A monitoring method for the sealing property of gypsum-salt caprock in gas storage reservoirs

Abstract

The present invention discloses a method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage reservoir, which includes: collecting the information of the gypsum-salt caprock during the operation of the gas storage reservoir in an oil and gas field for a certain storage time, and determining the stable interval value of the wellhead and formation pressure per unit time at the depth of the abnormal position for sealing performance monitoring; determining the safe pore pressure value according to the caprock thickness at the depth of the abnormal position for sealing performance monitoring and the safe position depth within the variation range of the safe pore pressure; performing calculations on the distribution laws of fractures and faults for the gypsum-salt caprock information to obtain the sealing performance monitoring permeability at different temperatures; determining the influencing factors of the rock structure of the gypsum-salt caprock information, and obtaining the stable interval value of the wellhead and formation pressure to be monitored according to the rock structure, the influence weights of different factors such as the fluctuations of the wellhead and formation pressure, and the stable interval value of the wellhead and formation pressure with high sealing performance, and judging the gas leakage condition of the gas storage reservoir in the oil and gas field according to the stable interval value of the wellhead and formation pressure to be monitored. The present invention can effectively improve the safety of the sealing performance monitoring of the gas storage reservoir.

Description

Technical Field

[0001] The present invention relates to the field of monitoring the sealing performance of gas storage caverns, and particularly to a method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage cavern. Background Art

[0002] Gas storage caverns play an important role in energy storage and management, especially in providing stable supply during peak gas demand periods. In a gas storage cavern, the gypsum-salt caprock, as a key sealing structure, mainly functions to prevent gas leakage from the gas storage cavern and maintain the stability of the reservoir. The integrity of this caprock directly affects the safety of the gas storage cavern, the gas storage capacity, and the reliability of long-term operation. To ensure the effectiveness of the caprock, accurate sealing performance monitoring must be carried out. Such monitoring can not only reveal the physical and chemical properties of the caprock but also evaluate its performance under different operating conditions, such as pressure changes and temperature fluctuations. This is crucial for preventing potential leakage risks and optimizing the operation of the gas storage cavern. Therefore, developing an efficient and reliable sealing performance monitoring method is of great significance for enhancing the safety and operation efficiency of gas storage caverns.

[0003] Although there are currently various technologies for monitoring the sealing performance of gypsum-salt caprocks, these methods still have some obvious drawbacks. Traditional monitoring technologies usually rely on static data collection and limited geological models, and this method often fails to comprehensively capture the actual performance of the caprock in a dynamic environment. Due to the lack of effective utilization of real-time data, these methods are difficult to reflect the changes of the caprock under different pressure and temperature conditions. Secondly, many existing technologies have limitations in detecting microfractures and faults inside the caprock, and they often can only provide relatively rough monitoring data and cannot accurately identify potential structural defects. Such limitations may lead to inaccurate judgment of the actual condition of the caprock, thus increasing the risk of gas leakage and making the management and maintenance of gas storage caverns more complex. In addition, existing monitoring systems may be difficult to handle and analyze large-scale data, unable to provide real-time early warnings and adjustment suggestions, which makes it difficult for the operators of gas storage caverns to respond to potential problems in a timely manner.

[0004] To overcome these technical defects, it is urgent to develop an advanced method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage cavern. This new method should combine real-time data collection and dynamic analysis technologies to overcome the limitations of existing monitoring technologies. By integrating high-precision monitoring instruments and efficient data processing algorithms, it is possible to achieve comprehensive monitoring of the caprock state. This can not only improve the ability to identify minor defects of the caprock but also provide more accurate monitoring results under different operating conditions, thereby enhancing the safety and operation efficiency of gas storage caverns. This improved monitoring method will provide more reliable data support for the management and maintenance of gas storage caverns, reduce potential leakage risks, and ensure the long-term stable operation of gas storage caverns. Summary of the Invention

[0005] In order to solve the technical problem that the recognition effect of rock formation activities in related technologies is poor, which in turn leads to insufficient accuracy and reliability in the monitoring of the sealing performance of dynamic balance gas leakage, the present invention provides a method for monitoring the sealing performance of a plaster salt caprock in a gas storage reservoir. The specific technical solution adopted is as follows:

[0006] The present invention proposes a method for monitoring the sealing performance of a plaster salt caprock in a gas storage reservoir. The method includes:

[0007] Using a multi-modal monitoring and sensing device to collect the information of the plaster salt caprock during the operation of the oil and gas field gas storage reservoir within the storage time. Taking the depths at different altitudes within the storage time as the depths of abnormal positions for sealing performance monitoring, and the information of the plaster salt caprock at the depths of abnormal positions for sealing performance monitoring as the abnormal data for sealing performance monitoring. Using the abnormal data for sealing performance monitoring and the monitoring point information compliant with the temperature jump interval at different altitudes of the depth of the abnormal position for sealing performance monitoring, to determine the stable interval value of the wellhead and formation pressure per unit time at the depth of the abnormal position for sealing performance monitoring;

[0008] Determine the safe pore pressure change range of the plaster salt caprock information. At different altitudes, take the depth of the high-sealing position compliant with the temperature jump interval of the depth of the abnormal position for sealing performance monitoring as the safe depth. Using the safe pore pressure change range and the caprock thickness at the depth of the abnormal position for sealing performance monitoring and the safe depth, to determine the safe pore pressure value at the depth of the abnormal position for sealing performance monitoring; Using the stable interval value of the wellhead and formation pressure per unit time at the depth of the abnormal position for sealing performance monitoring, the safe pore pressure value, and the stable interval value of the wellhead and formation pressure per unit time of the plaster salt caprock information at all safe depths, to determine the stable interval value of the high-sealing wellhead and formation pressure at the depth of the abnormal position for sealing performance monitoring;

[0009] Perform calculations on the distribution laws of fractures and faults of the plaster salt caprock information to obtain the medium and low-sealing monitoring permeabilities. Calculate the porosity from the permeabilities of the sealing performance monitoring at different temperatures. Monitor the rock pore diameters of the permeabilities of the sealing performance monitoring at different temperatures. According to the porosity of the permeabilities of the sealing performance monitoring at different temperatures and the compliance threshold within the temperature jump interval of the depth of the abnormal position for sealing performance monitoring that matches the permeabilities of the sealing performance monitoring at different temperatures, integrate the influence weights of different factors on the wellhead and formation pressure fluctuations at the depth of the abnormal position for sealing performance monitoring;

[0010] Integrate the influencing factors of the rock structure of the plaster salt caprock information according to the caprock thickness of the permeabilities of the sealing performance monitoring at different temperatures at different depths. Using the rock structure, the influence weights of different factors on the wellhead and formation pressure fluctuations, and the stable interval value of the high-sealing wellhead and formation pressure, to obtain the stable interval value of the wellhead and formation pressure to be monitored at the depth of the abnormal position for sealing performance monitoring. Use the stable interval value of the wellhead and formation pressure to be monitored to judge the gas leakage condition of the oil and gas field gas storage reservoir.

[0011] Further, the step of determining the stable interval value of the wellhead and formation pressure per unit time at the depth of the closed monitoring abnormal position by using the abnormal data monitored by the closure and the monitoring point information compliant with the altitude temperature jump interval at a depth different from the depth of the closed monitoring abnormal position includes:

[0012] Calculating the monitoring point information compliant with the altitude temperature jump interval at a depth different from the depth of the closed monitoring abnormal position by using a logistic regression model; integrating the classification results of the abnormal data monitored by the closure with different regression coefficients as the monitoring abnormal influence nodes; and using the normalized result of the data of the monitoring abnormal influence nodes as the stable interval value of the wellhead and formation pressure per unit time at the depth of the closed monitoring abnormal position.

[0013] Further, the step of determining the safety pore pressure value at the depth of the closed monitoring abnormal position by using the caprock thickness within the safety pore pressure change range at the depths of the closed monitoring abnormal position and the safety position includes:

[0014] After performing a correlation analysis on the deposition rates of the caprock thickness within the safety pore pressure change range at the depths of the closed monitoring abnormal position and the safety position, using the result as the safety pore pressure value at the depth of the closed monitoring abnormal position.

[0015] Further, the step of determining the stable interval value of the high-closure wellhead and formation pressure at the depth of the closed monitoring abnormal position by using the stable interval value of the wellhead and formation pressure per unit time at the depth of the closed monitoring abnormal position, the safety pore pressure value, and the stable interval value of the wellhead and formation pressure per unit time of all the gypsum-salt caprock information at the depths of the safety positions includes:

[0016] Integrating the median of the stable interval value of the wellhead and formation pressure per unit time of the gypsum-salt caprock information at the depths of the safety positions as the normal benchmark of the wellhead and formation pressure;

[0017] Integrating the convolution of the normal benchmark of the wellhead and formation pressure and the safety pore pressure, and using the normalized result as the influence weight of different factors on the wellhead and formation pressure fluctuation;

[0018] Obtaining the stable interval value of the high-closure wellhead and formation pressure by using the influence weight of different factors on the wellhead and formation pressure fluctuation and the stable interval value of the wellhead and formation pressure per unit time. The influence weight of different factors on the wellhead and formation pressure fluctuation and the stable interval value of the high-closure wellhead and formation pressure are in a probability relationship, and the stable interval value of the wellhead and formation pressure per unit time and the stable interval value of the high-closure wellhead and formation pressure are in a probability relationship.

[0019] Further, the calculation of the fracture and fault distribution laws for the gypsum-salt caprock information to obtain the medium and low sealing monitoring permeability includes:

[0020] Perform fracture and fault distribution law calculation processing on the gypsum-salt caprock information according to the fracture and fault distribution law calculation algorithm to obtain the injection and production rates and volumes of different types of wellheads and formation pressures at the same altitude; calculate the remaining volume of the injection and production rates and volumes of different types of wellheads and formation pressures with medium and low sealing to obtain the sealing monitoring permeability at different temperatures.

[0021] Further, the integration of the porosity of the sealing monitoring permeability at different temperatures and the compliance threshold of the temperature jump interval at the depth of the sealing monitoring abnormal position within the sealing monitoring permeability at different temperatures, including the influence weights of different factors of the wellhead and formation pressure fluctuations at the depth of the sealing monitoring abnormal position, includes:

[0022] Analyze the three-dimensional stress-strain relationship of the porosity using Hooke's law to obtain the stress state of the porous rock formation;

[0023] Integrate the maximum value per unit time within the compliance threshold of the temperature jump interval at the depth of the sealing monitoring abnormal position in the sealing monitoring permeability at different temperatures and porosities at different altitudes as the sealing monitoring abnormal jump limit value, and convolve the sealing monitoring abnormal jump limit value with the stress state of the porous rock formation as the stress change interval;

[0024] Use the attention mechanism to analyze the stress change intervals of all porosities and the data normalization results to obtain the influence weights of different factors of the wellhead and formation pressure fluctuations.

[0025] Further, the integration of the rock structure influencing factors of the gypsum-salt caprock information according to the caprock thickness of the sealing monitoring permeability at different position depths includes:

[0026] Use the random forest model to integrate the penetration rates of the sealing monitoring permeability at different temperatures according to the caprock thickness of the sealing monitoring permeability at different position depths;

[0027] Use the Pearson correlation coefficient to analyze the compaction degree of fractures and caprocks for the penetration rates of all sealing monitoring permeabilities at different temperatures as the rock structure influencing factors of the gypsum-salt caprock information.

[0028] Further, there is a conditional relationship between the rock structure and the stable interval value of the formation pressure at the wellhead to be monitored at the depth of the abnormal position of the sealing monitoring. There is a probability relationship between the influence weights of different factors on the wellhead and formation pressure fluctuations, the stable interval value of the high-sealing wellhead and formation pressure, and the stable interval value of the wellhead to be monitored at the depth of the abnormal position of the sealing monitoring. The value of the stable interval value of the wellhead to be monitored is the value after data normalization.

[0029] Further, using the stable interval value of the wellhead to be monitored to judge the gas leakage condition of the gas storage reservoir in the oil and gas field includes: when the stable interval value of the wellhead to be monitored is greater than the limit value of the stable interval value of the safety wellhead and formation pressure, it is determined that gas leakage occurs during the operation of the gas storage reservoir in the oil and gas field; when the stable interval value of the wellhead to be monitored is lower than the limit value of the stable interval value of the safety wellhead and formation pressure, it is determined that the operation safety state of the gas storage reservoir in the oil and gas field is safe.

[0030] Further, the algorithm for calculating the distribution law of fractures and faults uses the finite element method to analyze the influence of fractures and faults on formation pressure and stress, simulate the influence of fractures and faults on fluid flow, and complete the calculation and processing of the distribution law of fractures and faults in the gypsum salt caprock information.

[0031] Beneficial effects:

[0032] The present invention provides a method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage reservoir. Through local analysis of the gypsum-salt caprock information, the stable interval value of the wellhead and formation pressure per unit time is determined based on the abnormal data of the sealing performance monitoring and the information of the monitoring points that comply with the altitude temperature jump interval at different depths from the abnormal position of the sealing performance monitoring. Since through the analysis of the safety pore pressure, the average pore pressure of each surrounding point can be used to reduce the influence of the pore pressure of accidental pore pressure on the analysis result of the wellhead and formation pressure fluctuation. Combining the stable interval value of the wellhead and formation pressure per unit time, the safety pore pressure value, and the stable interval value of the wellhead and formation pressure per unit time of the gypsum-salt caprock information at all safe position depths, the high-sealing wellhead and formation pressure stable interval value at the depth of the abnormal position of the sealing performance monitoring is determined. It can analyze all safe position depths locally from multiple angles, so as to obtain a high-sealing wellhead and formation pressure stable interval value with better reliability. By calculating the distribution law of fractures and faults, the sealing performance at different temperatures is monitored and analyzed, so as to obtain the influence weight of different factors on the wellhead and formation pressure fluctuation at the depth of the abnormal position of the sealing performance monitoring. Furthermore, based on the rock structure, the influence weight of different factors, and the high-sealing wellhead and formation pressure stable interval value, the stable interval value of the wellhead and formation pressure to be monitored at the depth of the abnormal position of the sealing performance monitoring is obtained, so that the stable interval value of the wellhead and formation pressure to be monitored can more accurately characterize the wellhead and formation pressure fluctuation at the depth of the abnormal position of the sealing performance monitoring. The present invention can judge the gas leakage condition of the gas storage reservoir in the oil and gas field according to the stable interval value of the wellhead and formation pressure to be monitored, and improve the analysis ability within different altitudes of gas leakage. The present invention uses a multi-modal sensor to collect data in real time and accurately, avoiding data collection errors, and performing correlation, different influence weight, and fracture and fault distribution law calculation and analysis on the collected data through a variety of different algorithms and models, ensuring that all influencing factors related to gas leakage can be effectively analyzed. The present invention can effectively improve the recognition effect of rock layer activities and improve the safety and accuracy of the sealing performance monitoring of the gas storage reservoir. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, form a part of this application, and do not constitute a limitation to the embodiments of the present invention. In the drawings:

[0034] Figure 1 is a flowchart of a method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage reservoir according to the present invention;

[0035] Figure 2 is a composition diagram of the operation modules of a method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage reservoir according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments may be combined with each other. The present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] As Figure 1 shown, it shows a flowchart of a method for monitoring the sealing performance of a gypsum-salt caprock in a gas storage reservoir provided by an embodiment of the present invention. The method includes:

[0038] Step S100: Use a multimodal monitoring and sensing device to collect information on the gypsum-salt caprock during the storage time of the gas storage reservoir in the oil and gas field. Take the depths at different altitudes within the storage time as the depths of abnormal positions for sealing performance monitoring, and the information on the gypsum-salt caprock at the depths of abnormal positions for sealing performance monitoring as the abnormal data for sealing performance monitoring.

[0039] Step S200: Determine the stable interval value of the wellhead and formation pressure per unit time at the depth of the abnormal position for sealing performance monitoring based on the abnormal data for sealing performance monitoring and the monitoring point information that complies with the temperature jump interval at different altitudes corresponding to the depth of the abnormal position for sealing performance monitoring.

[0040] A specific application scenario of the present invention is to determine the location of the gas storage reservoir in the oil and gas field, collect the gypsum-salt caprock conditions at the location of the gas storage reservoir in the oil and gas field during the storage time, so as to obtain the information on the gypsum-salt caprock. It can be understood that during the process of analyzing gas leakage during equipment operation, since rock formation activities can accurately characterize and match the gas leakage conditions during the operation process, therefore, the embodiments of the present invention combine the characteristics of the gypsum-salt caprock itself in the gypsum-salt caprock information and the characteristics of rock formation activities to effectively analyze the rock formation activities, ensuring the accuracy and reliability of the gas leakage analysis during equipment operation. The specific process is described in the subsequent embodiments.

[0041] In the embodiments of the present invention, the types of multimodal sensing devices include, but are not limited to, one of the following, and can be a combination of multiple types or others. Strain sensors, functions: Monitor the strain and stress changes of the caprock. Types: Fiber optic strain sensors, strain gauges. Pressure sensors, functions: Measure the pressure inside the gas storage reservoir and in the caprock. Types: Pressure sensors, piezoelectric sensors. Temperature sensors, functions: Monitor the temperature changes of the caprock and its environment. Types: Thermocouples, thermistors. Porosity sensors, functions: Measure the porosity of the caprock. Types: X-ray computed tomography (CT), nuclear magnetic resonance (NMR) sensors. Permeability sensors, functions: Measure the permeation characteristics of the caprock. Types: Permeameters, micro-permeability test devices. Displacement sensors, functions: Monitor the structural deformation of the caprock. Types: Laser displacement sensors, displacement gauges. Vibration sensors, functions: Detect the vibration and dynamic and static responses of the caprock. Types: Accelerometers, vibration sensors. Acoustic sensors, functions: Monitor the acoustic wave propagation in the caprock for detecting cracks or abnormalities. Types: Acoustic emission sensors, ultrasonic sensors.

[0042] In the embodiments of the present invention, from the extracted gypsum-salt caprock information, any selected position depth is used as the abnormal position depth for sealing monitoring, and the gypsum-salt caprock information at the abnormal position depth for sealing monitoring is used as the abnormal data for sealing monitoring. The abnormal position depth for sealing monitoring and the abnormal data for sealing monitoring are analyzed, so as to traverse all the gypsum-salt caprock information and realize the overall analysis of the gypsum-salt caprock information.

[0043] In some embodiments of the present invention, the rock formation activity usually has the characteristic of large local fluctuations. According to the abnormal data for sealing monitoring and the monitoring point information compliant with the temperature jump interval at different altitudes from the abnormal position depth for sealing monitoring, the stable interval value of the wellhead and formation pressure per unit time at the abnormal position depth for sealing monitoring is determined, including: calculating the monitoring point information compliant with the temperature jump interval at different altitudes from the abnormal position depth for sealing monitoring by using a logistic regression model; integrating the classification results of the abnormal data for sealing monitoring with different regression coefficients as the monitoring abnormal influence nodes; and taking the normalized result of the data of the monitoring abnormal influence nodes as the stable interval value of the wellhead and formation pressure per unit time at the abnormal position depth for sealing monitoring.

[0044] In one embodiment of the present invention, data normalization processing is a preprocessing technique that eliminates the dimensional differences between different features by converting the data into a unified scale range (such as 0 to 1). This processing helps to improve the efficiency and accuracy of model training and prevent certain features from having too much influence on the results. Normalization usually includes methods such as min-max normalization and standardization to make the data meet the requirements of the algorithm and improve the calculation accuracy.

[0045] In the embodiments of the present invention, by integrating the classification results of the abnormal data for sealing monitoring with different regression coefficients as the monitoring abnormal influence nodes, and taking the normalized result of the data of the monitoring abnormal influence nodes as the stable interval value of the wellhead and formation pressure per unit time at the abnormal position depth for sealing monitoring, when the monitoring abnormal influence node is larger, it indicates that there is a large difference between the matched abnormal data for sealing monitoring and the comparison data, that is, the local fluctuation is larger, and then the possibility of the wellhead and formation pressure fluctuation of the abnormal data for sealing monitoring is higher.

[0046] The stable interval value of the wellhead and formation pressure per unit time represents the stable interval value of the wellhead and formation pressure at the abnormal position depth for sealing monitoring that matches, and also represents the possibility of the wellhead and formation pressure fluctuation of the abnormal data for sealing monitoring that matches the abnormal position depth for sealing monitoring. Therefore, the larger the stable interval value of the wellhead and formation pressure per unit time, the greater the possibility that the abnormal data for sealing monitoring is the rock formation activity.

[0047] Step S300: Determine the safe pore pressure change range of the gypsum-salt caprock information. At different altitudes, take the depth of the high-sealing position compliant with the temperature jump interval at the depth of the abnormal position of the sealing monitoring as the safe position depth. According to the safe pore pressure change range and the caprock thickness at the depth of the abnormal position of the sealing monitoring and the safe position depth, determine the safe pore pressure value at the depth of the abnormal position of the sealing monitoring.

[0048] Step S400: According to the stable interval value of the wellhead and formation pressure per unit time at the depth of the abnormal position of the sealing monitoring, the safe pore pressure value, and the stable interval value of the wellhead and formation pressure per unit time of the gypsum-salt caprock information at all safe position depths, determine the high-sealing wellhead and formation pressure stable interval value at the depth of the abnormal position of the sealing monitoring.

[0049] The imbalance of the gas storage in the oil and gas field will cause safe pore pressure in the gypsum-salt caprock information. The more unbalanced the gas storage in the oil and gas field is, the higher the sensitivity to rock layer activities, the greater the degree of safe pore pressure, and the greater the possibility of matching the gypsum-salt caprock information for rock layer activities.

[0050] In the embodiment of the present invention, noise reduction processing can be performed on the gypsum-salt caprock information to obtain the safe pore pressure change range. And at different altitudes, take the depth of the high-sealing position compliant with the temperature jump interval at the depth of the abnormal position of the sealing monitoring as the safe position depth.

[0051] In some embodiments of the present invention, determining the safe pore pressure value at the depth of the abnormal position of the sealing monitoring according to the safe pore pressure change range and the caprock thickness at the depth of the abnormal position of the sealing monitoring and the safe position depth includes: performing a correlation analysis on the deposition rate of the safe pore pressure change range and the caprock thickness at the depth of the abnormal position of the sealing monitoring and the safe position depth, and then using it as the safe pore pressure value at the depth of the abnormal position of the sealing monitoring.

[0052] In order to perform a local analysis on the depth of the abnormal position of the sealing monitoring, therefore, in the embodiment of the present invention, after performing a correlation analysis on the integrated deposition rate of the safe pore pressure change range, the depth of the abnormal position of the sealing monitoring, and the caprock thickness at the safe position depth, it is used as the safe pore pressure value at the depth of the abnormal position of the sealing monitoring. Thus, the safe pore pressure value is used as the local average characteristic value matching the depth of the abnormal position of the sealing monitoring, avoiding the analysis error caused by the fluctuation of the wellhead and formation pressure of the safe pore pressure value at the depth of the abnormal position of the sealing monitoring. At the same time, the local analysis method can effectively characterize the safety situation of the matching local area and improve the reliability of the sealing monitoring.

[0053] In some embodiments of the present invention, the high-closure wellhead and formation pressure stable interval value for the abnormal position depth of the sealing monitoring is determined based on the wellhead and formation pressure stable interval value per unit time for the abnormal position depth of the sealing monitoring, the safe pore pressure value, and the wellhead and formation pressure stable interval value per unit time for the gypsum-salt caprock information at all safe position depths, including: integrating the median of the wellhead and formation pressure stable interval value per unit time for the gypsum-salt caprock information at the safe position depth as the wellhead and formation pressure normal benchmark; integrating the wellhead and formation pressure normal benchmark and the safe pore pressure for convolution, and using the data normalization result as the influence weights of different factors on the wellhead and formation pressure fluctuation; obtaining the high-closure wellhead and formation pressure stable interval value based on the influence weights of different factors on the wellhead and formation pressure fluctuation and the wellhead and formation pressure stable interval value per unit time. The influence weights of different factors on the wellhead and formation pressure fluctuation and the high-closure wellhead and formation pressure stable interval value are in a probability relationship, and the wellhead and formation pressure stable interval value per unit time and the high-closure wellhead and formation pressure stable interval value are in a probability relationship.

[0054] In the embodiments of the present invention, the sealing grade classification of the gypsum-salt caprock of the gas storage reservoir is evaluated and divided according to its gas sealing effect. It can be divided into:

[0055] High closure, characteristics: large caprock thickness, high density, extremely low permeability, uniform lithology, few fractures and faults. Function: Can effectively seal the natural gas in the gas storage reservoir, with almost no leakage. Application scenarios: Suitable for long-term storage of natural gas, important strategic reserve warehouses, etc.

[0056] Medium closure, characteristics: moderate caprock thickness, relatively high density, low permeability, relatively uniform lithology, and may have a small number of fractures and small faults. Function: Can better seal the natural gas in the gas storage reservoir, but there may be a small amount of leakage. Application scenarios: Suitable for medium-term storage of natural gas, gas storage reservoirs for commercial use, etc.

[0057] Low closure, characteristics: thin caprock thickness, general density, high permeability, non-uniform lithology, and many fractures and faults. Function: Poor sealing effect, with a high leakage risk. Application scenarios: Suitable for short-term storage of natural gas, gas storage reservoirs for non-critical uses, etc.

[0058] In the application scenarios, only by maintaining high closure can the safety of the gas storage reservoir be ensured, while medium and low closures have potential safety hazards, and it is necessary to timely investigate and optimize the storage measures to prevent accidents.

[0059] In the embodiments of the present invention, the median of the stable interval values of the wellhead and formation pressure per unit time that can integrate the information of the gypsum-salt caprock at the safe position depth can be used as the normal benchmark of the wellhead and formation pressure; the normal benchmark of the wellhead and formation pressure and the safe pore pressure are integrated and convolved, and the data normalization result is used as the influence weight of different factors on the wellhead and formation pressure fluctuations.

[0060] In the embodiments of the present invention, the median of the stable interval values of the wellhead and formation pressure per unit time at all safe position depths is used as the normal benchmark of the wellhead and formation pressure to characterize the fluctuations of the wellhead and formation pressure at the safe position depth according to the normal benchmark of the wellhead and formation pressure. It can be understood that when environmental rock layer activities occur and the wellhead and formation pressure fluctuates in the rock layer, usually the rock layer activities affect multiple position depths. Therefore, in the embodiments of the present invention, by integrating the median of the stable interval values of the wellhead and formation pressure per unit time at multiple position depths within a local area, the complexity of the stable interval values of the wellhead and formation pressure per unit time at multiple position depths is analyzed. The more complex it is, the greater the matching of the wellhead and formation pressure fluctuations within the local cycle range. Furthermore, according to the normal benchmark of the wellhead and formation pressure and the safe pore pressure value, the data normalization result of their convolution is integrated as the influence weight of different factors on the wellhead and formation pressure fluctuations, so that the influence weight of different factors on the wellhead and formation pressure fluctuations can combine the fluctuations of the stable interval values of the wellhead and formation pressure per unit time in the local area and the overall safe pore pressure situation, ensuring the accuracy and reliability of the influence weight of different factors on the wellhead and formation pressure fluctuations.

[0061] Then, the stable interval value of the wellhead and formation pressure with high sealing performance is obtained according to the influence weight of different factors on the wellhead and formation pressure fluctuations and the stable interval value of the wellhead and formation pressure per unit time. The influence weight of different factors on the wellhead and formation pressure fluctuations and the stable interval value of the wellhead and formation pressure with high sealing performance are in a probability relationship, and the stable interval value of the wellhead and formation pressure per unit time and the stable interval value of the wellhead and formation pressure with high sealing performance are in a probability relationship.

[0062] Thus, in the embodiments of the present invention, the influence weight of different factors on the wellhead and formation pressure fluctuations and the stable interval of the wellhead and formation pressure per unit time can be integrated and convolved, and by using it as the stable interval value of the wellhead and formation pressure with high sealing performance, there is no limitation on this. The stable interval value of the wellhead and formation pressure with high sealing performance is the stable interval value of the wellhead and formation pressure obtained by analyzing other position depths within a local range around the abnormal position depth of the sealing performance monitoring. The integration of the stable interval value of the wellhead and formation pressure with high sealing performance can characterize the local wellhead and formation pressure fluctuations, and then map the abnormal position depth of the sealing performance monitoring in combination with the local area, so that the stable interval value of the wellhead and formation pressure with high sealing performance has stronger reliability.

[0063] Step S500: Calculate the monitoring permeability of medium and low sealing properties through the calculation of the distribution laws of fissures and faults in the gypsum-salt caprock information, calculate the porosity based on the monitoring permeability of sealing properties at different temperatures, and monitor the pore size of the rock for the monitoring permeability of sealing properties at different temperatures.

[0064] Step S600: Integrate the influence weights of different factors such as the wellhead and formation pressure fluctuations at the depth of the abnormal position of the sealing property monitoring according to the porosity of the monitoring permeability of sealing properties at different temperatures and the compliance threshold of the temperature jump interval within the monitoring permeability of sealing properties at different temperatures matching the abnormal position of the sealing property.

[0065] It can be understood that the calculation of the distribution laws of fissures and faults: Objective: To understand the spatial distribution of fissures and faults in the gypsum-salt caprock and their influence on the caprock sealing property. Method: Analyze the distribution laws of fissures and faults in the caprock through geological exploration data and numerical simulation. This may include methods such as using geological models, fault analysis, and fissure network models. Significance: The distribution of fissures and faults will affect the permeability and sealing property of the caprock. Understanding these distribution laws helps to predict and manage the sealing performance of the gas storage reservoir.

[0066] Calculation of the monitoring permeability of medium and low sealing properties: Definition: The monitoring permeability of sealing properties is an important index for evaluating the sealing performance of the caprock. Medium and low sealing properties mean that the sealing property of the caprock is poor and the permeability is high. Method: Based on the distribution laws of fissures and faults, calculate the permeability under medium and low sealing property conditions. This can be achieved through methods such as numerical simulation and experimental data analysis.

[0067] Calculating the porosity of the monitoring permeability of sealing properties at different temperatures: Objective: To evaluate the influence of temperature change on the porosity of the caprock. Method: Calculate the monitoring permeability of sealing properties under different temperature conditions and infer the porosity accordingly. Temperature change will affect the physical properties of the rock, such as the expansion or contraction of gypsum-salt, which will change the porosity. Data processing: Use tools such as experimental data and thermodynamic models to analyze the porosity data at different temperatures.

[0068] Monitoring the pore size of the rock: Objective: To understand the change of the pore size of the rock. Method: Use the monitoring permeability data of sealing properties at different temperatures to monitor the change of the pore size of the rock. This can be achieved through experimental tests (such as CT scanning, nuclear magnetic resonance) or model simulation. Significance: The change of the pore size of the rock directly affects the porosity and permeability, thus affecting the sealing performance and gas storage capacity of the gas storage reservoir.

[0069] The porosity of the monitoring permeability of sealing properties at different temperatures: Definition: Porosity is the ratio of the pore volume in the rock to the total rock volume. The monitoring permeability of sealing properties under different temperature conditions can be used to calculate the porosity. Method: Infer the porosity according to the monitoring permeability data at different temperatures. Use the influence model of temperature on permeability and porosity for calculation and analysis.

[0070] Temperature jump interval compliance threshold for matching the depth of abnormal positions in tightness monitoring: Objective: To identify abnormal positions in tightness monitoring and their depths within different temperature jump intervals. Method: Compare the temperature jump intervals at different depth positions with the compliance threshold to determine whether there are abnormalities. Analyze whether these abnormal positions meet the set threshold criteria. Significance: Identifying abnormal positions helps to evaluate the safety and stability of the gas storage reservoir and take corresponding measures for adjustment and optimization.

[0071] Weights of influencing factors of wellhead and formation pressure fluctuations for integrating the depth of abnormal positions in tightness monitoring: Objective: To determine the influence weights of different factors on wellhead and formation pressure fluctuations. Method: Integrate and analyze the wellhead and formation pressure fluctuations at the depth of abnormal positions in tightness monitoring, and identify the main factors affecting these fluctuations, such as temperature, porosity, permeability, etc. Application: By identifying the weights of each factor, the management strategy can be optimized to improve the operation efficiency and safety of the gas storage reservoir.

[0072] Step S500 involves the calculation of the distribution of fractures and faults in the gypsum-salt caprock and the process of calculating tightness monitoring permeability and porosity under different temperature conditions. The key lies in understanding the permeation characteristics and pore structure of the caprock to evaluate its tightness performance.

[0073] Step S600 calculates the porosity based on the tightness monitoring permeability at different temperatures and analyzes the relationship between these data and the abnormal positions in tightness monitoring. By integrating and analyzing the weights of factors affecting wellhead and formation pressure fluctuations, optimization suggestions and improvement measures are provided.

[0074] Furthermore, in some embodiments of the present invention, the calculation of the distribution law of fractures and faults for the gypsum-salt caprock information obtains medium and low tightness monitoring permeabilities, including: performing the calculation and processing of the distribution law of fractures and faults for the gypsum-salt caprock information according to the calculation algorithm of the distribution law of fractures and faults to obtain the injection and production rates and amounts of different types of wellheads and formations at the same altitude; calculating the remaining volume of the injection and production rates and amounts of different types of wellheads and formations with medium and low tightness to obtain tightness monitoring permeabilities at different temperatures.

[0075] Furthermore, in some embodiments of the present invention, according to the porosity of the permeability monitored by different temperature sealings and the compliance threshold of the temperature jump interval at the depth of the abnormal position of the permeability monitored by different temperature sealings, the influence weights of different factors such as the wellhead and formation pressure fluctuations at the depth of the abnormal position of the sealing monitoring are integrated, including: analyzing the three-dimensional stress-strain relationship of the porosity of the permeability monitored by different temperature sealings using Hooke's law to obtain the stress state of the porous rock formation; integrating the maximum value per unit time within the compliance threshold of the temperature jump interval at the depth of the abnormal position of the sealing monitoring in the permeability monitored by different temperature sealings matching different porosities at different altitudes as the abnormal jump limit value of the sealing monitoring, and convolving the abnormal jump limit value of the sealing monitoring with the stress state of the porous rock formation as the stress change interval; using the attention mechanism to analyze the stress change intervals of all porosities and the data normalization results to obtain the influence weights of different factors of the wellhead and formation pressure fluctuations.

[0076] In the embodiments of the present invention, by analyzing the three-dimensional stress-strain relationship of the porosity of the permeability monitored by different temperature sealings using Hooke's law, the stress state of the porous rock formation is obtained, thereby retaining the information of the permeability monitored by different temperature sealings with stronger high-frequency information and enhancing the reliability of the stress state of the porous rock formation.

[0077] The stress change interval is obtained based on the abnormal jump limit value of the sealing monitoring and the stress state of the porous rock formation. Since the larger the abnormal jump limit value of the sealing monitoring, the higher the possibility of the wellhead and formation pressure fluctuations at the depth of the abnormal position of the matching sealing monitoring, and combining with the stress state of the matching porous rock formation to obtain the stress change interval, so that the stress change interval can accurately characterize the wellhead and formation pressure fluctuations at the depth of the abnormal position of the sealing monitoring under the matching porosity. Furthermore, by combining the optimized values of all porosities and the data normalization results, the influence weights of different factors of the wellhead and formation pressure fluctuations are obtained, improving the reliability of the influence weights of different factors of the wellhead and formation pressure fluctuations.

[0078] The abnormal jump limit value of the sealing monitoring is the influence jump limit value of the depth of the abnormal position of the sealing monitoring in the permeability monitored by different temperature sealings with different porosities. It can be understood that due to the huge influence of rock formation activities and gypsum-salt caps, matching jump limit values of rock formation activities will be generated, making the abnormal probability of the gypsum-salt cap very high, and thus leading to the effect of the jump limit value. Therefore, by analyzing the abnormal jump limit values of the sealing monitoring around the depth of the abnormal position of the sealing monitoring, the influence of the jump limit value of rock formation activities can be accurately determined.

[0079] Step S700: Integrate the influencing factors of the rock structure of the gypsum-salt cap information according to the cap thickness of the permeability monitored by different temperature sealings at different position depths.

[0080] Step S800: Based on the rock structure, the influence weights of different factors such as wellhead and formation pressure fluctuations, and the stable interval values of high-closure wellhead and formation pressure;

[0081] Step S900: Obtain the stable interval values of the wellhead to be monitored and the formation pressure at the depth of the abnormal position of the closure monitoring, and judge the gas leakage condition of the gas storage in the oil and gas field according to the stable interval values of the wellhead to be monitored and the formation pressure.

[0082] In some embodiments of the present invention, the influence factors of the rock structure integrating the gypsum-salt caprock information according to the caprock thickness at different position depths of the closure monitoring permeability at different temperatures include: using the random forest model, integrating the penetration velocities of the closure monitoring permeabilities at different temperatures according to the caprock thickness at different position depths; analyzing the compaction degree of fractures and caprocks using the Pearson correlation coefficient for all the penetration velocities of the closure monitoring permeabilities at different temperatures, and then taking them as the influence factors of the rock structure of the gypsum-salt caprock information.

[0083] Using the random forest model, we can predict the penetration velocity based on the closure monitoring permeability at different temperatures and the caprock thickness at different position depths. By inputting temperature, position depth, and caprock thickness as features into the random forest regression model, the model will learn the complex relationships between these features and the penetration velocity, and provide an estimate of the penetration velocity during the prediction process. This method can handle non-linear relationships and interactions between features, thus effectively estimating the penetration velocity under different temperature conditions. Therefore, the present invention uses the random forest model to integrate the penetration velocities of the closure monitoring permeabilities at different temperatures respectively, and integrates all the penetration velocities to analyze the compaction degree of fractures and caprocks using the Pearson correlation coefficient, and then obtains the influence factors of the rock structure of the gypsum-salt caprock information.

[0084] Of course, in some other embodiments of the present invention, various other possible implementation methods can also be used to determine the rock structure, such as using the method of trend feature extraction to extract the trend features of the gypsum-salt caprock information to obtain periodic terms, and analyzing the periodic terms, etc., which are not limited herein.

[0085] In some embodiments of the present invention, there is a conditional relationship between the rock structure and the stable interval values of the wellhead to be monitored and the formation pressure at the depth of the abnormal position of the closure monitoring. There is a probability relationship between the influence weights of different factors such as wellhead and formation pressure fluctuations, the stable interval values of high-closure wellhead and formation pressure, and the stable interval values of the wellhead to be monitored and the formation pressure at the depth of the abnormal position of the closure monitoring. The value of the stable interval values of the wellhead to be monitored and the formation pressure is the value after data normalization.

[0086] That is to say, in the embodiments of the present invention, further analysis is carried out on the stable interval value of the high-closed wellhead and formation pressure according to the rock structure and the influence weights of different factors such as the wellhead and formation pressure fluctuations. When the rock structure is larger, it indicates that the matching gypsum-salt caprock information is more periodically distributed. Therefore, the probability of wellhead and formation pressure fluctuations is lower. There is a conditional relationship between the rock structure and the stable interval value of the wellhead and formation pressure to be monitored. When the influence weights of different factors of wellhead and formation pressure fluctuations are larger, it indicates that the stable interval value of the wellhead and formation pressure of the data wellhead matching the abnormal data points of seal monitoring is higher. That is, there is a probability relationship between the influence weights of different factors of wellhead and formation pressure fluctuations, the stable interval value of the high-closed wellhead and formation pressure, and the stable interval value of the wellhead and formation pressure to be monitored at the depth of the abnormal position of seal monitoring.

[0087] In the embodiments of the present invention, after integrating the stable interval value of the wellhead and formation pressure to be monitored, the gas leakage condition of the gas storage in the oil and gas field can be analyzed and judged according to the stable interval value of the wellhead and formation pressure to be monitored. Specifically: In some embodiments of the present invention, judging the gas leakage condition of the gas storage in the oil and gas field according to the stable interval value of the wellhead and formation pressure to be monitored includes: when the stable interval value of the wellhead and formation pressure to be monitored is greater than the limit value of the stable interval value of the safe wellhead and formation pressure, it is determined that gas leakage occurs during the operation of the gas storage in the oil and gas field; when the stable interval value of the wellhead and formation pressure to be monitored is lower than the limit value of the stable interval value of the safe wellhead and formation pressure, it is determined that the operation safety state of the gas storage in the oil and gas field is safe.

[0088] As Figure 2 shown, it shows a composition diagram of the operation module of a method for monitoring the seal of a gypsum-salt caprock in a gas storage provided by an embodiment of the present invention, including:

[0089] The compliance information integration module for sensing data acquisition. This module uses multi-modal monitoring sensing devices to collect the gypsum-salt caprock information during the storage operation of the gas storage in the oil and gas field. The depths at different altitudes during the storage time are used as the depths of abnormal positions for seal monitoring. The gypsum-salt caprock information at the depths of abnormal positions for seal monitoring is used as abnormal data for seal monitoring. Using the abnormal data for seal monitoring and the monitoring point information compliant with the temperature jump interval at different altitudes at the depths of abnormal positions for seal monitoring, the stable interval value of the wellhead and formation pressure per unit time at the depths of abnormal positions for seal monitoring is determined;

[0090] Wellhead and formation pressure stability interval value determination module, which determines the safe pore pressure change range of gypsum salt caprock information, takes the depth of the high-sealing position compliant with the depth temperature jump interval of the closedness monitoring anomaly position at different altitudes as the safe position depth, and uses the safe pore pressure change range and the caprock thickness at the depth of the closedness monitoring anomaly position and the safe position depth to determine the safe pore pressure value at the depth of the closedness monitoring anomaly position; uses the wellhead and formation pressure stability interval value per unit time, the safe pore pressure value at the depth of the closedness monitoring anomaly position, and the wellhead and formation pressure stability interval value per unit time of the gypsum salt caprock information at all safe position depths to determine the high-sealing wellhead and formation pressure stability interval value at the depth of the closedness monitoring anomaly position;

[0091] Rock structure influence factor acquisition module, which performs calculations on the fracture and fault distribution laws of the gypsum salt caprock information to obtain medium and low closedness monitoring permeabilities, calculates the porosity based on the closedness monitoring permeabilities at different temperatures, monitors the rock pore diameter for the closedness monitoring permeabilities at different temperatures, and integrates the influence weights of different factors on the wellhead and formation pressure fluctuations at the depth of the closedness monitoring anomaly position according to the porosity of the closedness monitoring permeabilities at different temperatures and the compliance thresholds within the closedness monitoring permeabilities at different temperatures that match the depth temperature jump interval of the closedness monitoring anomaly position; integrates the rock structure influence factors of the gypsum salt caprock information according to the caprock thickness of the closedness monitoring permeabilities at different temperatures at different position depths;

[0092] Gas leakage judgment module for gas storage reservoir, which uses the rock structure, the influence weights of different factors on the wellhead and formation pressure fluctuations, and the high-sealing wellhead and formation pressure stability interval value to obtain the wellhead and formation pressure stability interval value to be monitored at the depth of the closedness monitoring anomaly position, and uses the wellhead and formation pressure stability interval value to be monitored to judge the gas leakage condition of the oil and gas field gas storage reservoir.

[0093] The present invention also provides an edge computing gateway for closedness monitoring of gypsum salt caprock in a gas storage reservoir. The edge computing gateway includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the steps of the foregoing method for closedness monitoring of gypsum salt caprock in a gas storage reservoir.

[0094] Through local analysis of the information of the gypsum-salt caprock, the stable interval value of the wellhead and formation pressure per unit time is determined based on the abnormal data of the sealing monitoring and the information of the monitoring points compliant with the altitude temperature jump interval at different depths from the abnormal position of the sealing monitoring; since through the analysis of the safety pore pressure, the average pore pressure of each surrounding point can be used to reduce the influence of the pore pressure of the accidental pore pressure on the analysis result of the wellhead and formation pressure fluctuation, combined with the stable interval value of the wellhead and formation pressure per unit time, the safety pore pressure value and the stable interval value of the wellhead and formation pressure per unit time of the gypsum-salt caprock information at all safe position depths, the high-sealing wellhead and formation pressure stable interval value at the depth of the abnormal position of the sealing monitoring is determined, and the local all safe position depths can be analyzed from multiple angles, so as to obtain a high-sealing wellhead and formation pressure stable interval value with better reliability. Then, combined with the fact that the rock layer activities are mostly high-frequency rock layer activities, the sealing at different temperatures is monitored and analyzed by means of calculating the distribution law of fractures and faults, so as to obtain the influence weights of different factors on the wellhead and formation pressure fluctuation at the depth of the abnormal position of the sealing monitoring; according to the caprock thickness of the sealing monitoring permeability at different position depths at different temperatures, the influence factors of the rock structure of the gypsum-salt caprock information are integrated. Due to the non-periodic characteristics of the rock layer activities, furthermore, based on the rock structure, the influence weights of different factors on the wellhead and formation pressure fluctuation, and the high-sealing wellhead and formation pressure stable interval value, the stable interval value of the wellhead and formation pressure to be monitored at the depth of the abnormal position of the sealing monitoring is obtained, so that the stable interval value of the wellhead and formation pressure to be monitored can more accurately characterize the wellhead and formation pressure fluctuation at the depth of the abnormal position of the sealing monitoring. The present invention combines the pore pressure characteristics of the local gypsum-salt caprock and the periodic characteristics of the gypsum-salt caprock to specifically and effectively analyze the wellhead and formation pressure fluctuation, realize the accurate identification of the rock layer activities in the gas storage reservoir of the oil and gas field, and then can judge the gas leakage condition of the gas storage reservoir of the oil and gas field according to the stable interval value of the wellhead and formation pressure to be monitored, improving the gas leakage analysis effect. In summary, the present invention can effectively improve the rock layer activity identification effect, and further improve the accuracy and reliability of the dynamic balance gas leakage sealing monitoring.

[0095] It should be noted that the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0096] Each embodiment in this specification is described in a progressive manner, and the same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

Claims

1. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir, characterized in that: The method includes: The multimodal monitoring sensor equipment is used to collect the gypsum cap layer information of the oil and gas field gas storage during the storage time, and the depths of different altitudes during the storage time are used as the depths of the abnormal position of the closure monitoring, and the gypsum cap layer information of the abnormal position of the closure monitoring is used as the abnormal data of the closure monitoring. The abnormal data of the closure monitoring and the monitoring point information that complies with the temperature jump interval of different altitudes of the abnormal position of the closure monitoring are used to determine the stable interval value of the wellhead and formation pressure per unit time of the abnormal position of the closure monitoring; Determine the safe pore pressure variation range of the gypsum caprock information, take the high closed position depth that complies with the temperature jump interval of the closed monitoring abnormal position depth at different altitudes as the safe position depth, and use the caprock thickness at the closed monitoring abnormal position depth and the safe position depth within the safe pore pressure variation range to determine the safe pore pressure value of the closed monitoring abnormal position depth; use the unit time wellhead and formation pressure stability interval value of the closed monitoring abnormal position depth, the safe pore pressure value and the unit time wellhead and formation pressure stability interval value of the gypsum caprock information of all safe position depths to determine the high closed wellhead and formation pressure stability interval value of the closed monitoring abnormal position depth; The distribution law of cracks and faults of the gypsum cap layer information is calculated to obtain medium and low closure monitoring permeability, the porosity is calculated for different temperature closure monitoring permeabilities, and the rock pore size is monitored for different temperature closure monitoring permeabilities. According to the porosity of different temperature closure monitoring permeabilities and the compliance threshold of the temperature jump interval within the different temperature closure monitoring permeabilities that matches the closure monitoring abnormal position depth, the influence weights of different factors of the wellhead and formation pressure fluctuations at the depth of the closure monitoring abnormal position are integrated; according to the cap layer thickness at different positions and depths of different temperature closure monitoring permeabilities, the rock structure influence factors of the gypsum cap layer information are integrated; By utilizing the weights of the different factors affecting the rock structure, wellhead and formation pressure fluctuations, and the stable interval values ​​of the highly closed wellhead and formation pressure, the stable interval values ​​of the wellhead and formation pressure to be monitored at the depth of the closed monitoring abnormal position are obtained, and the gas leakage status of the oil and gas field gas storage reservoir is judged by utilizing the stable interval values ​​of the wellhead and formation pressure to be monitored.

2. A method for monitoring the sealing performance of a gas storage gypsum cap layer according to claim 1, characterized in that: The method of using the abnormal closure monitoring data and the monitoring point information that complies with the temperature jump interval at different altitudes in accordance with the abnormal closure monitoring position depth to determine the stable interval value of the wellhead and formation pressure per unit time at the abnormal closure monitoring position depth includes: The monitoring point information that complies with the temperature jump interval at different altitudes at the depth of the closed monitoring anomaly position is calculated using a logistic regression model; the classification results of the closed monitoring anomaly data and different regression coefficients are integrated as the monitoring anomaly influence node; the data normalization result of the monitoring anomaly influence node is used as the unit time wellhead and formation pressure stability interval value at the depth of the closed monitoring anomaly position.

3. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: The method of determining the safe pore pressure value at the depth of the abnormal position of the sealing monitoring by using the caprock thickness at the depth of the abnormal position of the sealing monitoring within the range of the safe pore pressure variation includes: The safety pore pressure value at the depth of the abnormal position for closure monitoring is taken as the safety pore pressure value at the depth of the abnormal position for closure monitoring after correlation analysis is performed on the deposition rate of the caprock thickness at the depth of the abnormal position for closure monitoring.

4. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: The method of determining the high-sealing wellhead and formation pressure stability interval value at the abnormal position depth of the sealing monitoring by using the stable interval value of the wellhead and formation pressure per unit time at the abnormal position depth of the sealing monitoring, the safe pore pressure value, and the stable interval value of the wellhead and formation pressure per unit time of the gypsum cap layer information at all safe position depths, comprises: The median of the stable interval value of the wellhead and formation pressure per unit time of the gypsum cap layer information at the safety position depth is used as the normal reference of the wellhead and formation pressure; the normal reference of the wellhead and formation pressure and the safety pore pressure are integrated for convolution, and the data normalization result is used as the influence weight of different factors of the wellhead and formation pressure fluctuation; The high-closure wellhead and formation pressure stability interval value is obtained by utilizing the influence weights of different factors on the wellhead and formation pressure fluctuations and the stable interval value of the wellhead and formation pressure per unit time. The influence weights of different factors on the wellhead and formation pressure fluctuations and the stable interval value of the wellhead and formation pressure per unit time are in a probabilistic relationship with each other. The stable interval value of the wellhead and formation pressure per unit time and the stable interval value of the wellhead and formation pressure per unit time are in a probabilistic relationship with each other.

5. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: The method of calculating the distribution law of cracks and faults on the gypsum-salt caprock information to obtain medium and low closure monitoring permeability includes: The information of the gypsum salt caprock is processed according to the calculation algorithm of the distribution law of fractures and faults to obtain the injection and production speed and volume of different types of wellheads and formation pressures at the same altitude; the injection and production speed and volume of different types of wellheads and formation pressures with front, medium and low sealing properties are calculated by residual volume to obtain the permeability monitored at different temperature sealing properties.

6. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: The porosity of the closure monitoring permeability at different temperatures and the compliance threshold of the temperature jump interval within the closure monitoring permeability at different temperatures matching the closure monitoring abnormal position depth are integrated to influence the weights of different factors of the wellhead and formation pressure fluctuation at the closure monitoring abnormal position depth, including: The porosity of the permeability monitored at different temperatures is analyzed by using Hooke's law for three-dimensional stress-strain relationship to obtain the stress state of the porosity rock formation; The permeability of the closure monitoring at different temperatures matching the integrated porosity at different altitudes is taken as the maximum value per unit time of the compliance threshold of the temperature jump interval at the depth of the closure monitoring abnormal position, and the closure monitoring abnormal jump limit value is convolved with the stress state of the porosity rock formation as the stress change interval; the attention mechanism is used to analyze the stress change intervals of all porosities and the data normalization results to obtain the influence weights of different factors of wellhead and formation pressure fluctuations.

7. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: The rock structure influencing factors of integrating the gypsum cap layer information according to the cap layer thickness at different depths and monitoring the permeability at different temperatures include: Using the random forest model, the penetration rates of different temperature closure monitoring permeabilities are integrated according to the thickness of the cap layer at different depths. The penetration rates of all different temperature closure monitoring permeabilities are analyzed by the Pearson correlation coefficient between the cracks and the compaction degree of the cap layer, which is used as the rock structure influencing factor of the gypsum salt cap layer information.

8. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: There is a conditional relationship between the rock structure and the stable interval value of the wellhead to be monitored and the formation pressure at the depth of the abnormal position of the closed monitoring. There is a probabilistic relationship between the weights of the influence of different factors on the wellhead and the formation pressure fluctuation, the stable interval value of the high-closed wellhead and the formation pressure and the stable interval value of the wellhead to be monitored and the formation pressure at the depth of the abnormal position of the closed monitoring. The value of the stable interval value of the wellhead to be monitored and the formation pressure is the value after data normalization.

9. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 1, characterized in that: The method of judging the gas leakage status of the oil and gas field gas storage by using the stable interval value of the wellhead to be monitored and the formation pressure includes: When the value of the stable interval between the wellhead to be monitored and the formation pressure is greater than the limit value of the stable interval between the safety wellhead and the formation pressure, it is determined that gas leakage has occurred in the operation of the oil and gas field gas storage reservoir; when the value of the stable interval between the wellhead to be monitored and the formation pressure is lower than the limit value of the stable interval between the safety wellhead and the formation pressure, it is determined that the oil and gas field gas storage reservoir is in a safe operating state.

10. A method for monitoring the sealing performance of gypsum caprock in a gas storage reservoir as claimed in claim 5, characterized in that: The crack and fault distribution law calculation algorithm uses the finite element method to analyze the influence of cracks and faults on formation pressure and stress, simulates the influence of cracks and faults on fluid flow, and completes the crack and fault distribution law calculation processing in the gypsum salt cap layer information.

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