gathering and transportation pipeline network system as the research object, based on the five principles of systematic principle, hierarchical principle, independence principle, operability principle and practical principle, the main influencing factors of energy efficiency in each link of the gathering and transportation pipeline network system are selected, and the technical energy efficiency evaluation system of the gas field gathering and transportation pipeline network system is constructed from each process unit. The indicator system structure diagram is shown in the figure below. Figure 1 shown.

[0093] The evaluation index of the gathering and transportation pipeline network system is mainly divided into three levels: target layer, criterion layer and index layer. Based on the analysis of many factors affecting the energy efficiency of the gathering and transportation pipeline network system of gas fields, and combined with the energy consumption and benefits of the gathering and transportation pipeline network system and the sensitivity analysis of the energy efficiency level of the unit process, this paper finally constructed a comprehensive and systematic energy efficiency evaluation index system for the gathering and transportation pipeline network system.

[0094] The system is led by a target layer (first-level indicator), which is subdivided into second-level indicators from the two dimensions of technology and economy; the technical indicators are composed of well sites, gathering and transmission pipelines, and gas gathering stations, while the economic indicators focus on the energy consumption and benefits of the gathering and transmission pipeline network system. These four criterion layers (second-level indicators) together constitute the core of the evaluation framework; further, based on the corresponding process energy efficiency influencing factors of the second-level indicators, 17 third-level indicators are selected to form a hierarchical evaluation framework. The indicator system is shown in Table 1.

[0095] Table 1 Energy efficiency evaluation index system of gathering and transportation pipeline network system

[0096]

[0097]

[0098] (2) The analytic hierarchy process is used to obtain the subjective weights of the indicator layer (third-level indicators), and then the entropy weight method is used to obtain the subjective weights of the indicator layer. Finally, the weights of the indicator layer are obtained through the composite weight calculation formula; the analytic hierarchy process is used to obtain the weights of the criterion layer (secondary indicators).

[0099] The analytic hierarchy process is used to calculate the subjective weights of the indicator layer (third-level indicators) and the weights of the criterion layer (second-level indicators). The process is as follows:

[0100] ① Through the questionnaire survey to the experts, the scores (scale values) of multiple experts on the importance of different indicators are collected. The scale values ​​and their meanings are shown in Table 2. The judgment matrix is ​​constructed as shown in Table 3. The judgment matrix that can pass the consistency test is screened out and the subjective indicator weights are calculated.

[0101] Table 2 Scale values ​​and meanings

[0102]

[0103] a ij (i, j = 1, 2, 3... n) is the importance of index i relative to index j, then a ji is the importance of indicator j relative to i, and a ii = l,

[0104] a ij >0,a ij =l / a ji .

[0105] Table 3 Judgment Matrix

[0106]

[0107] ② Use the hierarchical analysis method to calculate the weight of the evaluation index. The formula is as follows:

[0108]

[0109]

[0110] Where A——judgment matrix;

[0111] ——The nth root of the product of each row of the constructed judgment matrix;

[0112] n——judgment matrix order;

[0113] W i ——Weight of evaluation indicators for each project.

[0114] ③Consistency test of the judgment matrix is ​​performed, the formula is as follows:

[0115]

[0116] Where λ max ——The maximum eigenvalue of the matrix, that is, AW = λ max W;

[0117] CI – Judgment Matrix Consistency Index;

[0118] CR——Consistency test index;

[0119] RI——Random consistency index, obtained by looking up Table 4.

[0120] If the CR value is less than 0.1, it means that the calculation result is credible and can be adopted; conversely, if the CR value is greater than 0.1, it means that the result is unreliable and the judgment matrix needs to be readjusted to ensure the accuracy and reliability of the analysis results.

[0121] Table 4 Average random consistency index

[0122]

[0123] The above-mentioned analytic hierarchy process is used to calculate the three-level indicator judgment matrix (taking the well site as an example) and the two-level indicator judgment matrix, and the maximum eigenvalue of the two-level indicator judgment matrix is ​​λmax=6.62, CR=0.025<0.1; the maximum eigenvalue of the three-level indicator judgment matrix of the well site is λmax=3.05, CR=0.046<0.1, and the consistency test is qualified. The three-level indicator judgment matrix and weight values ​​of the well site are shown in Table 5, and the two-level indicator judgment matrix and weight values ​​are shown in Table 6.

[0124] Table 5 Judgment matrix B of the three-level indicators 1 —C 1 With weight value

[0125]

[0126] Table 6 Judgment matrix AB and weight values

[0127]

[0128] The subjective weights calculated for the other three-level indicators are shown in Table 7:

[0129] Table 7 Subjective weights of gas gathering stations, collection and transmission pipelines, energy consumption and benefits

[0130]

[0131] The entropy weight method is used to calculate the objective weight of the indicator layer (three-level indicators). The process is as follows:

[0132] ① First, we need to construct an evaluation index matrix. Assuming there are m evaluation items and n evaluation indicators, we can construct an evaluation matrix X of the original data = (x ij ) n×m

[0133]

[0134] Where x ij ——Indicates the evaluation value of the jth evaluation item under the ith indicator.

[0135] ② Then standardize each indicator to obtain the standard matrix Y ij =(y ij ) m×n , the formula is as follows.

[0136] For the evaluation index of the “larger the value, the better the benefit” type, its calculation formula is shown in formula (8):

[0137]

[0138] For the evaluation index of the type “the smaller the value, the better the benefit”, the calculation formula is as shown in formula (9):

[0139]

[0140] Where y ij ——Indicates the standard evaluation value of the jth evaluation item under the ith indicator.

[0141] ③ Use the entropy weight method information entropy formula to calculate the entropy of each evaluation index of the gathering and transportation pipeline network system, and then calculate the entropy weight of each index. The size of the entropy weight can intuitively reflect the weak links in the energy efficiency of the gathering and transportation pipeline network system. The specific calculation steps are as follows:

[0142] The information entropy e of the jth evaluation index j The calculation formulas of weights are shown in equations (10) and (12):

[0143]

[0144] Where e j ——Information entropy of the jth evaluation index;

[0145] r ij ——The characteristic weight of each evaluation object of the ith item under the jth indicator;

[0146] ω j ——The weight of the jth evaluation indicator,

[0147] Since the trunk pipeline is much longer than other pipelines, the data of the DN500 trunk pipeline is selected for the collection of the transmission pipeline, the data of the gas gathering station is the average of the data of the two gas gathering stations, and the well field data is the average of the well field data under the jurisdiction of the two gas gathering stations. Therefore, the actual production data of the transmission pipeline, gas gathering station, and well field from May 2022 to December 2023 are collected, as shown in Tables 8 to 10. The actual production data from 2021 to 2023 are selected for energy consumption and benefits, as shown in Table 11.

[0148] Table 8 Actual production data of well site system

[0149]

[0150] Table 9 Actual production data of the pipeline

[0151]

[0152]

[0153] Table 10 Actual production data of gas gathering stations

[0154]

[0155] Table 11 Actual production data of energy consumption and benefits

[0156]

[0157] Tables 8 to 11 are used as data sets for the entropy weight method, and the above entropy weight method calculation steps are used for calculation. The information entropy and weights obtained are shown in Table 12.

[0158] Table 12 Information entropy and objective weight values ​​of the three-level indicators

[0159]

[0160] The composite weight calculation formula is shown in formula (13):

[0161] λ i =aw i +(1-a)u i (13)

[0162] Where a is a coefficient used to adjust the subjective and objective proportions of the composite weight, 0≤a≤1. When a=0, the composite weight value is the weight of the entropy weight method; when a=1, the composite weight value is the weight of the hierarchical analysis method.

[0163] Based on the results of calculating the weights of indicators at all levels using the tomography method and the entropy weight method, the hierarchical-entropy weight method composite weight of the indicators is calculated according to formula (13). After calculation, the weights of all indicator layers are obtained, as shown in Table 13.

[0164] Table 13 Weight values ​​of energy efficiency evaluation indicators of gathering and transportation pipeline network system

[0165]

[0166] (3) Using the ridge-type fuzzy membership function, each indicator value (actual data) of the three-level indicators is calculated to obtain the indicator membership value, which is then converted into a standard quantitative value.

[0167] The calculation process of fuzzy membership and quantitative index is as follows:

[0168] ① Calculate the fuzzy membership of the evaluation index. First, determine the lower limit a and upper limit b of each index and set the quantitative range of the index. For the positive index, the optimal value is b; for the reverse index, the optimal value is a.

[0169] ② According to the nature of the evaluation index, select the type of fuzzy membership function. The ridge-type fuzzy membership function is used, which includes two types: ascending ridge-shaped distribution and descending ridge-shaped distribution. The specific selection will be determined according to the characteristics of each index.

[0170] The positive index is calculated using the ascending ridge model, as shown in formula (14):

[0171]

[0172] Where a is the lower limit of the indicator;

[0173] b——upper limit of the indicator.

[0174] The reverse index is calculated using the descending ridge model, as shown in formula (15):

[0175]

[0176] ③ By setting each indicator value x i Substitute the fuzzy membership function for calculation and get the membership value of the index f(x i ), between 0 and 1, eliminating the dimension differences between indicators and allowing different indicators to be compared uniformly. i ) is converted into a standard quantitative value (three-level indicator evaluation score), which needs to be multiplied by 100. The calculation formula is shown in formula (16).

[0177] F(x i )=f(x i )×100 (16)

[0178] In the formula, f(x i )——Indicator fuzzy membership value;

[0179] F(x i)——quantitative value of the evaluation standard of the indicator.

[0180] According to the above steps, the fuzzy membership degree and function type of the evaluation index are shown in Table 14.

[0181] Table 14 Evaluation index fuzzy membership function type

[0182]

[0183]

[0184] Substitute the production data as the evaluation value into the simulated membership function to obtain the membership degree and the standard quantitative values ​​of the three-level indicators. The data of the well site, gas gathering station, and collection and transmission pipeline are taken as an example in January 2023, see Table 15. The energy consumption and benefits are taken as examples in 2022 and 2023, see Table 16.

[0185] Table 15 Fuzzy membership and quantitative values ​​of evaluation criteria for well sites, gas gathering stations, and gas collection and transmission pipelines

[0186]

[0187] Table 16 Energy consumption and benefit fuzzy membership and evaluation standard quantitative values

[0188]

[0189] The evaluation scores of the secondary and primary indicators are calculated by the linear weighted method:

[0190] The calculation formula of the secondary index evaluation value is shown in formula (17).

[0191]

[0192] Where U i ——Evaluation score of the ith secondary indicator;

[0193] U ij ——The quantitative value of the evaluation standard of the jth third-level indicator in the i-th second-level indicator;

[0194] ω ij ——The weight of the jth third-level indicator in the i-th second-level indicator.

[0195] The calculation formula of the first-level indicator evaluation value is shown in formula (18).

[0196]

[0197] Where U is the evaluation score of the first-level indicator;

[0198] U i ——The evaluation score of the i-th secondary indicator in the primary indicator;

[0199] ω i ——The weight of the i-th secondary indicator in the primary indicator.

[0200] Taking the data from January 2023 as an example, the linear weighted method is used to obtain the evaluation scores of the secondary and primary indicators, see Tables 17 and 18.

[0201] Table 17 Secondary indicator evaluation scores in January 2023

[0202]

[0203] Table 18 Total score of energy efficiency evaluation of gathering and transportation pipeline network system in January 2023

[0204]

[0205] The data from May 2022 to December 2023 are calculated by the present invention to obtain the monthly scores of energy efficiency evaluation of well sites, gas gathering pipelines, gas gathering stations, and gas gathering and transportation pipeline networks. Figure 2-Figure 5 According to the monthly scores of the energy efficiency evaluation of the well site, gathering and transmission pipeline, gas gathering station, and gathering and transmission pipeline network system, the weaknesses of the gathering and transmission pipeline network system can be analyzed to help improve the efficiency of the gathering and transmission pipeline network system.

[0206] According to relevant standards, analysis of energy efficiency influencing factors, etc., this paper constructs an energy efficiency evaluation system for gas field gathering and transportation pipeline system adopting a two-level station layout. The system includes three levels (target level, criterion level, indicator level) and 17 evaluation indicators. Its process is as follows Figure 6 As shown in the figure, in view of the complexity of the index system of the gathering and transportation pipeline network system, the combined weighting method is adopted to combine the hierarchical analysis method with the entropy weight method, which effectively integrates the advantages of the two. On this basis, the fuzzy membership function method and the linear weighting method are further combined to construct a set of energy efficiency evaluation algorithm models suitable for the gathering and transportation pipeline network system. By evaluating the energy efficiency of each link of the gas field gathering and transportation pipeline network system every month, the development trend of the energy efficiency of the gathering and transportation pipeline network system can be obtained, and the problems affecting the gathering and transportation pipeline network system can be discovered as early as possible, and measures can be taken actively to improve the benefits of the gathering and transportation pipeline network system.

Claims

1. A method for evaluating the energy efficiency of a gas field gathering and transportation pipeline system with a two-level station layout strategy, characterized in that: The following steps are involved: (1) According to the process flow of the gas field gathering and transportation pipeline system adopting the two-level station layout strategy, based on the five principles of systematic principle, hierarchical principle, independence principle, operability principle and practical principle, the main influencing factors of energy efficiency in each link of the gathering and transportation pipeline system are selected, and the technical energy efficiency evaluation system of the gas field gathering and transportation pipeline system is constructed from each process unit. It consists of three levels: target layer, criterion layer and indicator layer; (2) The subjective weight of the indicator layer (three-level indicator) is obtained by using the hierarchical analysis method, and then the objective weight of the indicator layer is obtained by using the entropy weight method. Finally, the weight of the indicator layer is obtained by using the composite weight calculation formula; The analytic hierarchy process was used to obtain the weights of the criterion layer (secondary indicators); (3) Using the ridge-type fuzzy membership function, each indicator value (actual data) of the three-level indicators is calculated to obtain the indicator membership value, which is then converted into a standard quantitative value; (4) The standard quantitative value of the third-level indicator evaluation index and the product of the weight are added together through the linear weighted method to obtain the evaluation score of each second-level indicator, and then the sum is calculated to obtain the evaluation score of the first-level indicator.

2. The method for evaluating energy efficiency of a gas field gathering and transportation pipeline network system with a two-level station layout strategy according to claim 1 is characterized by: In step (1), the evaluation index of the gathering and transportation pipeline network system is mainly divided into three levels: target layer, criterion layer, and indicator layer. The target layer (first-level indicator) is the energy efficiency of the gas field gathering and transportation pipeline network system, the criterion layer (second-level indicator) is the well site, gathering and transportation pipeline, gas gathering station and energy consumption and benefits, and the indicator layer (third-level indicator) is the process energy efficiency influencing factors corresponding to the second-level indicator.

3. The method for evaluating energy efficiency of a gas field gathering and transportation pipeline network system with a two-level station layout strategy according to claim 1 is characterized in that: In step (2), the AHP calculation steps are as follows: ① Through the questionnaire survey to the experts, the scores (scale values) of multiple experts on the importance of different indicators are collected, and the judgment matrix is ​​constructed as shown in formula (1), the judgment matrix that can pass the consistency test is screened out, and the subjective indicator weight is calculated; ② Use the analytic hierarchy process to calculate the weight of the evaluation index. The formulas are shown in (2) to (3): ③ Perform consistency check on the judgment matrix, as shown in formulas (4) to (6): Where A is the judgment matrix a ij ——the importance of indicator i relative to indicator j (scale value), and a ii = l, a ij >0,a ij =l / a ji , a ij =1, indicating that the two indicators are equally important. ij =9, indicating that the latter is absolutely more important than the former when comparing the two indicators; ——The nth root of the product of each row of the constructed judgment matrix; n——judgment matrix order; W i ——The weight of each project evaluation indicator; λ max ——The maximum eigenvalue of the matrix, that is, AW = λ max W; CI – Judgment Matrix Consistency Index; CR——Consistency test index. If the CR value is less than 0.1, it means that the calculation result is credible. RI——Random consistency index, judgment matrix order n=1,2, RI=0; n=3, RI=0.58; n=4, RI=0.9; n=5, RI=1.12; n=6, RI=1.24; n=7, RI=1.32; n=8, RI=1.41; n=9, RI=1.

45.

4. The method for evaluating energy efficiency of a gas field gathering and transportation pipeline system with a two-level station layout strategy according to claim 1 is characterized in that: In step (2), the entropy weight method and compound weight calculation steps are as follows: ① First, we need to construct an evaluation index matrix. Assuming there are m evaluation items and n evaluation indicators, we can construct an evaluation matrix X of the original data = (x ij ) n×m , as shown in formula (7); ② Then standardize each indicator to obtain the standard matrix Y ij =(y ij ) m×n , for the evaluation index of "the larger the value, the better the benefit", the calculation formula is shown in formula (8); for the evaluation index of "the smaller the value, the better the benefit", the calculation formula is shown in formula (9); ③ Use the entropy weight method information entropy formula to calculate the entropy of each evaluation index of the gathering and transportation pipeline network system, and then calculate the entropy weight of each index. The size of the entropy weight can intuitively reflect the weak links in the energy efficiency of the gathering and transportation pipeline network system. The information entropy of the jth evaluation index e j The calculation formulas of the weights are shown in formulas (10) and (12), and the calculation formula of the composite weights is shown in formula (13): λ i ZAW i +(1-a)u i (13) Where x ij ——Indicates the evaluation value of the jth evaluation item under the i-th indicator; y ij ——represents the standard evaluation value of the jth evaluation item under the i-th indicator; e j ——Information entropy of the jth evaluation index; r ij ——The characteristic weight of each evaluation object of the ith item under the jth indicator; ω j ——The weight of the jth evaluation indicator, 0≤ω j ≤1; a——The coefficient for adjusting the subjective and objective proportions of the composite weight, 0≤a≤1. When a=0, the composite weight value is the weight of the entropy weight method; when a=1, the composite weight value is the weight of the hierarchical analysis method.

5. The method for evaluating energy efficiency of a gas field gathering and transportation pipeline network system with a two-level station layout strategy according to claim 1 is characterized in that: In step (3), the fuzzy membership calculation steps are as follows: The calculation process of fuzzy membership and quantitative index is as follows: ① Calculate the fuzzy membership of the evaluation index. First, determine the lower limit a and upper limit b of each index and set the quantitative range of the index. For the positive index, the optimal value is b; for the reverse index, the optimal value is a; ② According to the nature of the evaluation index, select the type of fuzzy membership function. The ridge-type fuzzy membership function is used, which includes two types: ascending ridge distribution and descending ridge distribution. The specific selection will be determined according to the characteristics of each index. The positive index is calculated using the ascending ridge model, as shown in formula (14), and the reverse index is calculated using the descending ridge model, as shown in formula (15); ③ By setting each indicator value x i Substitute the fuzzy membership function for calculation and get the membership value of the index f(x i ), between 0 and 1, eliminating the dimension differences between indicators and allowing different indicators to be compared uniformly. i ) is converted into a standard quantitative value (three-level indicator evaluation score), which needs to be multiplied by 100. The calculation formula is shown in formula (16); F(x i )=f(x i )×100 (16) Where a is the lower limit of the indicator; b——upper limit of the indicator. f(x i )——Indicator fuzzy membership value; F(x i )——quantitative value of the evaluation standard of the indicator.

6. The method for evaluating energy efficiency of a gas field gathering and transportation pipeline system with a two-level station layout strategy according to claim 1 is characterized in that: In step (4), the linear weighted method calculation steps are as follows: The evaluation scores of the secondary and primary indicators are calculated by the linear weighted method. The calculation formula of the secondary indicator evaluation value is shown in formula (17), and the calculation formula of the primary indicator evaluation value is shown in formula (18): Where U i ——Evaluation score of the ith secondary indicator; U ij ——The quantitative value of the evaluation standard of the jth third-level indicator in the i-th second-level indicator; ω ij ——The weight of the jth third-level indicator in the i-th second-level indicator; U——Evaluation score of the first-level indicator; U i ——The evaluation score of the i-th secondary indicator in the primary indicator; ω i ——The weight of the i-th secondary indicator in the primary indicator.

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