A multi-level weight evaluation method for wellhead cleaning and heating optimization scheme

Abstract

The application provides a multilevel weight evaluation method for wellhead clean heating optimization scheme, and belongs to the technical field of oilfield wellhead heating. The technical scheme is as follows: a multilevel weight evaluation method for wellhead clean heating optimization scheme comprises the following steps: establishing a wellhead heating test platform, establishing a multilevel evaluation system, the first layer is a criterion layer including technical benefits, economic benefits and social benefits; the technical benefits include primary energy utilization rate, technical maturity and equipment maintainability; the economic benefits include investment, operation cost and investment recovery period; the social benefits include resource availability, policy support and balanced energy structure; the weights of the three criterion layers are determined by experts; the weights of each sublayer index are determined by using independent weights; the comprehensive scores of all schemes are calculated, and the highest score is the optimal scheme. The application is based on the wellhead heating test platform, simulates field conditions, is accurate in data, and can objectively and accurately evaluate the wellhead clean heating optimization scheme.

Description

Technical Field

[0001] This invention relates to the field of oilfield wellhead heating technology, and in particular to a multi-level weighted evaluation method for optimizing wellhead clean heating schemes. Background Technology

[0002] Currently, traditional energy sources are the main source of heating energy for oilfield production systems, accounting for over 90% of the total. Wellhead heating, an essential process in crude oil extraction and transportation, consumes a significant amount of energy; for example, approximately 40% of the annual production energy consumption of the Shengli Oilfield production system is consumed in heating.

[0003] With the advancement of national low-carbon and environmental protection policies, the demand for domestic gas is increasing, and emission standards are becoming increasingly stringent. This has limited the use of single-well gas-fired heaters, the primary heating method employed at oilfield well sites. The gas source for these heaters mainly consists of casing gas and pipeline dry gas, with supply and demand varying significantly with seasonal peaks and valleys. Winter demand is 1.7 times that of summer, while supply is only 4 / 5 of summer, leading to increasingly tight gas supplies in winter. Furthermore, the regulation and management of well site heaters are difficult, and their thermal efficiency is low. Electric heating offers stable energy supply and is currently the most feasible alternative for oilfield wellhead heating, but it suffers from high operating costs. Upgrading wellhead heating equipment with clean energy is a promising solution, but the conditions at wellheads and in different formations are complex. Multiple heating methods necessitate diverse composite heating solutions. The key is selecting a suitable solution from among numerous clean heating options. Currently, researchers often rely on experience from other wellheads or direct field experiments to choose solutions. Blindly replacing or testing solutions inevitably leads to losses of manpower and resources, potentially disrupting normal on-site operations, and cannot guarantee the superiority of the chosen solution. Summary of the Invention

[0004] To address the problems in the prior art, the present invention aims to provide a multi-level weighted evaluation method for wellhead clean heating optimization schemes. Based on the simulation of actual wellhead working conditions, a wellhead heating test platform is established, and a multi-level weighted evaluation method is established for various clean heating schemes. The optimal scheme is determined by comprehensive scores, ensuring the objectivity and accuracy of the upgrade scheme.

[0005] This invention is achieved through the following technical solution: an evaluation method for upgrading wellhead heating equipment, comprising the following steps:

[0006] Step S1: Develop multiple alternative heating schemes and simulate the heat load at the wellhead based on the heating requirements at the wellhead;

[0007] Step S2: Establish a wellhead heating test platform. The wellhead heating test platform includes a heating unit, a phase change thermal storage unit, a wellhead simulated heat load, and a heating control system. The heating unit includes multiple heating devices arranged in parallel. Each heating device corresponds to a heating alternative scheme and is connected in parallel with the phase change thermal storage unit. The heating control system can select any heating device to store heat for the phase change thermal storage unit. The phase change thermal storage unit can release heat to supply heat for the wellhead simulated heat load.

[0008] Step S3: Using the wellhead heating test platform, conduct heat load tests on all heating alternatives and eliminate heating alternatives that do not meet the heating requirements.

[0009] Step S4: Establish a hierarchical evaluation system for the heating system. The first layer is the target layer, which is the selection of alternative heating schemes. The second layer is the criterion layer, which evaluates alternative heating schemes based on three criteria: technical benefits, economic benefits, and social benefits. The third layer is the indicator layer, which includes sub-indicators corresponding to each criterion.

[0010] Step S5: Obtain the sub-layer indicators of each heating alternative scheme based on the wellhead heating test platform;

[0011] Step S6: Apply the independence weighting coefficient method to assign correlation weights to the various sub-indicators for obtaining technical, economic, and social benefits.

[0012] Step S7: Determine the weights of technical benefits, economic benefits, and social benefits in the second-level criteria layer;

[0013] Step S8: Calculate the comprehensive score of each heating alternative scheme based on steps S6 and S7.

[0014] Step S9: The heating alternative with the highest overall score is the optimal solution.

[0015] The wellhead heating test platform employs a phase change thermal energy storage unit, which is configured according to the characteristics of clean energy. Directly replacing the current electric heating mode with clean energy is difficult to achieve. However, by combining clean energy such as solar energy and geothermal energy with phase change thermal energy storage technology to form a composite clean heating solution, it is possible to ensure continuous and stable output on the demand side while significantly reducing electricity costs during off-peak hours when prices are low. The clean heating solution is based on clean energy combined with phase change thermal energy storage technology. The wellhead heating test platform can test and verify the above-mentioned clean heating solution.

[0016] To enable off-site testing, the wellhead heating test platform is equipped with a simulated wellhead heat load. Based on the actual wellhead operating conditions and required information, including but not limited to the required heat load, water source, and power consumption limitations, the wellhead heating method is determined according to the mixed oil conditions. There are two methods: direct heating and indirect heating. Furthermore, the simulated wellhead heat load includes a water tank (first tank), a water tank (second tank), a water tower, a water pump, and several solenoid valves located at nodes, all connected by pipelines. Water tank (second tank) contains a coil. Controlling the solenoid valves allows the simulated wellhead heat load to switch operating modes, including direct heating and indirect heating. In direct heating, the high-temperature medium flows from the phase change thermal storage unit into water tank (first tank), is cooled by the water tower, and then circulates back to the phase change thermal storage unit for heat exchange. In indirect heating, the high-temperature medium flows from the phase change thermal storage unit into the coil. The medium in the water tower continuously circulates between water tank (second tank) and the water tower to cool the coil, and after cooling, it circulates back to the phase change thermal storage unit for heat exchange. The function of the water tower is to dissipate heat, so that when the wellhead heating test platform is heated by the circulating medium and then refluxes, it is close to the constant temperature water intake condition in the actual working condition. The medium circulation adopts the conventional technology of pressurizing circulation by configuring a water pump in the pipeline, which will not be described in detail.

[0017] Furthermore, all of the aforementioned heating devices utilize clean energy sources, including PTC, solar energy, and dual-source heat pumps.

[0018] Furthermore, the sub-indicators corresponding to the technical benefits mentioned in step S4 include primary energy utilization rate, technology maturity, and equipment maintainability; the sub-indicators corresponding to the economic benefits include investment, operating costs, and investment payback period; and the sub-indicators corresponding to the social benefits include resource availability, policy support, and balanced energy structure.

[0019] The term "technology maturity" refers to the degree of industrial applicability of energy supply equipment in terms of its technical level, process flow, supporting resources, and technology life cycle. The comprehensive evaluation system for clean heating systems mainly involves three heating methods: solar heating, PTC heating, and dual-source heat pump heating. Solar heating technology is very mature and commercialized; dual-source heat pump technology is widely used and mature. PTC heating consumes a lot of energy, but it regulates temperature through its own material properties, eliminating the need for dedicated temperature controllers and temperature sensors such as resistance thermometers and thermocouples for temperature feedback. It has a long product lifespan, and its development is accelerating with the optimization of PTC materials. Expert evaluation is used for scoring.

[0020] The maintainability of the equipment is divided into equipment reliability and equipment repairability. Reliability ensures that the equipment can function properly for a long time, minimizing or eliminating malfunctions, reducing maintenance work and costs, and reducing losses caused by downtime. Solar heating systems have a simple structure, low operating costs, low maintenance costs, and require no dedicated operation and management personnel; dual-source heat pump systems are relatively complex, with relatively high operating and maintenance costs; PTC heating systems have low operating and maintenance costs; expert evaluation is used for scoring.

[0021] Economic benefits often play a crucial role in determining the feasibility of an engineering project and are the most important indicator for investors across all evaluation criteria. They are typically assessed using secondary economic evaluation indicators such as initial investment, operating costs, and payback period. The initial investment under actual operating conditions is calculated based on the heating equipment selected in the clean heating scheme matched to the wellhead test platform. This investment covers the purchase cost, installation cost, and other related engineering construction costs of each piece of equipment.

[0022] C t,c =∑I n C a

[0023] In the formula: C a For the amount spent; I n The unit price is the cost.

[0024] The operating costs include operating energy costs and maintenance costs.

[0025] O=P×Q×η

[0026] Where P is the price of energy required for heating by the heating equipment; η is the energy conversion efficiency of the heating equipment; η is the efficiency of the heating method; Q is the total annual heat load.

[0027] The investment payback period is as follows:

[0028]

[0029] In the formula: T represents the system's payback period. Y1 and Y2 represent the residual value of the equipment before and after the initial upgrade, respectively. O1 and O2 represent the annual operating costs before and after the upgrade, respectively.

[0030] Resource availability refers to the analysis of local available energy resources, including municipal power grid, solar energy resources and sunshine duration, geothermal resources, etc., with values ​​ranging from [0-1]. Power grid reliability is scored, with 0 for meeting the minimum solar energy requirement and 1 for the optimal local sunshine duration, based on the sunshine duration published by the local meteorological bureau. Geothermal resources are scored based on their availability and reliability.

[0031] The policy support is based on performance data obtained from policy subsidies in recent years, divided into one-time equipment subsidies (W1) and resource continuity subsidies (W2), and linear equations are established for each scheme. The resource continuity subsidy (W2) for the current year is predicted. The policy subsidy for N years of operation is...

[0032]

[0033] The aforementioned balanced energy structure involves determining the clean heating system scheme, identifying the off-peak and peak electricity periods for industrial use, and the duration of sunshine. At the same time, it involves designing an auxiliary heating and thermal storage system based on the characteristics of solar energy resources to reduce electricity costs.

[0034] All the above sub-layer indicators are determined based on the scheme adopted by the wellhead heating test platform, and each sub-layer indicator is quantified to ensure the objectivity and accuracy of the heating system hierarchical evaluation system, which has high guiding significance.

[0035] Furthermore, performance parameters can be directly obtained through the wellhead heating test platform, quickly verifying whether the current clean heating scheme meets the heating requirements. This also provides directly obtainable sub-layer indicators for subsequent evaluation, which is efficient and intuitive. The calculation process for the primary energy utilization rate is as follows:

[0036]

[0037] Where: PER is the primary energy utilization rate, Q H Q E These represent the system's heat output and power consumption, respectively; COP is the coefficient of performance in a heat pump system; η ε φ represents the average efficiency of a traditional coal-fired power plant; φ represents the power grid transmission line loss rate.

[0038] The heating control system includes sensors for detecting the pressure, flow rate, and temperature of each heating device, and solenoid valves for switching each heating device. All parameters in step S51 can be obtained through the heating control system.

[0039] Furthermore, step 6 specifically involves:

[0040] S61, aggregate the same sub-layer indexes from different heating alternative schemes into a sub-layer index set X = [x1, x2, x...]. i …x n ], where n is the number of alternative heating schemes;

[0041] S62, calculate the variance of all elements in the sub-layer index set X as follows:

[0042] in is the mean of all elements in the sub-level index set X;

[0043] S63, standardize each element in the sub-layer index set X to obtain the dimensionless sub-layer index corresponding to the i-th heating alternative scheme in the sub-layer index set X.

[0044]

[0045] S64, Establish a dimensionless sub-layer index set for the k-th sub-layer index. Then the multiple correlation coefficient of the k-th sub-level index relative to the other sub-level indices is: in For dimensionless sublayer index set The i-th element in This represents the mean of all elements in the dimensionless sub-layer index set. For dimensionless sublayer index set The regression value;

[0046] S65. Calculate the multiple correlation coefficient R between the k-th sub-level index and other sub-level indices. k The reciprocal of 1 / R k Normalization is performed.

[0047] S66. The weight of the k-th sub-layer index is obtained as follows:

[0048] S67. Obtain the weighted scores of each sub-level index using the independence weighting coefficient method, F i =1 / R` i *X i F i This represents the weight score of the sub-level index corresponding to the i-th heating alternative scheme in the sub-level index set X.

[0049] Furthermore, step S7 specifically involves establishing an evaluation team composed of technical experts, operators, and auditors to conduct a qualitative analysis of technical, economic, and social benefits based on past project experience and the current project situation, and to determine the weight of each benefit at the criteria level.

[0050] Furthermore, step S8 specifically includes:

[0051] S81. Based on the weighted scores Fi of all sub-level indicators belonging to the i-th heating alternative scheme obtained in step S67, the sub-level indicators are reordered and divided according to the subordinate relationship between the second and third levels. Sub-level indicators under the same criterion are numbered starting from 1 and denoted as F. jm , representing the score of the m-th sub-level index under the j-th criterion;

[0052] S82. Calculate the comprehensive score S of the i-th scheme. i =∑∑(Z) j ×F jm ), where Zj This represents the weight of the j-th criterion.

[0053] The specific calculation of the overall score for a given solution is shown in the table below:

[0054]

[0055] Furthermore, the overall scores of all heating alternatives are compared, and the heating alternative with the highest overall score is the optimal solution.

[0056] The beneficial effects of this invention are as follows: The evaluation method described in this invention, combined with the wellhead heating test platform, can objectively and accurately evaluate clean heating schemes; the evaluation method based on multi-level weights quantitatively measures the heating scheme, and tests the performance of the scheme on the experimental platform. The theory and practice complement and verify each other, providing researchers with a scientific and reasonable basis for selecting heating schemes, saving on-site experimental costs and time, and avoiding researchers blindly selecting heating schemes; the scoring system is established based on the three criteria of technical benefits, economic benefits, and social benefits scored by experts, as well as the sub-level indicators of their independence weight coefficients, ensuring the accuracy and superiority of the evaluation method. Attached Figure Description

[0057] Figure 1 This is a flowchart of the hierarchical evaluation system for heating systems.

[0058] Figure 2 This is a flowchart of the evaluation method.

[0059] Figure 3 This is a process connection diagram of the wellhead heating test platform.

[0060] Attached reference numerals: 11. Water tank one; 12. Water tank two; 13. Coil; 14. Water tower; 15. Water pump; 21. Solar energy; 22. PTC; 23. Dual-source heat pump; 24. Phase change thermal storage unit; 25. Other heating; 30. Solenoid valve. Detailed Implementation

[0061] To clearly illustrate the technical features of this solution, the following detailed implementation method will be used to explain the solution.

[0062] See Figures 1-3 Example 1: This invention is achieved through the following technical solution: a multi-level weighted evaluation method for wellhead clean heating optimization schemes, comprising the following steps:

[0063] Step S1: Develop multiple alternative heating schemes and simulate the heat load at the wellhead based on the heating requirements at the wellhead;

[0064] Step S2: Establish a wellhead heating test platform. The wellhead heating test platform includes a heating unit, a phase change thermal storage unit 24, a wellhead simulated heat load and a heating control system. The heating unit includes multiple heating devices arranged in parallel. Each heating device corresponds to a heating alternative scheme and is connected in parallel with the phase change thermal storage unit 24. The heating control system can select any heating device to store heat for the phase change thermal storage unit 24. The phase change thermal storage unit 24 can release heat to supply heat for the wellhead simulated heat load.

[0065] Step S3: Using the wellhead heating test platform, conduct heat load tests on all heating alternatives and eliminate heating alternatives that do not meet the heating requirements.

[0066] Step S4: Establish a hierarchical evaluation system for the heating system. The first layer is the target layer, which is the selection of alternative heating schemes. The second layer is the criterion layer, which evaluates alternative heating schemes based on three criteria: technical benefits, economic benefits, and social benefits. The third layer is the indicator layer, which includes sub-indicators corresponding to each criterion.

[0067] Step S5: Obtain the sub-layer indicators of each heating alternative scheme based on the wellhead heating test platform;

[0068] Step S6: Apply the independence weighting coefficient method to assign correlation weights to the various sub-indicators for obtaining technical, economic, and social benefits.

[0069] Step S7: Determine the weights of technical benefits, economic benefits, and social benefits in the second-level criteria layer;

[0070] Step S8: Calculate the comprehensive score of each heating alternative scheme based on steps S6 and S7.

[0071] Step S9: The heating alternative with the highest overall score is the optimal solution.

[0072] The wellhead heating test platform employs a phase change thermal energy storage unit 24, which is configured according to the characteristics of clean energy. Directly replacing the current electric heating mode with clean energy is difficult to achieve. However, by combining clean energy such as solar energy and geothermal energy with phase change thermal energy storage technology to form a composite clean heating solution, it is possible to ensure continuous and stable output on the demand side while significantly reducing electricity costs during off-peak hours when prices are low. The clean heating solution is based on clean energy combined with phase change thermal energy storage technology. The wellhead heating test platform can test and verify the above-mentioned clean heating solution.

[0073] To enable off-site testing, the wellhead heating test platform is equipped with a simulated wellhead heat load. Based on the actual wellhead operating conditions and required information, including but not limited to the required heat load, water source, and power consumption limitations, the wellhead heating method varies depending on the mixed oil fluid; there are two methods: direct heating and indirect heating. Furthermore, the simulated wellhead heat load includes a water tank 11, a water tank 2 12, a water tower 14, a water pump 15, and several solenoid valves 30 located at nodes, all connected by pipelines. The water tank 2 12 contains a coil 13, which is controlled by... The switching combination of the solenoid valve 30 can switch the working mode of the simulated heat load at the wellhead. The working mode includes direct heating and indirect heating. In direct heating, the high-temperature medium flows from the phase change heat storage unit 24 into the water tank 11, then passes through the water tower 14 for heat dissipation, and then circulates back to the phase change heat storage unit 24 for heat exchange. In indirect heating, the high-temperature medium flows from the phase change heat storage unit 24 into the coil 13. The medium in the water tower 14 continuously circulates between the water tank 12 and the water tower 14 to dissipate heat from the coil 13. After heat dissipation, the high-temperature medium circulates back to the phase change heat storage unit 24 for heat exchange. The function of the water tower 14 is to dissipate heat, so that the wellhead heating test platform, after the circulating medium has finished heating, returns to a condition close to the constant temperature water intake condition in actual working conditions. The medium circulation uses a water pump 15 configured in the pipeline for pressurized circulation, which is a conventional technology and will not be described in detail.

[0074] Furthermore, the sub-indicators corresponding to the technical benefits mentioned in step S4 include primary energy utilization rate, technology maturity, and equipment maintainability; the sub-indicators corresponding to the economic benefits include investment, operating costs, and investment payback period; and the sub-indicators corresponding to the social benefits include resource availability, policy support, and balanced energy structure.

[0075] Technology maturity refers to the degree of industrial applicability of energy supply equipment in terms of its technical level, process flow, supporting resources, and technology life cycle. The comprehensive evaluation system for clean heating systems mainly involves three heating methods: solar heating, PTC heating, and dual-source heat pump heating. Solar heating technology is very mature and commercialized; dual-source heat pump technology is widely used and mature. PTC heating consumes a lot of energy, but it regulates temperature through its own material properties, eliminating the need for dedicated temperature controllers and temperature sensors such as resistance thermometers and thermocouples for temperature feedback. It has a long product lifespan, and its development is accelerating with the optimization of PTC materials. Expert evaluation is used for scoring.

[0076] The maintainability of the equipment is divided into equipment reliability and equipment repairability. Reliability ensures that the equipment can function properly for a long time, minimizing or eliminating malfunctions, reducing maintenance work and costs, and reducing losses caused by downtime. Solar heating systems have a simple structure, low operating costs, low maintenance costs, and require no dedicated operation and management personnel; dual-source heat pump systems are relatively complex, with relatively high operating and maintenance costs; PTC heating systems have low operating and maintenance costs; expert evaluation is used for scoring.

[0077] Economic benefits often play a crucial role in determining the feasibility of an engineering project and are the most important indicator for investors across all evaluation criteria. They are typically assessed using secondary economic evaluation indicators such as initial investment, operating costs, and payback period. The initial investment under actual operating conditions is calculated based on the heating equipment selected in the clean heating scheme matched to the wellhead test platform. This investment covers the purchase cost, installation cost, and other related engineering construction costs of each piece of equipment.

[0078] C t,c =∑I n C a

[0079] In the formula: C a For the amount spent; I n The unit price is the cost.

[0080] The operating costs include operating energy costs and maintenance costs.

[0081] O=P×Q×η

[0082] Where P is the price of energy required for heating by the heating equipment; η is the energy conversion efficiency of the heating equipment; η is the efficiency of the heating method; Q is the total annual heat load.

[0083] The investment payback period is as follows:

[0084]

[0085] In the formula: T represents the system's payback period. Y1 and Y2 represent the residual value of the equipment before and after the initial upgrade, respectively. O1 and O2 represent the annual operating costs before and after the upgrade, respectively.

[0086] Resource availability refers to the analysis of local available energy resources, including municipal power grid, solar energy resources and sunshine duration, geothermal resources, etc., with values ​​ranging from [0-1]. Power grid reliability is scored, with 0 for meeting the minimum solar energy requirement and 1 for the optimal local sunshine duration, based on the sunshine duration published by the local meteorological bureau. Geothermal resources are scored based on their availability and reliability.

[0087] The policy support is based on performance data obtained from policy subsidies in recent years, divided into one-time equipment subsidies (W1) and resource continuity subsidies (W2), and linear equations are established for each scheme. The resource continuity subsidy (W2) for the current year is predicted. The policy subsidy for N years of operation is...

[0088]

[0089] The aforementioned balanced energy structure involves determining the clean heating system scheme, identifying the off-peak and peak electricity periods for industrial use, and the duration of sunshine. At the same time, it involves designing an auxiliary heating and thermal storage system based on the characteristics of solar energy resources to reduce electricity costs.

[0090] All the above sub-layer indicators are determined based on the scheme adopted by the wellhead heating test platform, and each sub-layer indicator is quantified to ensure the objectivity and accuracy of the heating system hierarchical evaluation system, which has high guiding significance.

[0091] Furthermore, performance parameters can be directly obtained through the wellhead heating test platform, quickly verifying whether the current clean heating scheme meets the heating requirements. This also provides directly obtainable sub-layer indicators for subsequent evaluation, which is efficient and intuitive. The calculation process for the primary energy utilization rate is as follows:

[0092]

[0093] Where: PER is the primary energy utilization rate, Q H Q E These represent the system's heat output and power consumption, respectively; COP is the coefficient of performance in a heat pump system; η ε φ represents the average efficiency of a traditional coal-fired power plant; φ represents the power grid transmission line loss rate; the heating control system includes sensors for detecting the pressure, flow rate, and temperature of each heating device, and solenoid valves 30 for switching each heating device. All of the above parameters can be obtained through the heating control system.

[0094] Furthermore, step S6 specifically includes:

[0095] S61, aggregate the same sub-layer indexes from different heating alternative schemes into a sub-layer index set X = [x1, x2, x...]. i …x n ], where n is the number of alternative heating schemes;

[0096] S62, calculate the variance of all elements in the sub-layer index set X as follows:

[0097] in is the mean of all elements in the sub-level index set X;

[0098] S63, standardize each element in the sub-layer index set X to obtain the dimensionless sub-layer index corresponding to the i-th heating alternative scheme in the sub-layer index set X.

[0099]

[0100] S64, Establish a dimensionless sub-layer index set for the k-th sub-layer index. Then the multiple correlation coefficient of the k-th sub-level index relative to the other sub-level indices is: in For dimensionless sublayer index set The i-th element in This represents the mean of all elements in the dimensionless sub-layer index set. For dimensionless sublayer index set The regression value;

[0101] S65. Calculate the reciprocal of the multiple correlation coefficient Rk between the k-th sub-level index and other sub-level indices, 1 / Rk. k Normalization is performed.

[0102] S66. The weight of the k-th sub-layer index is obtained as follows:

[0103] S67. Obtain the weighted scores of each sub-level index using the independence weighting coefficient method, F i =1 / R` i *X i F i This represents the weight score of the sub-level index corresponding to the i-th heating alternative scheme in the sub-level index set X.

[0104] Furthermore, step S7 specifically involves establishing an evaluation team composed of technical experts, operators, and auditors to conduct a qualitative analysis of technical, economic, and social benefits based on past project experience and the current project situation, and to determine the weight of each benefit at the criteria level.

[0105] Furthermore, step S8 specifically includes:

[0106] S81. Based on the weighted scores Fi of all sub-level indicators belonging to the i-th heating alternative scheme obtained in step S67, the sub-level indicators are reordered and divided according to the subordinate relationship between the second and third levels. Sub-level indicators under the same criterion are numbered starting from 1 and denoted as F. jm , representing the score of the m-th sub-level index under the j-th criterion;

[0107] S82. Calculate the comprehensive score S of the i-th scheme. i =∑∑(Z) j ×F jm ), where Z jThis represents the weight of the j-th criterion.

[0108] The specific calculation of the overall score for a given solution is shown in the table below:

[0109]

[0110]

[0111] Furthermore, the overall scores of all heating alternatives are compared, and the heating alternative with the highest overall score is the optimal solution.

[0112] Example 2, based on Example 1, includes multiple heating devices such as a PTC 22, solar energy 21, and a dual-source heat pump 23. The wellhead heating test platform can also reserve interfaces for other heating methods 25. All heating devices are connected in parallel. The heat storage process of each heating device in the wellhead heating test platform is as follows: 1. Close the valve between the phase change heat storage unit 24 and the simulated heat load at the wellhead. The heat exchange medium passes through the PTC... 2) After heating, the medium enters the phase change thermal storage unit 24, where it exchanges heat with the phase change thermal storage material, and the phase change thermal storage unit 24 stores heat. 2) The valve between the phase change thermal storage unit 24 and the simulated heat load at the wellhead is closed. After being heated by solar energy 21, the medium enters the phase change thermal storage unit 24, where it exchanges heat with the phase change thermal storage material, and the phase change thermal storage unit 24 stores heat. 3) The valve between the phase change thermal storage unit 24 and the simulated heat load at the wellhead is closed. The medium enters the dual-source heat pump 23. When the ambient temperature is high, an air source is used to heat the medium, and the medium exchanges heat with the phase change thermal storage material. The phase change thermal storage unit 24 absorbs the high-temperature medium's heat energy and stores heat. When the ambient temperature is low, a water source is used to heat the medium, and the medium exchanges heat with the phase change thermal storage material, and the phase change thermal storage unit 24 stores heat.

[0113] Heat release process: 1) Close the solenoid valve 30 of the heating equipment and the simulated heat load at the wellhead. Select the simulated heat load at the wellhead to be in the indirect heating or direct heating working mode according to the actual situation. The high temperature heat exchange medium flows from the phase change heat storage unit 24 into the simulated heat load at the wellhead. After being cooled by the water tower 14, it flows back to the phase change heat storage unit 24 for heat exchange again.

[0114] Example 3: Based on Example 2, the present invention is used to evaluate three clean heating schemes: the corresponding indicators for each scheme are as follows:

[0115] Option A-PTC: Energy utilization rate is 1 / 3, technology maturity is 1, and maintainability is 0.8;

[0116] Option B - Dual-source heat pump: Energy utilization rate is 2 / 3, technology maturity is 1, and maintainability is 0.7;

[0117] Option C-PTC and solar energy: Energy utilization rate is 2 / 3, technology maturity is 0.8, and maintainability is 0.8;

[0118] Standardize the sub-level indicators: For schemes A, B, and C, the average energy utilization rate is calculated according to the formula... The calculated value is 0.444444, and the standard deviation is calculated using the formula... The calculated value is 0.19245, according to the formula. The dimensionless sublayer indices of energy utilization efficiency were obtained as -0.57735, 1.154701, and -0.57735, respectively.

[0119] Similarly, for schemes A, B, and C, the mean technology maturity is 0.933333, the standard deviation is 0.11547, and the dimensionless sub-indices of technology maturity are 0.57735, 0.57735, and -1.1547, respectively; the mean maintainability is 0.733333, the standard deviation is 0.11547, and the dimensionless sub-indices of maintainability are 0.57735, -1.1547, and 0.57735, respectively.

[0120] The independence weighting method is adopted according to the formula. The weights of the sub-layers are calculated as R. 11 =R 12 =R 13 =1, calculate the reciprocal of the multiple correlation coefficient (1 / R) between each indicator and other indicators. 11 =1 / R 12 =1 / R 13 =1. According to the formula Normalizing the reciprocal of the correlation coefficient yields the weight 1 / R' of each indicator. 11 =1 / R` 12 =1 / R` 13 =1 / 3.

[0121] The weights of each indicator are obtained using the independence weighting method, and then calculated according to formula F. i =1 / R` i *X i The final scores are shown in the table below:

[0122] plan Energy utilization rate Technology maturity Maintainability Option A -0.190 0.190 0.190 Option B 0.381 0.190 -0.381 Option C -0.190 -0.381 0.190

[0123] Similarly, the scores for the remaining two sub-layers are obtained (the smaller the economic indicators of investment, operating costs, and investment payback period, the better; the inverse is taken before standardization).

[0124] plan invest Operating costs Investment recovery period Option A -0.031 -0.340 -0.136 Option B -0.313 0.020 -0.240 Option C 0.344 0.319 0.376

[0125] plan Resource availability Policy support Balanced energy structure Option A 0.33 -0.300 -0.381 Option B 0 -0.054 0.191 Option C -0.33 0.354 0.191

[0126] Technical, economic, and social criteria were assessed using expert scoring, with weights of [0.333; 0.570; 0.097].

[0127] In summary, the total score for each plan is calculated using the formula. have to

[0128]

[0129]

[0130] As can be seen from the table above, among the three options, option C has better performance across all indicators.

[0131] Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0132] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "setting" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0133] The technical features of this invention not described can be implemented by or using existing technology, and will not be repeated here. Of course, the above description is not a limitation of this invention, and this invention is not limited to the examples above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of this invention should also be within the protection scope of this invention.

Claims

1. A multi-level weighted evaluation method for optimizing wellhead cleaning heating schemes, characterized in that, Includes the following steps: Step S1: Develop multiple alternative heating schemes and simulate the heat load at the wellhead based on the heating requirements at the wellhead; Step S2: Establish a wellhead heating test platform. The wellhead heating test platform includes a heating unit, a phase change thermal storage unit, a wellhead simulated heat load, and a heating control system. The heating unit includes multiple heating devices arranged in parallel. Each heating device corresponds to a heating alternative scheme and is connected in parallel with the phase change thermal storage unit. The heating control system can select any heating device to store heat for the phase change thermal storage unit. The phase change thermal storage unit can release heat to supply heat for the wellhead simulated heat load. Step S3: Using the wellhead heating test platform, conduct heat load tests on all heating alternatives and eliminate heating alternatives that do not meet the heating requirements. Step S4: Establish a hierarchical evaluation system for the heating system. The first target layer is the selection of alternative heating schemes. The second layer is the criteria layer, which evaluates heating alternatives based on three criteria: technical benefits, economic benefits, and social benefits; the third layer is the indicator layer, which includes sub-indicators corresponding to each criterion. Step S5: Obtain the sub-layer indicators of each heating alternative scheme based on the wellhead heating test platform; Step S6: Apply the independence weighting coefficient method to assign correlation weights to the various sub-indicators for obtaining technical, economic, and social benefits. Step S7: Determine the weights of technical benefits, economic benefits, and social benefits in the second-level criteria layer; Step S8: Calculate the comprehensive score of each heating alternative scheme based on steps S6 and S7. Step S9: The heating alternative with the highest overall score is the optimal solution.

2. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 1, characterized in that, The simulated heat load at the wellhead includes a water tank (first tank), a water tank (second tank), a water tower, a water pump, and several solenoid valves located at nodes, all connected by pipelines. The water tank (second tank) contains a coil. By controlling the switching combination of the solenoid valves, the operating mode of the simulated heat load at the wellhead can be switched. The operating modes include direct heating and indirect heating. In direct heating, the high-temperature medium flows from the phase change thermal storage unit into the water tank (first tank), then is cooled by the water tower before circulating back to the phase change thermal storage unit for heat exchange. In indirect heating, the high-temperature medium flows from the phase change thermal storage unit into the coil. The medium in the water tower continuously circulates between the water tank (second tank) and the water tower to cool the coil. After cooling, the high-temperature medium circulates back to the phase change thermal storage unit for heat exchange.

3. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 1, characterized in that, The various heating devices include PTC, solar energy, and dual-source heat pumps.

4. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 2, characterized in that, The sub-indicators corresponding to the technical benefits include primary energy utilization rate, technology maturity, and equipment maintainability; the sub-indicators corresponding to the economic benefits include investment, operating costs, and investment payback period; and the sub-indicators corresponding to the social benefits include resource availability, policy support, and balanced energy structure.

5. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 4, characterized in that, The calculation process for the primary energy utilization rate is as follows: Where: PER is the primary energy utilization rate, Q H Q E These represent the system's heat output and power consumption, respectively; COP is the coefficient of performance for a heat pump system; η ε φ represents the average efficiency of a traditional coal-fired power plant; φ represents the power grid transmission line loss rate.

6. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 5, characterized in that, Step 6 specifically involves: S61, aggregate the same sub-layer indexes from different heating alternative schemes into a sub-layer index set X = [x1, x2, x...]. i …x n ], where n is the number of alternative heating schemes; S62, calculate the variance of all elements in the sub-layer index set X as follows: in is the mean of all elements in the sub-level index set X; S63, standardize each element in the sub-layer index set X to obtain the dimensionless sub-layer index corresponding to the i-th heating alternative scheme in the sub-layer index set X. S64, Establish a dimensionless sub-layer index set for the k-th sub-layer index. The multiple correlation coefficient of the k-th sub-level index relative to the other sub-level indices is: in For dimensionless sublayer index set The i-th element in This represents the mean of all elements in the dimensionless sub-layer index set. For dimensionless sublayer index set The regression value; S65. Calculate the multiple correlation coefficient R between the k-th sub-level index and other sub-level indices. k The reciprocal of 1 / R k Normalization is performed. S66. The weight of the k-th sub-layer index is obtained as follows: S67. Obtain the weighted scores of each sub-level index using the independence weighting coefficient method, F i =1 / R` i *X i F i This represents the weight score of the sub-level index corresponding to the i-th heating alternative scheme in the sub-level index set X.

7. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 6, characterized in that, Specifically, step S7 involves establishing an evaluation team composed of technical experts, operators, and auditors to conduct a qualitative analysis of the technical, economic, and social benefits based on past project experience and the current project situation, and to determine the weight of each benefit at the criteria level.

8. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 7, characterized in that, Step S8 is as follows: S81. Based on the weighted scores Fi of all sub-level indicators belonging to the i-th heating alternative scheme obtained in step S67, the sub-level indicators are reordered and divided according to the subordinate relationship between the second and third levels. Sub-level indicators under the same criterion are numbered starting from 1 and denoted as F. jm , representing the score of the m-th sub-level index under the j-th criterion; S82. Calculate the comprehensive score S of the i-th scheme. i =∑∑(Z) j ×F jm ), where Z j This represents the weight of the j-th criterion.

9. The multi-level weighted evaluation method for the wellhead clean heating optimization scheme according to claim 8, characterized in that, Compare the overall scores of all heating alternatives, and the heating alternative with the highest overall score is the optimal solution.

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