Oil and gas pipeline leakage gas rapid identification and positioning system

Abstract

The invention relates to the technical field of oil and gas storage and transportation, in particular to an oil and gas pipeline leakage gas rapid identification and positioning system which comprises a segmented monitoring module, a data storage module, a segmented prediction module and a multi-stage early warning module. The sectional monitoring module is used for setting monitoring intervals, dividing a pipeline into a plurality of pipe sections according to the monitoring intervals, and collecting operation data of each pipe section; the data storage module is used for storing the operation data of each pipe section, storing the operation data, leakage accidents and processing schemes of each past pipe section as historical data, and establishing a database by using the historical data; the segmentation prediction module is used for generating a risk prediction report of a leakage accident of each pipe section according to the operation data variation of each pipe section and sending the risk prediction report to the multi-stage early warning module; the segmentation prediction module is also used for sending a monitoring adjustment suggestion to the segmentation monitoring module according to the risk prediction report; the structure is complete, and the monitoring condition of leaked gas can be effectively optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas storage and transportation, and particularly relates to a system for quickly identifying and locating leaked gas in oil and gas pipelines. Background Art

[0002] As the main transportation mode of oil and natural gas, the safety of oil and gas pipelines is directly related to the stability of energy supply and environmental safety. Leakage not only causes resource loss, but also may pose a serious threat to the environment and human health. With the improvement of people's environmental awareness, higher requirements have been put forward for the monitoring and location of oil and gas pipeline leaks to ensure that timely measures can be taken to prevent the situation from expanding.

[0003] In the existing systems for identifying and locating leaked gas in oil and gas pipelines, the basic data such as the pressure, temperature, and flow rate of the oil and gas pipelines are mainly monitored, and then the monitored data is analyzed to determine whether there is gas leakage in the oil and gas pipelines and locate the position of the gas leakage; however, such a method is not conducive to the staff to cope with sudden gas leakage accidents due to the lack of prediction of the pipeline state.

[0004] In summary, how to solve the problem that in the existing technologies for identifying and locating leaked gas in oil and gas pipelines, due to the lack of prediction of the pipeline state, the position of the gas leakage cannot be quickly identified and located has become a difficult problem that urgently needs to be solved in the current field. Therefore, it is necessary to propose a more reasonable system for quickly identifying and locating leaked gas in oil and gas pipelines. Summary of the Invention

[0005] To solve the above problems, the present invention provides a system for quickly identifying and locating leaked gas in oil and gas pipelines. Through the design of a segmented monitoring module, the accuracy of monitoring various data of the oil and gas pipelines can be improved; the data storage module can effectively store various types of data, and the segmented prediction module can predict the data change conditions of each pipe section, thereby improving the staff's ability to cope with sudden gas leakage accidents.

[0006] To achieve the above object, the technical solution of the present invention is as follows: A system for quickly identifying and locating leaked gas in oil and gas pipelines includes a segmented monitoring module, a data storage module, a segmented prediction module, and a multi-level early warning module.

[0007] The segmented monitoring module is used to set a monitoring interval. The segmented monitoring module divides the pipeline into several pipe sections according to the monitoring interval and collects the operation data of each pipe section; the segmented monitoring module is also used to transmit the operation data of each pipe section to the data storage module.

[0008] A data storage module, which is used to store the operation data of each pipe section, and store the operation data, leakage accidents and treatment plans of each pipe section in the past as historical data, and establish a database using the historical data.

[0009] A segmented prediction module, which is used to generate a risk prediction report for leakage accidents of each pipe section according to the change amount of the operation data of each pipe section and send it to a multi-level early warning module; the segmented prediction module is also used to send monitoring adjustment suggestions to the segmented monitoring module according to the risk prediction report.

[0010] The segmented prediction module is also used to retrieve the historical operation data with the highest similarity and its related leakage accidents and treatment plans in the database according to the operation data of the pipe section with the risk of leakage accident, and generate an emergency treatment plan based on this treatment plan; if a leakage accident occurs, the emergency treatment plan will be adjusted according to the difference between the current operation data and the historical operation data to generate a treatment plan.

[0011] A multi-level early warning module, which is used to set different levels of early warning prompts; the multi-level early warning module is also used to receive the risk prediction report and send out corresponding-level early warning prompts according to the content of the risk prediction report.

[0012] Furthermore, the segmented monitoring module is also used to set the limit deviation of the operation data; the segmented monitoring module compares the current operation data of each pipe section with the historical operation data of each pipe section, calculates whether the difference between the two sets of operation data exceeds the limit deviation, and judges whether there is a gas leakage in each pipe section according to the calculation result.

[0013] Furthermore, the operation data includes the pipeline appearance, pipeline pressure, pipeline temperature, gas flow rate, gas concentration and sound wave.

[0014] Furthermore, the segmented monitoring module includes a basic data monitoring unit and a sound wave positioning unit.

[0015] The basic data monitoring unit is used to monitor the pipeline appearance, pipeline pressure, pipeline temperature, gas concentration and gas flow rate of each pipe section, judge whether there is a gas leakage in each pipe section and judge the specific pipe section where the gas leakage occurs.

[0016] The sound wave positioning unit is used to confirm the specific location where the gas leakage occurs according to the sound wave on the specific pipe section where the gas leakage occurs.

[0017] Furthermore, the risk prediction report includes the predicted risk incidence rate, risk severity and the cause of the risk.

[0018] Furthermore, the monitoring adjustment suggestion includes the monitoring priority of each pipe section; among them, the higher the risk incidence rate and risk severity, the higher the monitoring priority of the pipe section.

[0019] Furthermore, the warning prompts include information prompts, indicator light prompts, and voice broadcast prompts in order from low level to high level.

[0020] Furthermore, the multi-level warning module is also used to receive a treatment plan and send the treatment plan to the remote control terminal for optimization and confirmation.

[0021] Furthermore, the reasons for historical leakage accidents are stored in the database.

[0022] Furthermore, the segment prediction module generates accident prevention suggestions based on the change amounts of the operation data of each pipe segment.

[0023] The technical principle of the above solution is as follows:

[0024] Through the segment monitoring module, the oil and gas pipeline can be divided into several pipe segments according to the set monitoring interval, and the operation data of each pipe segment can be collected. These data include the pipeline appearance, pipeline pressure, pipeline temperature, gas flow rate, gas concentration, and sound waves, etc. The segment monitoring module also has a comparison function, which can compare the operation data of the current pipe segment with the historical data, and judge whether there is a gas leakage situation by calculating whether the difference between the two sets of data exceeds the preset limit deviation. The segment monitoring module can also adjust the monitoring strategy according to the risk assessment report of the segment prediction module to improve the monitoring priority of the pipe segments with higher risks.

[0025] The data storage module is responsible for storing the operation data of each pipe segment, and storing the past leakage accidents and their treatment plans as historical data, so as to establish a database.

[0026] The segment prediction module generates a risk assessment report for leakage accidents according to the change amounts of the operation data of each pipe segment; the report content includes the predicted risk occurrence rate, risk severity, and the reasons for the risk. The segment prediction module can also retrieve historical gas leakage accidents similar to the current leakage risk in the database, and generate an emergency treatment plan based on this; if a leakage accident occurs, the segment prediction module will adjust the emergency treatment plan according to the difference between the current data and the historical data to generate the final treatment plan; the segment prediction module can also generate accident prevention suggestions according to the reasons for the leakage accidents.

[0027] The multi-level warning module is responsible for setting different levels of warning prompts, including information prompts, indicator light prompts, and voice broadcast prompts, etc. The level and content of the warning prompts can be dynamically adjusted according to the content of the risk assessment report. The multi-level warning module can also receive the treatment plan and send it to the remote control terminal for optimization and confirmation.

[0028] Adopting the above solution has the following beneficial effects:

[0029] 1. Through the design of the segmented monitoring module, the present invention divides the pipeline into several pipe segments and collects detailed operation data for each pipe segment. Compared with the overall monitoring of the entire pipe segment in the prior art, this method realizes refined monitoring of the pipeline, which can not only quickly determine whether there is gas leakage in the pipeline, but also locate by pipe segment, so as to more quickly and accurately find the specific location where the gas leakage occurs, effectively improving the monitoring efficiency of the pipeline.

[0030] 2. Through the design of the segmented prediction module, the present invention can generate a risk prediction report based on the change amount of operation data, including the predicted risk incidence rate, risk severity and reasons, so as to identify high-risk areas in advance. At the same time, providing monitoring adjustment suggestions for the segmented monitoring module also enables the staff to take corresponding preventive measures to reduce the incidence rate of gas leakage accidents. At the same time, the multi-level warning module dynamically adjusts the warning prompt level according to the content of the risk prediction report to ensure timely and effective transmission of risk information.

[0031] 3. When a leakage accident occurs, the segmented prediction module can quickly retrieve historical similar cases and generate an emergency treatment plan based on this. This not only shortens the emergency response time, but also ensures the pertinence and effectiveness of the treatment plan. In addition, by adjusting the plan to adapt to the current situation, the flexibility of emergency treatment can be further improved. The multi-level warning module will also transmit the treatment plan to the remote control terminal for the staff to conduct final optimization and confirmation, further improving the rationality and feasibility of the treatment plan.

[0032] 4. The data storage module can store the pipeline operation data and the leakage accident treatment plan, providing valuable data support for subsequent monitoring, warning and emergency treatment.

[0033] The additional aspects and advantages of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a schematic flow chart of a rapid gas identification and location system for an oil and gas pipeline according to the present invention.

[0035] Figure 2 It is a schematic flow chart of the segmented monitoring module in a rapid gas identification and location system for an oil and gas pipeline according to the present invention.

[0036] Figure 3 It is a schematic flow chart of the segmented prediction module in a rapid gas identification and location system for an oil and gas pipeline according to the present invention.

[0037] Figure 4It is a schematic flow diagram of the multi - level warning module in a system for rapid identification and location of leaked gas in oil and gas pipelines according to the present invention. Detailed implementation mode

[0038] The following is a further detailed description through specific implementation modes:

[0039] As shown in the implementation example Figures 1 - 4 A system for rapid identification and location of leaked gas in oil and gas pipelines includes a sectional monitoring module for monitoring pipelines, a data storage module for storing various pipeline data, a sectional prediction module for predicting the operation conditions of pipelines, and a multi - level warning module for issuing warning prompts; each module is connected by signals to each other.

[0040] The main functions of each module are as follows:

[0041] The sectional monitoring module is used to set the monitoring interval. The sectional monitoring module divides the pipeline into several pipe segments according to the monitoring interval and collects the operation data of each pipe segment; the sectional monitoring module is also used to transmit the operation data of each pipe segment to the data storage module. The sectional monitoring module is also used to set the limit deviation of the operation data; the sectional monitoring module compares the current operation data of each pipe segment with the historical operation data of each pipe segment, calculates whether the difference between the two sets of operation data exceeds the limit deviation, and judges whether there is gas leakage in each pipe segment according to the calculation result. The operation data includes the appearance of the pipeline, pipeline pressure, pipeline temperature, gas flow rate, gas concentration, and sound wave.

[0042] The sectional monitoring module includes a basic data monitoring unit and a sound wave positioning unit.

[0043] The basic data monitoring unit is used to monitor the appearance of the pipeline, pipeline pressure, pipeline temperature, gas concentration, and gas flow rate of each pipe segment, judge whether there is gas leakage in each pipe segment, and judge the specific pipe segment where gas leakage occurs. In this embodiment, the basic data monitoring unit mainly monitors the outer pipeline of the pipeline through a camera, monitors the pipeline pressure through a pressure sensor, monitors the pipeline temperature through a temperature sensor, and monitors the gas concentration through a gas monitor.

[0044] The sound wave positioning unit is used to confirm the specific location where gas leakage occurs according to the sound wave on the specific pipe segment where gas leakage occurs. In this embodiment, the sound wave positioning unit mainly monitors the sound wave on the pipe segment through a sound wave detector.

[0045] For example, if the operator sets the monitoring interval to 50 m and the limit deviation to 20%, the segmented monitoring module will take each 50 m as a pipe section, collect the operation data of each pipe section, and label and name each pipe section in the order of "Pipe Section 1", "Pipe Section 2", and "Pipe Section 3", which facilitates quickly locating and searching for the pipe section in case of a gas leakage accident.

[0046] Suppose that in the historical normal operation data of "Pipe Section 2", the pipeline pressure is 10 MPa, while the current pipeline pressure of "Pipe Section 2" is 6 MPa. Through calculation, the segmented monitoring module finds that the current operation data differs from the historical normal operation data by 40%, which is much greater than the limit deviation. Therefore, the basic data monitoring unit will determine that there is a gas leakage in the pipeline, and the specific pipe section is "Pipe Section 2".

[0047] Since the sound waves emitted from the gas leakage location are significantly different from those during normal gas transportation, at this time, the sound wave positioning unit will determine the specific location of the gas leakage by monitoring the emission point of abnormal sound waves on "Pipe Section 2". For example, if the emission point of the abnormal sound wave is about 39 m away from the starting position of "Pipe Section 2", then the specific location of the gas leakage is the length of the front end of "Pipe Section 2" plus 39 m, thus calculating that the specific location of the gas leakage is at the 89 m position of the pipeline. This enables the operator to quickly identify and locate the specific location of the gas leakage.

[0048] The data storage module is used to store the operation data of each pipe section, and store the operation data, leakage accidents, and treatment plans of each past pipe section as historical data, and establish a database using the historical data. The reasons for historical leakage accidents are stored in the database. In this embodiment, the data storage module is mainly constructed based on a memory to achieve the storage of various types of data. The data storage module can store pipeline operation data and leakage accident treatment plans, providing valuable data support for subsequent monitoring, early warning, and emergency treatment.

[0049] The segmented prediction module is used to generate a risk prediction report for leakage accidents of each pipe section based on the change amount of the operation data of each pipe section and send it to the multi-level early warning module; the risk prediction report includes the predicted risk incidence rate, risk severity, and the reasons leading to the risk. The segmented prediction module will calculate the risk incidence rate based on historical operation data, judge the risk severity according to the gas leakage volume, and analyze the reasons leading to the risk based on the pipeline operation data situation.

[0050] For example, assume that in the historical normal operation data of "Pipe Section 3", the pipe temperature is 8°C and its limit deviation is 50%. Due to the high weather temperature, the pipe temperature rises to 38°C, and the difference between the two is much larger than the limit deviation. Due to factors such as the principle of thermal expansion and contraction and the large temperature difference between the inside and outside of the pipe, the stress at the pipe connection will increase, and gas leakage accidents are likely to occur. Assume that in the database, the number of gas leakage accidents occurring in each pipe due to the temperature change exceeding the limit deviation is 40 times, and the number of times the limit deviation is exceeded but no gas leakage accident occurs is 100 times. The gas transmission volume of "Pipe Section 3" is large, and the segmented prediction module will generate a risk prediction report for "Pipe Section 3": the risk incidence rate is about 40%, the risk severity is relatively high, and the leakage reason is the too high pipe temperature.

[0051] The segmented prediction module generates accident prevention suggestions based on the change amount of the operation data of each pipe section.

[0052] Taking the above "Pipe Section 3" as an example, due to weather reasons, the temperature of "Pipe Section 3" is too high and gas leakage accidents are likely to occur. Therefore, the segmented prediction module will provide accident prevention suggestions for the staff: the current temperature of "Pipe Section 3" is too high, and it is recommended to carry out sunshade and cooling treatment to avoid gas leakage accidents.

[0053] The segmented prediction module is also used to send monitoring adjustment suggestions to the segmented monitoring module according to the risk prediction report. The monitoring adjustment suggestions include the monitoring priorities of each pipe section; among them, the higher the risk incidence rate and the risk severity, the higher the monitoring priority of the pipe section.

[0054] The segmented prediction module is also used to retrieve the historical operation data with the highest similarity and its related leakage accidents and treatment plans in the database according to the operation data of the pipe sections at risk of leakage accidents, and generate an emergency treatment plan based on this treatment plan; if a leakage accident occurs, the emergency treatment plan will be adjusted according to the difference between the current operation data and the historical operation data to generate a treatment plan.

[0055] The multi-level early warning module is used to set different levels of early warning prompts; the multi-level early warning module is also used to receive the risk prediction report and send corresponding-level early warning prompts according to the content of the risk prediction report. The early warning prompts include information prompts, indicator light prompts, and voice broadcast prompts from low level to high level in turn.

[0056] When the risk level is low, an information prompt is sent to the operator; when the risk level is medium, an indicator light prompt is sent to the operator; when the risk level is high, a voice broadcast prompt is sent to the operator. The multi-level early warning module can dynamically adjust the early warning prompt level according to the risk level, and ensure the timely and effective transmission of risk information according to the content of the risk prediction report, improving the operator's ability to respond to gas leakage accidents.

[0057] The multi-level early warning module is also used to receive the treatment plan, send the treatment plan to the remote control terminal for optimization and confirmation, so as to further improve the rationality and feasibility of the treatment plan.

[0058] Through the design of the segmented monitoring module, the pipeline is divided into several pipe segments, and the detailed operation data of each pipe segment is collected. Compared with the overall monitoring of the entire pipeline in the prior art, this method realizes the refined monitoring of the pipeline, which can not only quickly judge whether there is gas leakage in the pipeline; but also locate by pipe segment, so that the specific location of the gas leakage can be found more quickly and accurately, effectively improving the monitoring efficiency of the pipeline.

[0059] Through the design of the segmented prediction module, a risk prediction report can be generated according to the change amount of the operation data, including the predicted risk incidence rate, risk severity and reasons, so that high-risk areas can be identified in advance. At the same time, providing monitoring adjustment suggestions for the segmented monitoring module also enables the staff to take corresponding preventive measures to reduce the incidence of gas leakage accidents. At the same time, the multi-level early warning module dynamically adjusts the early warning prompt level according to the content of the risk prediction report to ensure timely and effective transmission of risk information.

[0060] In the event of a leakage accident, the segmented prediction module can quickly retrieve historical similar cases and generate an emergency treatment plan based on this. This not only shortens the emergency response time, but also ensures the pertinence and effectiveness of the treatment plan. In addition, by adjusting the plan to adapt to the current situation, the flexibility of emergency treatment can be further improved.

[0061] Obviously, the above embodiments are only examples given for clear illustration, and are not limitations on the implementation manners. For those of ordinary skill in the art, other different forms of changes or modifications can be made on the basis of the above description. It is not necessary and impossible to list all implementation manners here. And the obvious changes or modifications derived therefrom still fall within the protection scope of the present invention.

Claims

1. A system for rapid identification and positioning of leaking gas in oil and gas pipelines, characterized in that: It includes segmented monitoring module, data storage module, segmented prediction module and multi-level early warning module; The segmented monitoring module is used to set the monitoring interval; the segmented monitoring module divides the pipeline into several segments according to the monitoring interval and collects the operation data of each segment; the segmented monitoring module is also used to transmit the operation data of each segment to the data storage module; The data storage module is used to store the operation data of each pipe section, and store the past operation data of each pipe section, leakage accidents and treatment plans as historical data, and use the historical data to establish a database; The segment prediction module is used to generate a risk estimation report of leakage accidents in each pipe section according to the change in the operation data of each pipe section and send it to the multi-level warning module; the segment prediction module is also used to issue monitoring adjustment suggestions to the segment monitoring module according to the risk estimation report; The segmented prediction module is also used to retrieve the historical operation data with the highest similarity and its related leakage accidents and treatment plans in the database according to the operation data of the pipe section with leakage accident risk, and generate an emergency treatment plan using the treatment plan as a template; If a leakage accident occurs, the emergency response plan will be adjusted and a treatment plan will be generated based on the difference between the current operation data and the historical operation data; Multi-level warning module, used to set different levels of warning prompts; The multi-level warning module is also used to receive risk assessment reports and issue warning prompts of corresponding levels based on the content of the risk assessment reports.

2. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 1 is characterized in that: The segmented monitoring module is also used to set the limit deviation of the operating data; the segmented monitoring module compares the current operating data of each pipe section with the historical operating data of each pipe section, calculates whether the difference between the two sets of operating data exceeds the limit deviation, and determines whether there is a gas leak in each pipe section based on the calculation results.

3. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 2 is characterized in that: Operation data include pipeline appearance, pipeline pressure, pipeline temperature, gas flow, gas concentration and sound waves.

4. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 3 is characterized in that: The segment monitoring module includes a basic data monitoring unit and an acoustic wave positioning unit; Basic data monitoring unit, used to monitor the pipeline appearance, pipeline pressure, pipeline temperature, gas concentration and gas flow of each pipeline section, determine whether there is gas leakage in each pipeline section and determine the specific pipeline section where gas leakage occurs; The acoustic wave positioning unit is used to confirm the specific location of the gas leakage based on the acoustic waves on the specific pipe section where the gas leakage occurs.

5. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 4 is characterized in that: The risk assessment report includes the estimated risk occurrence rate, risk severity and the causes of the risk.

6. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 5 is characterized in that: The monitoring adjustment suggestions include the monitoring priority of each pipeline section; among them, the higher the risk occurrence rate and risk severity, the higher the monitoring priority of the pipeline section.

7. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 6 is characterized in that: The warning prompts include information prompts, indicator light prompts and voice broadcast prompts from low level to high level.

8. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 7 is characterized in that: The multi-level warning module is also used to receive treatment plans and send the treatment plans to the remote control terminal for optimization and confirmation.

9. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 8, characterized in that: The database stores the causes of historical leakage accidents.

10. The oil and gas pipeline leak gas rapid identification and positioning system according to claim 9, characterized in that: The segmented prediction module generates accident prevention suggestions based on the changes in the operating data of each pipeline segment.

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