A method, system and storage medium for oil and gas pipeline leakage monitoring and early warning

Abstract

The present application relates to oil and gas pipeline leakage monitoring and early warning field, specifically for a kind of method, system and storage medium for oil and gas pipeline leakage monitoring and early warning, including data acquisition module, soil temperature analysis module, leakage triple progressive analysis module and early warning processing module, soil temperature analysis module is according to the temperature parameter value received, the temperature change of each monitoring sub defense area is analyzed, early warning processing module is according to the leakage early warning signal received, obtains the positioning information of this sub defense area, and contacts personnel and is repaired, leakage triple progressive analysis module is according to setting leakage triple progressive effect comparison calculation, discriminates whether the monitoring sub defense area that triggers calculation pre-judgment alarm leaks, the present application solves the problem that the temperature change caused by small leakage in a short time is not enough to trigger pre-judgment alarm, and the progressive perception pre-judgment ability of small leakage is enhanced.

Description

Technical Field

[0001] This invention relates to the field of oil and gas pipeline leak monitoring and early warning, specifically to a method, system, and storage medium for oil and gas pipeline leak monitoring and early warning. Background Technology

[0002] Oil and gas resources occupy a vital position in modern society, serving as an important energy source for industrial production, transportation, and residential life. Oil and gas pipelines, as the primary means of transporting these resources, offer advantages such as efficiency, safety, and stability. However, because oil and gas pipelines typically span long distances and traverse various complex terrains and environments, they face numerous risks during operation. Currently, there are some application cases of monitoring equipment and supporting software using single-mode optical fiber to monitor and warn of damage to oil and gas pipelines caused by third-party excavation and heavy-load crushing. There are also many application cases of monitoring equipment and supporting software based on the temperature sensing function of multimode optical fiber to monitor the temperature distribution of indoor storage areas and the ambient temperature of outdoor equipment. However, there are no successful cases of using single-mode optical fiber temperature sensing equipment laid in the same trench as the oil and gas pipeline for accurate monitoring and early warning of oil and gas pipeline leaks. This invention utilizes single-mode optical fiber temperature sensing laid in the same trench as the oil and gas pipeline for monitoring and early warning of oil and gas pipeline leaks, and sets up a calculation comparison reflecting the cumulative effect of minor leaks to enhance the ability to perceive and predict minor leaks. Summary of the Invention

[0003] To address the technical problems mentioned in the background, this invention provides a method, system, and storage medium for monitoring and early warning of oil and gas pipeline leaks.

[0004] The objective of this invention can be achieved through the following technical solutions:

[0005] The first aspect of the present invention provides a system for monitoring and early warning of oil and gas pipeline leaks, including a data acquisition module, a soil temperature analysis module, a leak triple progressive analysis module, an early warning processing module, and a data center.

[0006] The data acquisition module is equipped with a monitoring and early warning system according to on-site requirements, and monitors soil temperature data in real time within the total monitoring section length through the system. The specific acquisition process is as follows:

[0007] The output of the data acquisition module is connected to the input of the soil temperature analysis module to obtain the length of the current total monitoring segment. The length of each monitoring sub-zone is divided proportionally according to the length of the total monitoring segment, and each monitoring sub-zone is numbered in sequence. Temperature sensors are installed in each monitoring sub-zone proportionally to its length. The temperature monitoring and acquisition time interval in each monitoring sub-zone is set to Ki. Temperature data information of each monitoring sub-zone is collected in real time through the temperature sensors to obtain the temperature parameter values ​​of each monitoring sub-zone.

[0008] The acquired temperature parameter values ​​for each monitoring sub-zone are sent to the soil temperature analysis module.

[0009] The soil temperature analysis module analyzes the temperature changes in each monitored sub-zone based on the received temperature parameter values ​​and sends the analysis results to the early warning module. The specific acquisition process is as follows:

[0010] The input of the soil temperature analysis module is connected to the output of the data center, and the input of the early warning module is connected to the output of the soil temperature analysis module. Based on the received temperature parameter values ​​from each monitoring sub-zone, the module analyzes the data and sets a trigger time of 0 to begin calculating temperature rise and fall changes. For any monitoring sub-zone, it acquires the temperature monitoring time point from any previous moment, marking it as the initial time point, and then the temperature monitoring time point up to the current moment, marking it as the final time point. The difference between the initial and final time points is calculated to obtain the temperature change trigger duration. All temperature parameter values ​​within the trigger duration are acquired, and the difference between all adjacent temperature parameter values ​​within the trigger duration is calculated to obtain the temperature change value within the trigger duration. These temperature change values ​​are then arranged in ascending order, and the maximum temperature change value is identified and marked as the temperature change peak value. Extract the preset cooling peak and preset heating peak values ​​from the data center. If the temperature change peak value is positive, compare it with the preset heating peak value. If the temperature change peak value is greater than the preset heating peak value, mark the end time point as time 0 and generate a heating signal to send to the leakage triple cumulative analysis module. If the temperature change peak value is negative, compare it with the preset cooling peak value. If the temperature change peak value is greater than the preset cooling peak value, mark the end time point as time 0 and generate a cooling signal to send to the leakage triple cumulative analysis module. Divide the obtained temperature change trigger duration into several temperature change sub-durations in equal proportions. Obtain the temperature parameter values ​​at the start and end times of each temperature change sub-duration, and label them FG and FD respectively. Then, obtain the number of acquisitions within each temperature change sub-duration, and label it FK. The average temperature change FQ for each temperature change interval is obtained. The difference between two adjacent average temperature change values ​​is calculated to obtain the temperature change difference. The temperature change difference is then divided by the temperature change interval to obtain the rate of change of the average temperature change. The preset rate of change of the data center is extracted. The rate of change of the average temperature change is compared with the preset rate of change. If the rate of change of the average temperature change is greater than the preset rate of change, the end time point is marked as time 0, and an abnormal signal is generated and sent to the leakage triple progressive analysis module.

[0011] The triple-cumulative leakage analysis module calculates and compares the triple-cumulative leakage effect to determine whether the monitoring sub-zone that triggered the pre-alarm calculation has a leakage. The specific acquisition process is as follows:

[0012] The output of the soil temperature analysis module is connected to the input of the triple progressive analysis module, and the output of the triple progressive analysis module is connected to the input of the early warning processing module. Upon receiving signals from the soil temperature analysis module, the module initiates a monitoring and early warning program and performs a calculation. A first temperature change calculation duration is set. The monitored temperature within the first temperature change calculation duration for the triggered temperature change calculation sub-zone is compared with the temperature monitored at time 0. The peak and average temperature changes are calculated and marked as the first temperature change peak and the first temperature change average, respectively. The first temperature change peak setpoint and the first temperature change average setpoint are extracted from the data center. The first temperature change peak and the first temperature change average setpoint are compared with the first temperature change peak setpoint and the first temperature change average setpoint. If they do not match, the module determines the appropriate action to be taken. If the temperature exceeds the first temperature change peak value and the first temperature change average value, and the calculation prediction alarm is not triggered, a secondary calculation signal is generated and sent to the monitoring and early warning program. Upon receiving the secondary calculation signal, the monitoring and early warning program initiates secondary calculation, sets a second temperature change calculation duration, and continues to acquire the temperature monitored in the affected area during the second temperature change calculation duration and the temperature monitored at the end of the first temperature change calculation duration. It then calculates the temperature change peak value and the temperature change average value, marking them as the second temperature change peak value and the second temperature change average value. The second temperature change peak value and the second temperature change average value are extracted from the data center and compared with their corresponding settings. If the second temperature change peak value and the second temperature change average value do not exceed their corresponding settings... If the corresponding set value is not specified, the second temperature change peak value is added to the first temperature change peak value to obtain the second cumulative temperature change peak value, and the second temperature change average value is added to the first temperature change average value to obtain the second cumulative temperature change average value. The set values ​​for the second cumulative temperature change peak value and the second cumulative temperature change average value of the data center are extracted. The second cumulative temperature change peak value and the second cumulative temperature change average value are compared with their corresponding set values. If the second cumulative temperature change peak value and the second cumulative temperature change average value are less than their corresponding set values, three calculation signals are generated and sent to the monitoring and early warning program. The monitoring and early warning program receives the three calculation signals and initiates three calculations, sets the third temperature change calculation duration, and obtains the monitored temperature and the first temperature change calculation duration within the third temperature change calculation sub-zone during the third temperature change calculation duration. At the end of the monitoring process, the peak and average temperatures of the temperature changes are calculated and labeled as the third temperature change peak and the third temperature change average. The setpoints for the third temperature change peak and the third temperature change average are extracted and compared with their corresponding setpoints. If neither the third temperature change peak nor the third temperature change average exceeds its corresponding setpoint, the third temperature change peak is added to the second temperature change peak to obtain the third cumulative temperature change peak, and the third temperature change average is added to the second temperature change average to obtain the third cumulative temperature change average. The setpoints for the third cumulative temperature change peak and the third cumulative temperature change average are extracted and compared with their corresponding setpoints.If the third cumulative temperature change peak value and the third cumulative temperature change average value are less than their corresponding set values, a stop signal is generated and sent to the monitoring and early warning program, and the next round of temperature change calculation ends. Conversely, if any of the calculated values ​​in the first, second, and third calculations exceed their corresponding set values, a leakage early warning signal is generated and sent to the early warning processing module.

[0013] Upon receiving a leakage warning signal, the early warning processing module obtains the location information of the sub-zone and contacts personnel for maintenance. The specific acquisition process is as follows:

[0014] The location information of the monitoring sub-area is obtained based on the positioning sensor. Taking the monitoring sub-area as the center, the location of the mobile terminal of each maintenance personnel within the radius is obtained. The location of the monitoring sub-area and the location of the mobile terminal of each maintenance personnel are connected to obtain the maintenance distance. The maintenance distances are arranged in ascending order. The minimum maintenance distance is obtained and the corresponding maintenance personnel are marked as preferred personnel. An emergency signal is generated and sent to the preferred personnel. The preferred personnel receive the emergency signal and repair the oil and gas pipeline leak in the monitoring sub-area.

[0015] Reference Figure 2 As shown, the second aspect of the present invention provides a method for monitoring and early warning of leaks in oil and gas pipelines, the steps of which are as follows:

[0016] F1. Data Acquisition: Install a monitoring and early warning system according to site requirements, and monitor soil temperature data in real time within the total monitoring section length through the system.

[0017] F2. Soil temperature analysis: Based on the received temperature parameter values, analyze the temperature changes in each monitoring sub-zone and send the analysis results to the early warning module.

[0018] F3. Leakage Triple Progression Analysis: Based on the setting of leakage triple progression effect comparison calculation, it determines whether the monitoring sub-zone that triggers the calculation and prediction alarm has leakage.

[0019] F4. Early Warning Processing: Upon receiving a leakage early warning signal, obtain the location information of the sub-zone and contact personnel for maintenance.

[0020] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0021] Compared with existing technologies, the beneficial effects of this invention are as follows: By employing a triple progressive effect comparison calculation to determine whether a leak has occurred, the probability of false alarms and missed alarms is reduced. It solves the problem that temperature changes from minor leaks in a short period are insufficient to trigger a pre-alarm, enhancing the progressive sensing and pre-judgment capability for minor leaks and effectively reducing the risk of leak accidents. Once the monitoring system detects abnormal data, it can immediately trigger an early warning mechanism, rapidly sending warning information to relevant personnel, thus gaining valuable time for timely countermeasures and minimizing potential safety hazards from leaks, protecting the lives and property of personnel. Utilizing advanced data analysis algorithms, the data collected by sensors is analyzed and processed in depth, enabling timely and effective monitoring and early warning of oil and gas pipeline leaks, which can significantly reduce the occurrence of leak accidents and thus reduce oil and gas pollution to the environment. Oil and gas leaks not only pollute soil and water sources but may also harm the air, affecting the ecological balance and the quality of life of surrounding residents. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. The following drawings are not drawn to scale according to the actual size, but are intended to illustrate the main idea of ​​the present invention.

[0023] Figure 1 This is a schematic diagram of the principle of the present invention.

[0024] Figure 2 This is a diagram illustrating the method steps of the present invention. Detailed Implementation

[0025] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are also within the scope of protection of the present invention.

[0026] Please refer to Figure 1 As shown, the first aspect of the present invention provides a system for monitoring and early warning of oil and gas pipeline leaks, including a data acquisition module, a soil temperature analysis module, a leak triple progressive analysis module, an early warning processing module, and a data center.

[0027] The data acquisition module is equipped with a monitoring and early warning system according to on-site requirements, and monitors soil temperature data in real time within the total monitoring section length through the system. The specific acquisition process is as follows:

[0028] The output of the data acquisition module is connected to the input of the soil temperature analysis module to obtain the length of the current total monitoring segment. Based on the length of the total monitoring segment, the lengths of each monitoring sub-zone are proportionally divided, and each monitoring sub-zone is numbered sequentially. Temperature sensors are installed proportionally to the length of each monitoring sub-zone, and the temperature monitoring and acquisition time interval within each monitoring sub-zone is set to Ki. Temperature data from each monitoring sub-zone is collected in real time using the temperature sensors to obtain the temperature parameter values ​​for each monitoring sub-zone. The obtained temperature parameter values ​​for each monitoring sub-zone are then sent to the soil temperature analysis module.

[0029] The soil temperature analysis module analyzes the temperature changes in each monitored sub-zone based on the received temperature parameter values ​​and sends the analysis results to the early warning module. The specific acquisition process is as follows:

[0030] The input of the soil temperature analysis module is connected to the output of the data center, and the input of the early warning module is connected to the output of the soil temperature analysis module. Based on the received temperature parameter values ​​from each monitoring sub-zone, the module analyzes the data and sets a time (0) to trigger the calculation of temperature rise and fall changes. For any monitoring sub-zone, it acquires the temperature monitoring time point from any previous time and marks it as the initial time point, and then marks the temperature monitoring time point up to the current time point as the final time point. The difference between the initial and final time points is calculated to obtain the temperature change trigger duration. All temperature parameter values ​​within the temperature change trigger duration are acquired, and the difference between any two adjacent temperature parameter values ​​within the temperature change trigger duration is calculated to obtain the temperature change trigger duration itself. The temperature change values ​​are arranged in ascending order. The maximum temperature change value is obtained and marked as the temperature change peak value. The preset cooling peak value and preset heating peak value of the data center are extracted. If the temperature change peak value is positive, the temperature change peak value is compared with the preset heating peak value. If the temperature change peak value is greater than the preset heating peak value, the end time point is marked as time 0 and a heating signal is generated and sent to the leakage triple cumulative analysis module. If the temperature change peak value is negative, the temperature change peak value is compared with the preset cooling peak value. If the temperature change peak value is greater than the preset cooling peak value, the end time point is marked as time 0 and a cooling signal is generated and sent to the leakage triple cumulative analysis module.

[0031] The obtained temperature change trigger duration is divided into several equal-order temperature change sub-durations. The temperature parameter values ​​at the start and end times of each sub-duration are obtained and labeled as FG and FD, respectively. The number of data acquisitions within each sub-duration is then obtained and labeled as FK. The average temperature change FQ for each temperature change interval is obtained. The difference between two adjacent average temperature change values ​​is calculated to obtain the temperature change difference. The temperature change difference is then divided by the temperature change interval to obtain the rate of change of the average temperature change. The preset rate of change of the data center is extracted. The rate of change of the average temperature change is compared with the preset rate of change. If the rate of change of the average temperature change is greater than the preset rate of change, the end time point is marked as time 0, and an abnormal signal is generated and sent to the leakage triple progressive analysis module.

[0032] The triple-cumulative leakage analysis module calculates and compares the triple-cumulative leakage effect to determine whether the monitoring sub-zone that triggered the pre-alarm calculation has a leakage. The specific acquisition process is as follows:

[0033] The output of the soil temperature analysis module is connected to the input of the triple progressive analysis module, and the output of the triple progressive analysis module is connected to the input of the early warning processing module. Upon receiving signals from the soil temperature analysis module, the module initiates a monitoring and early warning program and performs a calculation. A first temperature change calculation duration is set. The monitored temperature within the first temperature change calculation duration for the triggered temperature change calculation sub-zone is compared with the temperature monitored at time 0. The peak and average temperature changes are calculated and marked as the first temperature change peak and the first temperature change average, respectively. The first temperature change peak setpoint and the first temperature change average setpoint are extracted from the data center. The first temperature change peak and the first temperature change average setpoint are compared with the first temperature change peak setpoint and the first temperature change average setpoint. If they do not match, the module determines the appropriate action to be taken. If the temperature exceeds the first temperature change peak value and the first temperature change average value, and the calculation prediction alarm is not triggered, a secondary calculation signal is generated and sent to the monitoring and early warning program. Upon receiving the secondary calculation signal, the monitoring and early warning program initiates secondary calculation, sets a second temperature change calculation duration, and continues to acquire the temperature monitored in the affected area during the second temperature change calculation duration and the temperature monitored at the end of the first temperature change calculation duration. It then calculates the temperature change peak value and the temperature change average value, marking them as the second temperature change peak value and the second temperature change average value. The second temperature change peak value and the second temperature change average value are extracted from the data center and compared with their corresponding settings. If the second temperature change peak value and the second temperature change average value do not exceed their corresponding settings... If the corresponding set value is not specified, the second temperature change peak value is added to the first temperature change peak value to obtain the second cumulative temperature change peak value, and the second temperature change average value is added to the first temperature change average value to obtain the second cumulative temperature change average value. The set values ​​for the second cumulative temperature change peak value and the second cumulative temperature change average value of the data center are extracted. The second cumulative temperature change peak value and the second cumulative temperature change average value are compared with their corresponding set values. If the second cumulative temperature change peak value and the second cumulative temperature change average value are less than their corresponding set values, three calculation signals are generated and sent to the monitoring and early warning program. The monitoring and early warning program receives the three calculation signals and initiates three calculations, sets the third temperature change calculation duration, and obtains the monitored temperature and the first temperature change calculation duration within the third temperature change calculation sub-zone during the third temperature change calculation duration. At the end of the monitoring process, the peak and average temperatures of the temperature changes are calculated and labeled as the third temperature change peak and the third temperature change average. The setpoints for the third temperature change peak and the third temperature change average are extracted and compared with their corresponding setpoints. If neither the third temperature change peak nor the third temperature change average exceeds its corresponding setpoint, the third temperature change peak is added to the second temperature change peak to obtain the third cumulative temperature change peak, and the third temperature change average is added to the second temperature change average to obtain the third cumulative temperature change average. The setpoints for the third cumulative temperature change peak and the third cumulative temperature change average are extracted and compared with their corresponding setpoints.If the third cumulative temperature change peak value and the third cumulative temperature change average value are less than their corresponding set values, a stop signal is generated and sent to the monitoring and early warning program, and the next round of temperature change calculation ends. Conversely, if any of the calculated values ​​in the first, second, and third calculations exceed their corresponding set values, a leakage early warning signal is generated and sent to the early warning processing module.

[0034] Upon receiving a leakage warning signal, the early warning processing module obtains the location information of the sub-zone and contacts personnel for maintenance. The specific acquisition process is as follows:

[0035] The location information of the monitoring sub-area is obtained based on the positioning sensor. Taking the monitoring sub-area as the center, the location of the mobile terminal of each maintenance personnel within the radius is obtained. The location of the monitoring sub-area and the location of the mobile terminal of each maintenance personnel are connected to obtain the maintenance distance. The maintenance distances are arranged in ascending order. The minimum maintenance distance is obtained and the corresponding maintenance personnel are marked as preferred personnel. An emergency signal is generated and sent to the preferred personnel. The preferred personnel receive the emergency signal and repair the oil and gas pipeline leak in the monitoring sub-area.

[0036] Reference Figure 2 As shown, the second aspect of the present invention provides a method for monitoring and early warning of leaks in oil and gas pipelines, the steps of which are as follows:

[0037] F1. Install a monitoring and early warning system according to site requirements, and monitor soil temperature data within the total monitoring section length in real time through the system;

[0038] F2. Analyze the temperature changes in each monitored sub-zone based on the received temperature parameter values;

[0039] F3. Based on the comparison calculation of the triple cumulative effect of leakage, determine whether the monitoring sub-zone that triggered the calculation and prediction alarm is leaking.

[0040] F4. Upon receiving a leakage warning signal, obtain the location information of the sub-zone and contact personnel for maintenance.

[0041] An embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method. It is understood that the computer-readable storage medium in this embodiment can be a volatile readable storage medium or a non-volatile readable storage medium.

[0042] The foregoing description is illustrative of the invention and should not be construed as limiting it. Although several exemplary embodiments of the invention have been described, those skilled in the art will readily understand that many modifications can be made to the exemplary embodiments without departing from the novel teachings and advantages of the invention. Therefore, all such modifications are intended to be included within the scope of the invention as defined in the claims. It should be understood that the foregoing description is illustrative of the invention and should not be construed as limiting it to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The invention is defined by the claims and their equivalents.

Claims

1. A system for monitoring and early warning of oil and gas pipeline leaks, comprising a data acquisition module, a leak triple progressive analysis module, an early warning processing module, and a data center, characterized in that, It also includes a soil temperature analysis module. This module analyzes temperature changes in each monitored sub-zone based on received temperature parameter values. It sets a time (0) to trigger the calculation of temperature rise and fall changes. For any monitored sub-zone, it obtains the temperature monitoring time point from any previous time and marks it as the initial time point. The temperature monitoring time point up to the current time is marked as the final time point. The difference between the initial and final time points is calculated to obtain the temperature change trigger duration. All temperature parameter values ​​within the trigger duration are obtained. The difference between any two adjacent temperature parameter values ​​within the trigger duration is calculated to obtain the temperature change value within the trigger duration. The temperature change values ​​are arranged in ascending order, and the maximum temperature change value is obtained and marked as the temperature change peak value. The preset values ​​from the data center are then extracted. The temperature change peak value and the preset temperature rise peak value are compared. If the temperature change peak value is positive, the temperature change peak value and the preset temperature rise peak value are compared. If the temperature change peak value is greater than the preset temperature rise peak value, the end time point is marked as time 0, and a temperature rise signal is generated and sent to the leakage triple cumulative analysis module. If the temperature change peak value is negative, the temperature change peak value and the preset temperature drop peak value are compared. If the temperature change peak value is greater than the preset temperature drop peak value, the end time point is marked as time 0, and a temperature drop signal is generated and sent to the leakage triple cumulative analysis module. The obtained temperature change trigger duration is divided into several temperature change sub-durations in equal proportions. The temperature parameter values ​​at the beginning and end times of each temperature change sub-duration are obtained and marked as FG and FD, respectively. The number of acquisitions within each temperature change sub-duration is also obtained and marked as FK. The average temperature change value FQ for each temperature change time period is obtained. The difference between two adjacent average temperature change values ​​is calculated to obtain the temperature change difference value. The temperature change difference value is then divided by the temperature change time period to obtain the rate of change of the average temperature change value. The preset rate of change of the data center is extracted. The rate of change of the average temperature change value is compared with the preset rate of change. If the rate of change of the average temperature change value is greater than the preset rate of change, the end time point is marked as time 0, and a leakage signal at time 0 is generated and sent to the leakage triple progressive analysis module. The triple-cumulative leakage analysis module calculates and compares the triple-cumulative leakage effect to determine whether the monitoring sub-zone that triggered the pre-alarm calculation is leaking. The specific process is as follows: The output of the soil temperature analysis module is connected to the input of the triple progressive leakage analysis module, and the output of the triple progressive analysis module is connected to the input of the early warning processing module. Upon receiving the leakage signal at time 0 from the soil temperature analysis module, the monitoring and early warning program is activated and a calculation is initiated. A first temperature change calculation duration is set. The monitored temperature of the triggered temperature change calculation sub-zone within the first temperature change calculation duration is compared with the temperature monitored at time 0. The peak temperature and average temperature change are calculated and marked as the first temperature change peak value and the first temperature change average value, respectively. The first temperature change peak value and the first temperature change average value setpoints are extracted from the data center. The first temperature change peak value and the first temperature change average value are then compared with the first temperature change peak value and the first temperature change average value setpoints. If the values ​​do not exceed the first temperature change peak value and the first temperature change average value respectively, no calculation prediction alarm is triggered. A secondary calculation signal is generated and sent to the monitoring and early warning program. The monitoring and early warning program receives the secondary calculation signal and starts the secondary calculation. It sets the second temperature change calculation duration and continues to acquire all monitoring temperature data of the triggered temperature change calculation sub-zone within the second temperature change calculation duration. It also extracts the temperature data at the end of the first temperature change calculation duration, calculates the temperature change peak value and the temperature change average value, and marks them as the second temperature change peak value and the second temperature change average value. It extracts the second temperature change peak value and the second temperature change average value setpoints of the data center and compares the second temperature change peak value and the second temperature change average value with their corresponding setpoints. If the second temperature change peak value and the second temperature change average value do not exceed the first temperature change peak value and the second temperature change average value setpoint respectively, then the alarm is triggered. If the peak temperature change and the average temperature change do not exceed their corresponding set values, then the second peak temperature change is added to the first peak temperature change to obtain the second cumulative peak temperature change, and the second average temperature change is added to the first average temperature change to obtain the second cumulative average temperature change. The set values ​​for the second cumulative peak temperature change and the second cumulative average temperature change are extracted from the data center. The second cumulative peak temperature change and the second cumulative average temperature change are compared with their corresponding set values. If the second cumulative peak temperature change and the second cumulative average temperature change are less than their corresponding set values, then three calculation signals are generated and sent to the monitoring and early warning program. The monitoring and early warning program receives the three calculation signals and initiates three calculations, sets the third temperature change calculation duration, and obtains the temperature change calculation sub-zone at the third temperature change. All monitored temperature data within the calculation period are used. The monitored temperatures and the temperatures monitored at the end of the first temperature change calculation period are used to calculate the peak and average temperature changes, which are marked as the third temperature change peak and the third temperature change average. The set values ​​for the third temperature change peak and the third temperature change average of the data center are extracted. These are then compared with their corresponding set values. If neither the third temperature change peak nor the third temperature change average exceeds its corresponding set value, the third temperature change peak is added to the second temperature change peak to obtain the third cumulative temperature change peak, and the third temperature change average is added to the second temperature change average to obtain the third cumulative temperature change average. Finally, the set values ​​for the third cumulative temperature change peak and the third cumulative temperature change average of the data center are extracted.The third cumulative temperature change peak value and the third cumulative temperature change average value are compared with their corresponding set values. If the third cumulative temperature change peak value and the third cumulative temperature change average value are less than their corresponding set values, a stop signal is generated and sent to the monitoring and early warning program, and this round of temperature change calculation ends. Conversely, if any of the calculated values ​​in the first, second, and third calculations exceed their corresponding set values, a leakage signal is generated and sent to the early warning processing module. The early warning processing module obtains the location information of the sub-zone based on the received leakage signal and contacts personnel for maintenance. The specific process is as follows: The location information of the monitoring sub-zone is calculated based on the temperature change triggered by the positioning sensor. Taking the monitoring sub-zone as the center, the location of each maintenance personnel's mobile terminal within the radius is obtained. The location of the monitoring sub-zone and the location of each maintenance personnel's mobile terminal are connected to obtain the maintenance distance. The maintenance distances are arranged in ascending order to obtain the minimum maintenance distance and mark the corresponding maintenance personnel as the preferred personnel. An emergency signal is generated and sent to the preferred personnel. The preferred personnel receive the emergency signal and repair the oil and gas pipeline leak in the monitoring sub-zone.

2. The system for monitoring and early warning of oil and gas pipeline leaks according to claim 1, characterized in that, The data acquisition module is equipped with a monitoring and early warning system according to on-site requirements, and monitors soil temperature data in real time within the total monitoring section length through the monitoring and early warning system. The specific process is as follows: The output of the data acquisition module is connected to the input of the soil temperature analysis module to obtain the length of the current total monitoring segment. The length of each monitoring sub-zone is divided proportionally according to the length of the total monitoring segment, and each monitoring sub-zone is numbered in sequence. Temperature sensors are installed in each monitoring sub-zone proportionally according to the length. The temperature monitoring and acquisition time interval in each monitoring sub-zone is set to Ki. Temperature data information of each monitoring sub-zone is collected in real time through temperature sensors to obtain the temperature parameter values ​​of each monitoring sub-zone. The acquired temperature parameter values ​​for each monitoring sub-zone are sent to the soil temperature analysis module.

3. A method for monitoring and early warning of oil and gas pipeline leaks, characterized in that, The specific steps of the system for monitoring and early warning of oil and gas pipeline leaks as described in any one of claims 1-2 are as follows: F1. Data Acquisition: Install a monitoring and early warning system according to site requirements, and monitor soil temperature data in real time within the total monitoring section length through the monitoring and early warning system. F2. Soil temperature analysis: Based on the received temperature parameter values, analyze the temperature changes in each monitoring sub-zone, and send the leakage signal at time 0 to the leakage triple cumulative analysis module. F3. Leakage Triple Progression Analysis: Based on the set leakage triple progression effect, compare and calculate to determine whether the sub-zone is leaking due to the trigger temperature change. F4. Early Warning Handling: Based on the received leakage signal, calculate the location information of the sub-zone by obtaining the temperature change of the trigger, and contact personnel for maintenance.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the method for monitoring and early warning of oil and gas pipeline leaks as described in claim 3.

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