A salt cavern gas storage well site micro-leakage detection point optimization method and device

Abstract

The application provides a salt cavern gas storage well site micro-leakage detection point position optimization method and device, which combines wind data and similar equipment failure data to determine the comprehensive occurrence probability of a random leakage scene, and obtains a three-dimensional concentration field according to the diffusion law of the leaked gas in the well site. The comprehensive occurrence probability and the three-dimensional concentration field are used to quantitatively determine the probability of successfully monitoring the leaked gas, and a constraint condition is constructed for the optimal point position of the well site gas leakage monitoring by using the combination of the gas monitoring mode and the monitoring point position setting factor. The optimal gas leakage monitoring equipment layout scheme is output through the constraint condition. The application can establish a "point + line" monitoring point position optimization scheme combining multiple monitoring modes, thereby providing an optimal solution for the leakage monitoring of the salt cavern gas storage, and ensuring the long-term safe and efficient operation of the salt cavern gas storage.

Description

Technical Field

[0001] This invention mainly relates to the field of leakage detection technology for salt cavern gas storage well sites, specifically to a method and device for optimizing micro-leakage detection points in salt cavern gas storage well sites. Background Technology

[0002] Natural gas in salt cavern gas storage facilities possesses characteristics such as high temperature, high pressure, and flammability and explosiveness. Once a leak occurs and comes into contact with air, it can easily trigger serious secondary disasters such as fires. Micro-leakage monitoring at the well site is one of the key means to ensure the safe and stable operation of salt cavern gas storage facilities. However, the deployment of existing gas leak monitoring equipment is mostly based on standards such as SY6503-2000 "Specifications for the Use of Combustible Gas Detection Alarms" and SY-6503-2008 "Safety Technical Specifications for Combustible Gas Detection Alarm Systems in Petroleum and Natural Gas Engineering," without providing more detailed specifications for the operational characteristics of equipment at salt cavern gas storage well sites. Currently, the selection of leak monitoring points still largely relies on the experience of field engineers, lacking comprehensive and systematic gas leak simulation methods and optimal monitoring point selection methods, resulting in application problems such as low monitoring accuracy and wasted deployment.

[0003] The currently disclosed technical methods in this field do not take into account the influence of the external environment. Well sites are open and are more severely affected by the external environment, especially wind speed and direction. The diffusion law of gas leakage is more complex and cannot be comprehensively considered under the constraints of multiple factors such as economy, scene installation, and monitoring accuracy. Therefore, the resulting solutions are not accurate.

[0004] Currently, widely used gas micro-leakage monitoring equipment can be categorized into point-type, spot-shooting, and scanning-path-type equipment based on its monitoring method, and its price is increasing exponentially. Scientific and reasonable selection of monitoring points can not only improve the accuracy of gas leak monitoring but also reduce the number of monitoring points, saving costs. However, the layout of operating equipment at well sites is complex, and potential leak sources mainly include wellheads, valve groups, and injection / production pipelines. These leak sources are widely distributed, and the probability of leakage varies considerably. Therefore, relying on human experience can only yield qualitative inferences; quantitative gas leak simulation methods and methods for optimizing monitoring point selection are urgently needed to achieve optimal equipment utilization. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide a method and device for optimizing the detection points of micro-leakage in salt cavern gas storage well sites, which addresses the shortcomings of the existing technology.

[0006] The technical solution of this invention to solve the above-mentioned technical problems is as follows: A method for optimizing the detection points of micro-leakage in salt cavern gas storage well sites, comprising the following steps:

[0007] Wind data is obtained from the meteorological database of the gas storage well site, and failure data of similar equipment is obtained from the gas leakage database of external salt cavern gas storage. The comprehensive probability of random leakage scenarios is determined based on the wind data and the failure data of similar equipment.

[0008] Based on the distribution rules of the well site equipment, a three-dimensional physical model of the well site is constructed. Taking the leakage source and environmental conditions as random scenarios, the diffusion law of gas in the well site after leakage is analyzed from the three-dimensional physical model of the well site, and the three-dimensional concentration field of the leaked gas distribution in the well site is obtained.

[0009] The probability of successful detection of leaked gas is quantified based on the combined occurrence probability of the random leakage scenario and the three-dimensional concentration field.

[0010] Establish a set of gas monitoring methods, and maximize the probability of successfully detecting the leaked gas based on the set of gas monitoring methods;

[0011] The optimal monitoring points for well site gas leakage are determined by setting the combination of monitoring points based on factors and maximizing the probability of successful monitoring of leaked gas.

[0012] The monitoring probability corresponding to the combination of monitoring points that satisfies the constraints is solved, and the optimal gas leak monitoring equipment deployment scheme is output based on the solution results.

[0013] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: A device for optimizing the detection point of micro-leakage in a salt cavern gas storage well site, comprising the following steps:

[0014] The environmental probability prediction module is used to obtain wind data from the meteorological database of the gas storage well site and similar equipment failure data from the gas leakage database of the external salt cavern gas storage, and determine the comprehensive probability of occurrence of random leakage scenarios based on the wind data and the similar equipment failure data.

[0015] The leakage simulation module is used to construct a three-dimensional physical model of the well site based on the distribution rules of the well site equipment, and to analyze the diffusion law of gas in the well site after leakage occurs from the three-dimensional physical model of the well site, taking the leakage source and environmental conditions as random scenarios, and to obtain the three-dimensional concentration field of the leaked gas distribution in the well site.

[0016] The monitoring probability prediction module is used to quantify the probability of successful monitoring of leaked gas based on the comprehensive occurrence probability of the random leak scenario and the three-dimensional concentration field.

[0017] It is also used to establish a set of gas monitoring methods, and to maximize the probability of the leaked gas being successfully monitored based on the set of gas monitoring methods;

[0018] The site optimization module is used to construct constraints on the optimal sites for monitoring gas leaks at the well site by setting the combination of monitoring sites based on factors and maximizing the probability of successful monitoring of leaked gas.

[0019] It is also used to solve for the monitoring probability corresponding to the combination of monitoring points that meet the constraints, and output the optimal gas leak monitoring equipment deployment scheme based on the solution results.

[0020] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a device for optimizing the detection point of micro-leakage at a well site of a salt cavern gas storage facility, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the method for optimizing the detection point of micro-leakage at a well site of a salt cavern gas storage facility as described above.

[0021] Another technical solution of the present invention to solve the above-mentioned technical problems is as follows: a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for optimizing the micro-leakage detection point of the salt cavern gas storage well site as described above is implemented.

[0022] The beneficial effects of this invention are as follows: It combines wind power data and failure data of similar equipment to determine the comprehensive probability of random leakage scenarios, and obtains a three-dimensional concentration field by analyzing the diffusion law of gas in the well site after leakage. It quantifies the probability of successful monitoring of leaked gas by combining the comprehensive probability of occurrence and the three-dimensional concentration field. It constructs constraints on the optimal monitoring points for gas leakage in the well site by combining gas monitoring methods and monitoring points with set factors. It outputs the optimal gas leakage monitoring equipment deployment scheme through the constraints, and can establish a "point + line" monitoring point optimization scheme that combines multiple monitoring methods. This provides the optimal solution for leakage monitoring of salt cavern gas storage facilities and ensures the long-term safe and efficient operation of salt cavern gas storage facilities. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating the method for optimizing the detection points of micro-leakage in salt cavern gas storage well sites according to an embodiment of the present invention.

[0024] Figure 2 This is a schematic diagram of the functional modules of the salt cavern gas storage well site micro-leakage detection point optimization device provided in an embodiment of the present invention. Detailed Implementation

[0025] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0026] The diffusion pattern of leaked gas within the well site is a crucial factor that needs to be considered in the optimized deployment of monitoring equipment. Salt cavern gas storage well sites have significant unique characteristics compared to traditional factories and warehouses. First, most salt cavern gas storage sites are located in open areas, where wind speed and direction have a significant impact on the diffusion pattern of leaked gas. Second, the operating equipment at the gas storage well site is relatively complex, with significant differences in the leakage probability of each device, exhibiting clear hierarchical characteristics. Therefore, fully considering the unique characteristics of salt cavern gas storage well sites and establishing a gas leakage simulation method that perfectly matches them is the foundation and prerequisite for the optimal selection of monitoring points.

[0027] Related studies have shown that under the cyclic alternating temperature and pressure loads accompanying injection and production, the casing is prone to instability and failure, and the interface between the cement sheath and the casing is also prone to weakening, resulting in gas channeling. Therefore, the risk of gas leakage at the wellhead is the greatest. The valve group area involves frequent switching between injection and production and frequent opening and closing of valves, so the risk of gas leakage in the valve group area is the second highest. As for the injection and production gas pipeline, there is only a low risk of gas leakage at the joint.

[0028] Therefore, it is urgent to conduct corresponding research to address the aforementioned problems and difficulties, clarify the influence of wind speed and direction on gas leakage and diffusion, and establish a simulation method for gas leakage and diffusion in salt cavern gas storage well sites. Furthermore, under the constraints of both economy and accuracy, and based on the leakage risk levels of different operating equipment and the advantages of various monitoring methods, a "point + line" method for optimizing monitoring points should be established, combining multiple monitoring methods. This will provide the optimal solution for leakage monitoring in salt cavern gas storage facilities, ensuring their long-term safe and efficient operation.

[0029] Figure 1 This is a flowchart illustrating the method for optimizing micro-leakage detection points in salt cavern gas storage well sites provided in an embodiment of the present invention.

[0030] Example 1:

[0031] like Figure 1 As shown, a method for optimizing the detection points of micro-leakage at a salt cavern gas storage well site includes the following steps:

[0032] S1. Obtain wind data from the meteorological database of the gas storage well site and obtain similar equipment failure data from the gas leakage database of the external salt cavern gas storage. Determine the comprehensive probability of random leakage scenarios based on the wind data and the similar equipment failure data.

[0033] S2. Construct a three-dimensional physical model of the well site based on the distribution rules of the well site equipment, and analyze the diffusion law of gas in the well site after leakage from the three-dimensional physical model of the well site, taking the leakage source and environmental conditions as random scenarios, to obtain the three-dimensional concentration field of the leaked gas in the well site; specifically, based on the distribution rules of the well site equipment, construct a three-dimensional physical model of the well site through a leakage simulation system, take the leakage source and environmental conditions as random scenarios, analyze the diffusion law of gas in the well site after leakage, and obtain the spatiotemporal distribution of the three-dimensional concentration field of the leaked gas in the well site.

[0034] S3. Quantify the probability of successful monitoring of leaked gas based on the comprehensive occurrence probability of the random leakage scenario and the three-dimensional concentration field.

[0035] S4. Establish a set of gas monitoring methods, and maximize the probability of successfully monitoring the leaked gas based on the set of gas monitoring methods.

[0036] S5. By setting the combination of monitoring points for various factors and maximizing the probability of successful monitoring of leaked gas, constraints are established for the optimal monitoring points for gas leaks at the well site.

[0037] S6. Solve for the monitoring probability corresponding to the combination of monitoring points that satisfy the constraints, and output the optimal gas leak monitoring equipment deployment scheme based on the solution results.

[0038] In the above embodiments, wind data and failure data of similar equipment are combined to determine the comprehensive probability of random leakage scenarios, and the diffusion law of gas in the well site after leakage is obtained to obtain a three-dimensional concentration field. The probability of successful monitoring of leaked gas is quantified by combining the comprehensive probability of occurrence and the three-dimensional concentration field. Constraints are constructed on the optimal gas leakage monitoring points in the well site by combining gas monitoring methods and monitoring points with set factors. The optimal gas leakage monitoring equipment deployment scheme is output through the constraints. It is possible to establish a "point + line" monitoring point optimization scheme that combines multiple monitoring methods, thereby providing the optimal solution for leakage monitoring of salt cavern gas storage and ensuring the long-term safe and efficient operation of salt cavern gas storage.

[0039] Based on the above embodiments, the step of obtaining wind data from the meteorological database of the gas storage well site and obtaining similar equipment failure data from the external salt cavern gas storage gas leakage database, and determining the comprehensive probability of random leakage scenarios based on the wind data and the similar equipment failure data, specifically involves:

[0040] Wind data, including wind speed and direction information, is obtained from a meteorological database at the gas storage well site. A probability model for the distribution of wind direction and wind speed at the gas storage well site is constructed based on this wind data. The probability model for the distribution of wind direction and wind speed is as follows:

[0041] P e =P w P d ,

[0042] Among them, P e P represents the overall probability of the environmental scenario occurring. w P represents the probability of wind direction. d This indicates the probability of the wind speed occurring under the given wind direction;

[0043] Failure data of similar equipment were obtained from the gas leakage database of external salt cavern gas storage facilities. A gas leakage probability model was constructed based on the failure data of similar equipment. The gas leakage probability model is as follows:

[0044]

[0045] Among them, F E and F M P represents the equipment and management correction factors, respectively. q and P z The numbers represent the failure frequencies of similar equipment with leakage orifice diameters of q and z, respectively, where g is the required leakage source orifice diameter in mm; q and z are the left and right end dimensions of the given orifice diameter range in the similar equipment failure database, respectively; the units of the left and right end dimensions are mm.

[0046] Under random wind direction and speed conditions at the gas storage well site, the probability model of wind direction and speed distribution and the probability model of gas leakage are multiplied to obtain the comprehensive probability of occurrence of the random leakage scenario. The comprehensive probability of occurrence is:

[0047] P c =P e P g .

[0048] In the above embodiments, the actual situation is taken into account. The well site is open and is more severely affected by the external environment, especially wind speed and wind direction. The diffusion law of gas leakage is combined to determine the comprehensive probability of random leakage scenarios, which is reliable.

[0049] Based on the above embodiments, the step of quantifying the probability of successful monitoring of leaked gas according to the comprehensive occurrence probability of the random leakage scenario and the three-dimensional concentration field specifically includes:

[0050] Construct a scenario set consisting of environmental scenarios and leakage sources;

[0051] Monitor the environmental concentration of leaked gas in the environment and obtain the accuracy of the monitoring equipment;

[0052] Based on the scenario set consisting of the environmental scene and the leak source, the environmental concentration monitored by the three-dimensional concentration field, the accuracy of the monitoring equipment, and the comprehensive occurrence probability, a successful leak gas monitoring probability model is constructed. The successful leak gas monitoring probability model is as follows:

[0053]

[0054] Where L(e,g) represents the set of scenarios consisting of environmental scenarios and leakage sources, and C s C represents the monitored environmental concentration. t Indicates the accuracy threshold of the monitoring equipment;

[0055] When the monitored environmental concentration C s Greater than the accuracy threshold C of the monitoring equipment t If the condition is met, the probability of successful monitoring is 1; otherwise, it is 0.

[0056] Based on the above embodiments, the step of establishing a set of gas monitoring methods and maximizing the probability of successfully detecting the leaked gas according to the set of gas monitoring methods specifically involves:

[0057] A set of gas monitoring methods is established based on point-based, line-based, and scanning path-based methods. This set of gas monitoring methods is as follows:

[0058]

[0059] Where L(p), L(l), and L(f) represent the sets of point-based, line-based, and scanning path-based gas monitoring methods, respectively;

[0060] Maximize the probability of successful detection of the leaked gas based on the set of gas monitoring methods L(m):

[0061] maxP = max{P i ,i∈L(m)}.

[0062] Based on the above embodiments, the following factors need to be considered: the optimal location of gas leakage monitoring points at the well site of salt cavern gas storage facilities is limited by various factors, mainly including: 1) Economic efficiency: Although the probability of successful monitoring increases with the density of monitoring points, the increase becomes smaller and smaller; 2) It is necessary to ensure that the probability of monitoring meets the minimum threshold for leakage monitoring; 3) It is necessary to consider the installation location of existing equipment at the well site to ensure that the monitoring points are feasible to install and are not limited by the original equipment and injection / production operations at the well site. Therefore, the constraints are:

[0063]

[0064] Among them, C i (i∈L(m))≤C maxThis indicates monitoring point C set up based on economic factors. i The density is less than or equal to the maximum density C at the monitoring point. max The higher the density of monitoring points, the greater the probability of successful monitoring, P≥P min This means maximizing the probability that the leaked gas is successfully detected to be greater than or equal to (i.e., satisfying) the minimum threshold P for leak detection. min L(a) represents the available equipment installation paths at the well site.

[0065] In the above embodiments, an optimization method for gas leak monitoring points is established with factors such as economy, installation scenario, and monitoring accuracy as common constraints. This method has high reliability and provides the optimal solution for leak monitoring in salt cavern gas storage facilities, ensuring the long-term safe and efficient operation of these facilities.

[0066] Figure 2 This is a schematic diagram of the functional modules of the salt cavern gas storage well site micro-leakage detection point optimization device provided in an embodiment of the present invention.

[0067] Example 2:

[0068] like Figure 2 As shown, a device for optimizing micro-leakage detection points in salt cavern gas storage well sites includes the following steps:

[0069] The environmental probability prediction module is used to obtain wind data from the meteorological database of the gas storage well site and similar equipment failure data from the gas leakage database of the external salt cavern gas storage, and determine the comprehensive probability of occurrence of random leakage scenarios based on the wind data and the similar equipment failure data.

[0070] The leakage simulation module is used to construct a three-dimensional physical model of the well site based on the distribution rules of the well site equipment, and to analyze the diffusion law of gas in the well site after leakage occurs from the three-dimensional physical model of the well site, taking the leakage source and environmental conditions as random scenarios, and to obtain the three-dimensional concentration field of the leaked gas distribution in the well site.

[0071] The monitoring probability prediction module is used to quantify the probability of successful monitoring of leaked gas based on the comprehensive occurrence probability of the random leak scenario and the three-dimensional concentration field.

[0072] It is also used to establish a set of gas monitoring methods, and to maximize the probability of the leaked gas being successfully monitored based on the set of gas monitoring methods;

[0073] The site optimization module is used to construct constraints on the optimal sites for monitoring gas leaks at the well site by setting the combination of monitoring sites based on factors and maximizing the probability of successful monitoring of leaked gas.

[0074] It is also used to solve for the monitoring probability corresponding to the combination of monitoring points that meet the constraints, and output the optimal gas leak monitoring equipment deployment scheme based on the solution results.

[0075] In the above embodiments, wind data and failure data of similar equipment are combined to determine the comprehensive probability of random leakage scenarios, and the diffusion law of gas in the well site after leakage is obtained to obtain a three-dimensional concentration field. The probability of successful monitoring of leaked gas is quantified by combining the comprehensive probability of occurrence and the three-dimensional concentration field. Constraints are constructed on the optimal gas leakage monitoring points in the well site by combining gas monitoring methods and monitoring points with set factors. The optimal gas leakage monitoring equipment deployment scheme is output through the constraints. It is possible to establish a "point + line" monitoring point optimization scheme that combines multiple monitoring methods, thereby providing the optimal solution for leakage monitoring of salt cavern gas storage and ensuring the long-term safe and efficient operation of salt cavern gas storage.

[0076] The environmental probability prediction module obtains wind data from the meteorological database of the gas storage well site and similar equipment failure data from the external salt cavern gas storage gas leakage database. Based on the wind data and the similar equipment failure data, it determines the comprehensive probability of random leakage scenarios, specifically as follows:

[0077] Wind data, including wind speed and direction information, is obtained from a meteorological database at the gas storage well site. A probability model for the distribution of wind direction and wind speed at the gas storage well site is constructed based on this wind data. The probability model for the distribution of wind direction and wind speed is as follows:

[0078] P e =P w P d ,

[0079] Among them, P e P represents the overall probability of the environmental scenario occurring. w P represents the probability of wind direction. d This indicates the probability of the wind speed occurring under the given wind direction;

[0080] Failure data of similar equipment were obtained from the gas leakage database of external salt cavern gas storage facilities. A gas leakage probability model was constructed based on the failure data of similar equipment. The gas leakage probability model is as follows:

[0081]

[0082] Among them, F E and F M P represents the equipment and management correction factors, respectively. q and P zLet q and z represent the failure frequencies of similar equipment with leakage orifice diameters of q and z, respectively, and g be the diameter of the leakage source; q and z are the left and right end dimensions of the given orifice diameter range in the failure database of similar equipment, respectively.

[0083] Under random wind direction and speed conditions at the gas storage well site, the probability model of wind direction and speed distribution and the probability model of gas leakage are multiplied to obtain the comprehensive probability of occurrence of the random leakage scenario. The comprehensive probability of occurrence is:

[0084] P c =P e P g .

[0085] In the above embodiments, the actual situation is taken into account. The well site is open and is more severely affected by the external environment, especially wind speed and wind direction. The diffusion law of gas leakage is combined to determine the comprehensive probability of random leakage scenarios, which is reliable.

[0086] In the monitoring probability prediction module, the probability of successful monitoring of leaked gas is quantified based on the comprehensive occurrence probability of the random leak scenario and the three-dimensional concentration field. Specifically:

[0087] Construct a scenario set consisting of environmental scenarios and leakage sources;

[0088] Monitor the environmental concentration of leaked gas in the environment and obtain the accuracy of the monitoring equipment;

[0089] Based on the scenario set consisting of the environmental scene and the leak source, the environmental concentration monitored by the three-dimensional concentration field, the accuracy of the monitoring equipment, and the comprehensive occurrence probability, a successful leak gas monitoring probability model is constructed. The successful leak gas monitoring probability model is as follows:

[0090]

[0091] Where L(e,g) represents the set of scenarios consisting of environmental scenarios and leakage sources, and C s C represents the monitored environmental concentration. t Indicates the accuracy threshold of the monitoring equipment;

[0092] When the monitored environmental concentration C s Greater than the accuracy threshold C of the monitoring equipment t If the condition is met, the probability of successful monitoring is 1; otherwise, it is 0.

[0093] In the monitoring probability prediction module, a set of gas monitoring methods is established, and the probability of successfully detecting the leaked gas is maximized based on the set of gas monitoring methods. Specifically:

[0094] A set of gas monitoring methods is established based on point-based, line-based, and scanning path-based methods. This set of gas monitoring methods is as follows:

[0095]

[0096] Where L(p), L(l), and L(f) represent the sets of point-based, line-based, and scanning path-based gas monitoring methods, respectively;

[0097] Maximize the probability of successful detection of the leaked gas based on the set of gas monitoring methods L(m):

[0098] maxP = max{P i ,i∈L(m)}.

[0099] The constraints are as follows:

[0100]

[0101] Among them, C i (i∈L(m))≤C max This indicates monitoring point C set up based on economic factors. i The density is less than or equal to the maximum density C at the monitoring point. max The higher the density of monitoring points, the greater the probability of successful monitoring, P≥P min This indicates that the probability of successfully detecting the leaked gas is maximized to be greater than or equal to the minimum threshold P for leak detection. min L(a) represents the available equipment installation paths at the well site.

[0102] In the above embodiments, an optimization method for gas leak monitoring points is established with factors such as economy, installation scenario, and monitoring accuracy as common constraints. This method has high reliability and provides the optimal solution for leak monitoring in salt cavern gas storage facilities, ensuring the long-term safe and efficient operation of these facilities.

[0103] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0104] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing the detection points of micro-leakage at well sites in salt cavern gas storage facilities, characterized in that, Includes the following steps: Wind data is obtained from the meteorological database of the gas storage well site, and failure data of similar equipment is obtained from the gas leakage database of external salt cavern gas storage. The comprehensive probability of random leakage scenarios is determined based on the wind data and the failure data of similar equipment. Based on the distribution rules of the well site equipment, a three-dimensional physical model of the well site is constructed. Taking the leakage source and environmental conditions as random scenarios, the diffusion law of gas in the well site after leakage is analyzed from the three-dimensional physical model of the well site, and the three-dimensional concentration field of the leaked gas distribution in the well site is obtained. The probability of successful detection of leaked gas is quantified based on the combined occurrence probability of the random leakage scenario and the three-dimensional concentration field. Establish a set of gas monitoring methods, and maximize the probability of successfully detecting the leaked gas based on the set of gas monitoring methods; The optimal monitoring points for well site gas leakage are determined by setting the combination of monitoring points based on factors and maximizing the probability of successful monitoring of leaked gas. The monitoring probability corresponding to the combination of monitoring points that satisfy the constraints is solved, and the optimal gas leak monitoring equipment deployment scheme is output based on the solution results. The process involves obtaining wind data from a meteorological database at the gas storage well site location and obtaining similar equipment failure data from a gas leakage database of external salt cavern gas storage facilities. Based on the wind data and the similar equipment failure data, the overall probability of a random leakage scenario is determined, specifically as follows: Wind data, including wind speed and direction information, is obtained from a meteorological database at the gas storage well site. A probability model for the distribution of wind direction and speed at the gas storage well site is constructed based on this wind data. The probability model for the distribution of wind direction and speed is as follows: ， Among them, P e P represents the overall probability of the environmental scenario occurring. w P represents the probability of wind direction. d This indicates the probability of the wind speed occurring under the given wind direction; Failure data of similar equipment were obtained from the gas leakage database of external salt cavern gas storage facilities. A gas leakage probability model was constructed based on the failure data of similar equipment. The gas leakage probability model is as follows: ， Among them, F E and F M P represents the correction factor. q and P z Let q and z represent the failure frequencies of similar equipment with leakage orifice diameters of q and z, respectively, and g be the diameter of the leakage source; q and z are the left and right end dimensions of the given orifice diameter range in the failure database of similar equipment, respectively. Under random wind direction and speed conditions at the gas storage well site, the probability model of wind direction and speed distribution and the probability model of gas leakage are multiplied to obtain the comprehensive probability of occurrence of the random leakage scenario. The comprehensive probability of occurrence is: 。 2. The method for optimizing the detection points of micro-leakage at salt cavern gas storage well sites according to claim 1, characterized in that, The method of quantifying the probability of successful detection of leaked gas based on the comprehensive occurrence probability of the random leak scenario and the three-dimensional concentration field is as follows: Construct a scenario set consisting of environmental scenarios and leakage sources; Monitor the environmental concentration of leaked gas in the environment and obtain the accuracy of the monitoring equipment; Based on the scenario set consisting of the environmental scene and the leak source, the environmental concentration monitored by the three-dimensional concentration field, the accuracy of the monitoring equipment, and the comprehensive occurrence probability, a successful leak gas monitoring probability model is constructed. The successful leak gas monitoring probability model is as follows: ， Where L(e,g) represents the set of scenarios consisting of environmental scenarios and leakage sources, and C s C represents the monitored environmental concentration. t Indicates the accuracy threshold of the monitoring equipment; When the monitored environmental concentration C s Greater than the accuracy threshold C of the monitoring equipment t If the condition is met, the probability of successful monitoring is 1; otherwise, it is 0.

3. The method for optimizing the detection points of micro-leakage at salt cavern gas storage well sites according to claim 1, characterized in that, The establishment of a set of gas monitoring methods, and the maximization of the probability of successful detection of the leaked gas based on the set of gas monitoring methods, specifically involves: A set of gas monitoring methods is established based on point-based, line-based, and scanning path-based methods. This set of gas monitoring methods is as follows: ， Where L(p), L(l), and L(f) represent the sets of point-based, line-based, and scanning path-based gas monitoring methods, respectively; Maximize the probability of successful detection of the leaked gas based on the set of gas monitoring methods L(m): 。 4. The method for optimizing the detection points of micro-leakage at salt cavern gas storage well sites according to claim 3, characterized in that, The constraints are as follows: ， in, This indicates the monitoring points set up based on economic factors. The density is less than or equal to the maximum density at the monitoring point. The higher the density of monitoring points, the greater the probability of successful monitoring. This means that the probability of successfully detecting the leaked gas is maximized to be greater than or equal to the minimum threshold for leak detection. L(a) represents the available equipment installation paths at the well site.

5. A device for optimizing the detection points of micro-leakage at well sites in salt cavern gas storage facilities, characterized in that, Includes the following steps: The environmental probability prediction module is used to obtain wind data from the meteorological database of the gas storage well site and failure data of similar equipment from the gas leakage database of the external salt cavern gas storage. Based on the wind data and the failure data of similar equipment, the module determines the comprehensive probability of occurrence of random leakage scenarios. The leakage simulation module is used to construct a three-dimensional physical model of the well site based on the distribution rules of the well site equipment, and to analyze the diffusion law of gas in the well site after leakage occurs from the three-dimensional physical model of the well site, taking the leakage source and environmental conditions as random scenarios, and to obtain the three-dimensional concentration field of the leaked gas distribution in the well site. The monitoring probability prediction module is used to quantify the probability of successful monitoring of leaked gas based on the comprehensive occurrence probability of the random leak scenario and the three-dimensional concentration field. It is also used to establish a set of gas monitoring methods, and to maximize the probability of the leaked gas being successfully monitored based on the set of gas monitoring methods; The site optimization module is used to construct constraints on the optimal sites for monitoring gas leaks at the well site by setting the combination of monitoring sites based on factors and maximizing the probability of successful monitoring of leaked gas. It is also used to solve the monitoring probability corresponding to the combination of monitoring points that meet the constraints, and output the optimal gas leak monitoring equipment deployment scheme based on the solution results. The environmental probability prediction module obtains wind data from the meteorological database of the gas storage well site and similar equipment failure data from the external salt cavern gas storage gas leakage database. Based on the wind data and the similar equipment failure data, it determines the comprehensive probability of random leakage scenarios, specifically as follows: Wind data, including wind speed and direction information, is obtained from a meteorological database at the gas storage well site. A probability model for the distribution of wind direction and speed at the gas storage well site is constructed based on this wind data. The probability model for the distribution of wind direction and speed is as follows: ， Among them, P e P represents the overall probability of the environmental scenario occurring. w P represents the probability of wind direction. d This indicates the probability of the wind speed occurring under the given wind direction; Failure data of similar equipment were obtained from the gas leakage database of external salt cavern gas storage facilities. A gas leakage probability model was constructed based on the failure data of similar equipment. The gas leakage probability model is as follows: ， Among them, F E and F M P represents the correction factor. q and P z Let q and z represent the failure frequencies of similar equipment with leakage orifice diameters of q and z, respectively, and g be the diameter of the leakage source; q and z are the left and right end dimensions of the given orifice diameter range in the failure database of similar equipment, respectively. Under random wind direction and speed conditions at the gas storage well site, the probability model of wind direction and speed distribution and the probability model of gas leakage are multiplied to obtain the comprehensive probability of occurrence of the random leakage scenario. The comprehensive probability of occurrence is: 。 6. The device for optimizing the detection point of micro-leakage at the well site of a salt cavern gas storage facility according to claim 5, characterized in that, In the monitoring probability prediction module, the probability of successful monitoring of leaked gas is quantified based on the comprehensive occurrence probability of the random leak scenario and the three-dimensional concentration field. Specifically: Construct a scenario set consisting of environmental scenarios and leakage sources; Monitor the environmental concentration of leaked gas in the environment and obtain the accuracy of the monitoring equipment; Based on the scenario set consisting of the environmental scene and the leak source, the environmental concentration monitored by the three-dimensional concentration field, the accuracy of the monitoring equipment, and the comprehensive occurrence probability, a successful leak gas monitoring probability model is constructed. The successful leak gas monitoring probability model is as follows: ， Where L(e,g) represents the set of scenarios consisting of environmental scenarios and leakage sources, and C s C represents the monitored environmental concentration. t Indicates the accuracy threshold of the monitoring equipment; When the monitored environmental concentration C s Greater than the accuracy threshold C of the monitoring equipment t If the condition is met, the probability of successful monitoring is 1; otherwise, it is 0.

7. The device for optimizing the detection point of micro-leakage at the well site of a salt cavern gas storage facility according to claim 5, characterized in that, In the monitoring probability prediction module, a set of gas monitoring methods is established, and the probability of successfully detecting the leaked gas is maximized based on the set of gas monitoring methods. Specifically: A set of gas monitoring methods is established based on point-based, line-based, and scanning path-based methods. This set of gas monitoring methods is as follows: ， Where L(p), L(l), and L(f) represent the sets of point-based, line-based, and scanning path-based gas monitoring methods, respectively; Maximize the probability of successful detection of the leaked gas based on the set of gas monitoring methods L(m): 。 8. The device for optimizing the detection point of micro-leakage at the well site of a salt cavern gas storage facility according to claim 7, characterized in that, The constraints are as follows: ， in, This indicates the monitoring points set up based on economic factors. The density is less than or equal to the maximum density at the monitoring point. The higher the density of monitoring points, the greater the probability of successful monitoring. This means that the probability of successfully detecting the leaked gas is maximized to be greater than or equal to the minimum threshold for leak detection. L(a) represents the available equipment installation paths at the well site.

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