CN116697276B - Thick oil thermal recovery medium conveying pipeline leakage monitoring method and system based on virtual sensing - Google Patents
Thick oil thermal recovery medium conveying pipeline leakage monitoring method and system based on virtual sensingInfo
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- CN116697276B CN116697276B CN202310598052.2A CN202310598052A CN116697276B CN 116697276 B CN116697276 B CN 116697276B CN 202310598052 A CN202310598052 A CN 202310598052A CN 116697276 B CN116697276 B CN 116697276B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
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Abstract
The invention provides a thickened oil thermal recovery medium conveying pipeline leakage monitoring method and a system based on virtual sensing, which are used for acquiring and transmitting data and processing data through operating characteristic parameters such as pressure, temperature, flow and the like of an inlet and an outlet of a pipeline, and solving by adopting a software-based leak detection algorithm model, comparing simulation results with field data, and determining the running state and the leak parameters of the manifold. The invention has the advantages that the invention is suitable for real-time monitoring and daily maintenance of pipeline leakage state of offshore thermal production platform, overcomes the limitation of space and extreme environment, simulates common normal working conditions such as steam injection, valve opening and closing, leakage and the like by means of system simulation, test and the like, and realizes dynamic simulation of valve opening and closing, injection, leakage and the like by setting relevant working conditions in test sections and performing test and data verification by taking saturated steam and superheated steam as working media. By researching working condition changes such as the opening or closing process of the valve pressure difference, the overall performance of the thick oil thermal recovery medium leakage detection system and the accuracy of the virtual sensing model are improved.
Description
Technical Field
The invention relates to the field of thick oil thermal recovery medium conveying pipeline leakage monitoring, in particular to a thick oil thermal recovery medium conveying pipeline leakage monitoring method and system based on virtual sensing.
Background
The heavy oil has high asphalt colloid content, low wax content, high viscosity, difficult flow, high exploitation difficulty and other problems. The heavy oil thermal recovery is used as a main means for heavy oil development and has been widely applied to the development of heavy oil reservoirs at home and abroad. The steam huff and puff is a main method for thick oil exploitation, and a certain amount of steam is injected into an oil well, the well is closed for a period of time, and after the heat energy of the steam is diffused to an oil layer, the well is opened for production so as to improve the yield increase of the thick oil. Compared with land oilfield steam huff and puff thermal recovery, the offshore thermal recovery has the characteristics of small space, high steam injection temperature, high steam injection pressure and the like, and once high-temperature and high-pressure steam leaks, serious consequences are caused, and threat is caused to inspection personnel. Therefore, the leakage monitoring method and system are developed by researching the leakage monitoring technology of the high-temperature high-pressure steam pipeline, and the safety guarantee level of unconventional oil gas development is improved.
The thickened oil thermal recovery medium has the characteristics of high temperature and high pressure, and the detection means for the leakage detection of the high temperature and high pressure steam pipeline is generally divided into a detection method based on hardware and a detection method based on software.
The existing steam leakage detection method has the problems that the method based on hardware detection such as infrared thermal imaging, optical fiber detection and the like is high in cost, the leakage amount cannot be calculated quantitatively, meanwhile, equipment is not suitable or precision is easily affected due to the environmental and space limitations of a thermal recovery platform and the like, the detection method based on software is mostly used for fluids such as liquid, natural gas and the like, is generally suitable for long-distance pipelines, is less in application to high-temperature and high-pressure media, is greatly affected by temperature due to unstable steam property, causes measurement deviation easily, and cannot be ensured in accuracy.
The existing pipeline leakage monitoring method and system mainly rely on related hardware monitoring equipment or a sensor system to acquire pipeline real-time operation data, simulation solution is carried out on characteristic parameters of internal operation of a pipeline, and a thick oil thermal recovery steam pipeline is influenced by various factors such as working condition change, environmental temperature, operating pressure and the like in the operation process, so that larger errors exist in the aspect of leakage monitoring. Most detection equipment is relatively slow in calculation speed and poor in real-time performance for steam pipeline related calculation, and is not fully applicable to conditions such as complex pipeline systems and pipeline operation under variable working conditions.
Disclosure of Invention
The invention overcomes the defects in the prior art and provides a thickened oil thermal recovery medium conveying pipeline leakage monitoring method and system based on virtual sensing.
The aim of the invention is achieved by the following technical scheme.
The thick oil thermal recovery medium conveying pipeline leakage monitoring method based on virtual sensing fully considers the fluid flow parameter change based on the software leakage method, has high simulation output precision of a model and quick equipment state identification phase response, and has low equipment cost, and the method specifically comprises the following steps:
Step 1, deploying a sensor in an acquisition pipeline, transmitting data acquired by the sensor to a remote upper computer through a remote communication means, and forming an operation and verification data set of physical properties and related characteristic parameters of equipment;
step 2, combining a fluid transient model and a thermodynamic model, and establishing a pipeline virtual model according to the change of the speed, pressure, density and viscosity parameters of the fluid in the pipeline;
Step 3, solving the flow field related data in the pipeline under the boundary condition of the field by using the pipeline virtual model established in the step 2, constructing a field pipeline operation data set and a virtual pipeline simulation data set by using the acquired data and the simulation data,
The on-site pipeline operation data set consists of steam pipeline operation data, the operation data are collected and data transmission is realized through deployed sensors, and the sensors are deployed at the inlet and outlet of the pipeline to monitor inlet and outlet pressure, temperature and speed parameter data in a key way;
The virtual pipeline simulation data set comprises a steam pipeline transportation data set and a steam pipeline leakage data set, wherein the steam pipeline transportation data set is constructed according to parameter data calculated by a pipeline steam medium flow model, and the steam pipeline leakage data set is constructed according to parameter data calculated by a pipeline steam leakage model;
Comparing the data of the on-site pipeline operation data set and the virtual pipeline simulation data set, and comparing the calculated value with the verification data precision to finish leakage identification, leakage quantity estimation and leakage early warning;
performing data association on the leakage identification through field data of known equipment working conditions and model simulation calculation results of corresponding working conditions, determining a normal operation threshold value of the equipment, and performing comparison on the leakage identification through real-time simulation model calculation results and the leakage threshold value to determine the leakage identification;
The leakage quantity estimation is determined through the difference between the mass flow difference of the inlet and the outlet of the pipeline and the leakage threshold value;
The leakage early warning is carried out by judging whether the difference value between the absolute value of the inlet and outlet mass flow difference value of the real-time simulation result and the leakage threshold value is larger than zero or not, and calculating the leakage quantity estimated value and displaying the subsequent result;
The model mainly comprises a pipeline virtual model which is a pipeline steam medium flow model, wherein the continuity equation of steam flow of the pipeline steam medium flow model is that,
In the formula,
Ρ -gas density, kg/m 3;
x-distance of gas along the flow direction of the pipeline, m;
w-flow rate of gas in the pipeline, m/s;
The flow area of the section of the A-pipeline, m 2;
the momentum equation of the steam flow of the pipe steam medium flow model is,
Wherein, p-gas pressure, pa, D-pipe inner diameter, m, lambda-friction resistance coefficient;
The energy equation of the steam flow of the pipeline steam medium flow model is that,
Wherein, the enthalpy value of h-gas, J/kg; The heat exchange rate per unit length of tube of the gas per unit mass flow is W/m 2.
The method for solving the pipeline steam medium flow model is based on a finite volume and finite difference method, partial differential terms in the model are discretized, a numerical discrete formula in a high-precision format is combined with a corresponding limiter, a model equation is solved in a set implicit iteration mode based on coefficient nonlinear characteristics of a momentum equation, simulation data in time dimensions in the pipeline are obtained according to internal iteration of the node coefficient equation and external iteration of the equation set and residual error requirements before and after iteration, the data are mapped with real operation data, and the relation between a virtual pipeline and the real pipeline is obtained under the normal operation condition, so that support is provided for leakage discrimination and early warning.
In the step 3, the steam pipeline leakage data set is calculated and judged by adopting a pipeline steam leakage model, the pipeline steam leakage model equation is that,
Wherein:
The internal energy of the u-gas, J/kg;
h-enthalpy of gas, J/kg;
ρ -gas density, kg/m 3;
p-gas pressure, pa;
The flow rate of w gas in the pipeline, m/s;
t-is time, s;
x-is the distance of the gas along the flow direction of the pipeline, m
The flow area of the section of the A-pipeline, m 2;
g - g gravity, m/s 2;
Lambda-coefficient of friction;
d, the inner diameter of the pipeline, m;
-heat exchange rate per unit mass flow of gas per unit tube length, in W/m 2;
Mass leak rate at the M Leakage of -leak location, unit kg/(m.s);
Momentum leak rate at Mv Leakage of -leak location, unit N/m 3;
e Leakage of -the energy leakage rate at the leakage site, in W/m.
The calculation flow of the pipeline steam leakage model specifically comprises the following steps:
s1, inputting initial recognition conditions;
s2, setting a fault condition;
S3, reading in fault parameters;
S4, taking pressure, temperature and flow data acquired by the inlet and the outlet into a pipeline steam leakage model for calculation;
S5, carrying out residual judgment on the calculation result, ending calculation when the calculation result meets the condition, and returning to the step S3 when the calculation result does not meet the condition, and carrying out recalculation.
In the step 3, the on-site pipeline operation data set and the virtual pipeline simulation data set are compared by adopting a leakage early warning algorithm, the leakage early warning algorithm performs preliminary early warning determination by comparing on-site inlet and outlet data according to inlet and outlet flow calculation of transient results under different working conditions, performs preliminary judgment on inlet and outlet simulation data combined with a pressure point analysis method and a mass balance method, performs accurate treatment on a leakage early warning threshold value by combining analysis comparison of on-site and simulation data aiming at specific inlet and outlet parameters after judging leakage, and establishes a model on various methods in terms of leakage identification and leakage quantity estimation by a data statistics method so as to realize establishment of the leakage early warning algorithm.
A thickened oil thermal recovery medium transfer line leak monitoring system based on virtual sensing, comprising:
The sensor system is arranged on the pipeline system, is arranged at the position of an inlet and an outlet of the pipeline and the position of the pipeline with the pipe diameter change according to the fluid mechanics theory related model, and is used for acquiring corresponding data information and comprises a pressure sensor, a temperature sensor and a flow sensor;
The data acquisition equipment comprises a data processor and an infinite communication module, the sensor performs data transmission with the node controller through serial communication, the node controller consists of a control chip of the data processor and a peripheral circuit and is responsible for signal acquisition and transmission, data acquisition and communication transmission of each node are realized, the data of the sensor is transmitted to the wireless communication module through the node controller, and the wireless communication module packages the data and transmits the data to the cloud server;
The leakage early warning system comprises a pipeline steam medium flow model, a pipeline steam leakage model and a leakage monitoring early warning algorithm, wherein the pipeline steam medium flow model is adopted to perform data simulation, relevant data analysis is performed according to the on-site and simulation results, and leakage judgment, leakage early warning and relevant leakage quantity estimation are performed through the pipeline steam leakage model and the leakage monitoring early warning algorithm;
the man-machine interaction system is used for carrying out normal operation of pipelines, acquisition of related information of leakage accidents and leakage alarm processing by related operators, guiding on-site personnel to take measures and carrying out characteristic processing, noise reduction analysis and signal filtering content on the data acquired by the sensors so as to realize validity processing of the acquired data;
and the database is used for storing and managing operation data, pipeline physical property data and simulation result data related data.
The beneficial effects of the invention are as follows:
1. Compared with the conventional physical sensing detection equipment, the virtual sensing detection system is lower in cost, is more suitable for development and daily maintenance, can overcome the limitation of space and extreme environments, and particularly can be redesigned according to requirements for insufficient space, high temperature and corrosive environments of an offshore thermal recovery platform, the virtual sensing detection system is convenient to use, and physical sensing means such as infrared detection and the like are relocated through mechanical intervention.
2. When the virtual sensing model is constructed, the variable working condition operation condition of the steam injection process is considered, and the common normal working conditions (steam injection, switching valve and well closing) are simulated by means of system simulation, test and the like. By researching the system parameter change in the valve pressure difference opening or closing process, a reference is provided for the overall performance design of the thick oil thermal recovery medium leakage detection system, and the accuracy of the virtual sensing model is improved.
Drawings
FIG. 1 is a schematic diagram of a thickened oil thermal recovery medium conveying pipeline leakage monitoring system based on virtual sensing;
FIG. 2 is a computational flow diagram of a pipeline vapor leakage model;
FIG. 3 is a flow chart of a leak identification and leak estimation process.
Detailed Description
The technical scheme of the invention is further described by specific examples.
Examples
According to the invention, the sensor system is arranged at the inlet and outlet of the monitored pipeline, and is connected with the data acquisition and transmission system module to realize on-site data acquisition and transmission, and the data management is carried out by combining an upper computer database. The sensor system module consists of an electromagnetic flowmeter, a pressure sensor and a temperature sensor, wherein the sensors are arranged on two sides of an inlet and an outlet of a pipeline, the specific sensor selection is required to meet the high-temperature high-pressure numerical value requirement of a thermal recovery medium, meanwhile, the sampling response time of the sensor is short, and the signal acquisition frequency and the accuracy are high so as to meet the high-accuracy model input of the follow-up model solution. And the data acquisition and transmission system completes the database storage of the data from the on-site sensor equipment to the upper computer platform end by combining with communication protocols such as MQTT, TCP/IP and the like under the condition of meeting the maximum sampling frequency requirement of the sensor data, and realizes the collection of the running data from the medium conveying pipeline equipment. The simulation and the field device state analysis result are completed by a man-machine interaction front end deployed at a platform end, and the leakage early warning system is completed by a rear-end programming frame and a database deployed at an upper computer. The man-machine interaction front end mainly adopts a Vue front end frame construction webpage technology to display leakage monitoring conditions, so that related operators can perform normal operation of pipelines, leakage accident related information acquisition and leakage alarm processing, and on-site personnel can be guided to take measures. The rear end part data processing part is mainly used for performing characteristic processing, noise reduction analysis, signal filtering and the like on the collected data of the sensor, so that the effectiveness processing of the collected data is realized. The model simulation module processes the data of the sensor collected data and then is used as model input, a specific model solving method is adopted according to the establishment of a virtual pipeline model and the determination of boundary conditions and initial recognition conditions, simulation data results are calculated to be compared with field data and verification data, leakage conditions and specific results are determined, the relation between monitoring parameters and performance parameters under different leakage amounts and different working conditions and the leakage amount is deduced, the mathematical relation between the monitoring parameters and the leakage amount is deduced, meanwhile, the mutual influence of pressure and temperature when steam flows in the pipeline is considered in the aspect of model establishment, so that the established pipeline model describes the real flow state of the steam in the pipeline as accurately as possible, and the performance of a monitoring system is improved. The leakage early warning module performs relevant data analysis according to the field and simulation results, and performs leakage judgment, leakage early warning, relevant leakage amount estimation and the like by combining other leakage analysis methods. The database is mainly used for storing and managing relevant data such as operation data, pipeline physical property data, simulation result data and the like.
The sensor such as pressure, temperature and flow meeting the requirements is deployed at the inlet and outlet ends of a pipeline to be tested, sensor data acquisition is realized through an RS-485 conversion interface, data exchange is realized by combining Modbus-RTU protocol, real-time data storage is realized through a database system through data processing of acquired signals, a monitoring algorithm respectively carries out real-time calculation through a pipeline normal simulation model and a leakage simulation model through acquisition simulation calculation of back-end data, and the monitoring algorithm is compared with a threshold value after test calibration and algorithm test, so that the state analysis result of equipment and related data is realized through analysis results.
The thick oil thermal recovery medium conveying pipeline leakage monitoring method based on virtual sensing is characterized in that data acquisition and transmission, data processing and later solving are carried out through the input of an algorithm model on operation characteristic parameters such as pressure, temperature and flow of an inlet and an outlet of a pipeline, and the leakage related parameters are determined by comparing simulation results, verification data and field data.
As shown in FIG. 1, the thick oil thermal recovery medium conveying pipeline leakage monitoring system based on virtual sensing comprises a sensor system, a data acquisition system, a database management system, a man-machine interaction front end and a leakage early warning system. The monitoring method and the system based on the virtual sensing are realized through data acquisition and transmission, construction of a pipeline virtual model and calculation analysis.
The data acquisition and transmission work is completed by a sensor system and a data acquisition and transmission system, wherein the sensor system is arranged on a pipeline system and is arranged at positions of an inlet and an outlet of the pipeline, the change of the pipe diameter of the pipeline and the like according to a related model of a hydrodynamic theory. The sensor system includes a pressure sensor, a temperature sensor, and a flow sensor.
According to the high-temperature and high-pressure requirements of the steam medium, a high-temperature pressure sensor with a wide pressure range, a wide temperature range, high stability and strong wear resistance, impact resistance and corrosion resistance is selected. The sensor is provided with a communication protocol interface, can perform long-distance transmission, and has strong anti-interference capability and high signal transmission rate in the operation process.
The temperature sensor is an explosion-proof digital heat temperature sensor, the working range is-200-500 ℃, the temperature measurement requirement of a thermal recovery medium is met, and the data communication can be ensured by the communication module.
The flow sensor is used as a preliminary judgment basis for the leakage monitoring of a follow-up algorithm model, and adopts a digital mass flow controller with high temperature resistance, high precision, high sampling frequency, a preliminary flow reading function, short preheating time, small zero drift, high reliability, a communication interface, a data storage function and the like. The three sensors adopt a unified communication protocol.
The installation position of the sensor is designed based on specific working condition requirements, and the pressure design and working requirements of a general pipeline system at the pipeline inlet are met, so that the pressure sensor is slightly forward to be installed, and the working condition verification and the working condition change confirmation are convenient to carry out. The other sensors are respectively positioned at the rear sides of the pressure sensors as the sensors for real-time data acquisition and transmission.
Under the condition that the maximum sampling frequency requirement of sensor data is met, the database storage of data from the on-site sensor equipment to the upper computer platform end is completed by combining communication protocols such as MQTT, TCP/IP and the like, and the collection of operation data from the medium conveying pipeline equipment is realized.
The data acquisition and transmission system consists of a control chip, a basic circuit, a communication interface module circuit for receiving sensor signals and a wireless communication module circuit for transmitting data. The control chip is rich in interfaces and can meet the industrial requirements under low power consumption. The sensor performs data transmission with the node controller through serial communication. The node controller is composed of a control chip and a peripheral circuit and is responsible for signal acquisition and transmission and is used for realizing data acquisition and communication transmission of pressure and the like of each node.
The system comprises a wireless communication module, a node controller, a data transmission module and a data transmission module, wherein a bus network is realized through an RS-485 conversion interface between each sensor, pressure, temperature and flow data are acquired through the sensor system, the node controller realizes data exchange of the acquired signals through a Modbus-RTU protocol, the acquired signals are transmitted to the wireless communication module through RS-485 communication, the wireless communication module packages the acquired data in a JSON format, and the acquired data are transmitted to a cloud server through an MQTT transmission protocol. The storage management of the data is accomplished by a database system.
The running condition of the system is displayed by the man-machine interaction front end. The on-site leakage monitoring condition is completed by a man-machine interaction front end deployed at a platform end, a leakage early warning system rear end and a database for data management. The man-machine interaction front end mainly adopts a Vue front end frame construction webpage technology to display leakage monitoring conditions, so that related operators can perform normal operation of pipelines, leakage accident related information acquisition and leakage alarm processing, and on-site personnel can be guided to take measures. The rear end part data processing part is mainly used for performing characteristic processing, noise reduction analysis, signal filtering and the like on the collected data of the sensor, so that the effectiveness processing of the collected data is realized.
As shown in fig. 2-3, the leakage early warning system performs data simulation on the pipeline steam medium flow model through the pipeline steam medium flow model, and the calculated data is used as the operation basis of the pipeline steam leakage model. The pipeline steam leakage model is operated according to the data acquired by the sensor, and whether leakage occurs or not is judged through residual errors of the data. And forming a simulated pipeline simulation data set by the operation data of the pipeline steam medium flow model and the pipeline steam leakage model, and bringing the simulated pipeline simulation data set and the on-site pipeline operation data set into a leakage early warning algorithm to finish the work of leakage identification, leakage calculation amount and leakage early warning.
The foregoing describes the embodiments of the present invention in detail, but the description is only a preferred embodiment of the present invention and should not be construed as limiting the scope of the invention. All equivalent changes and modifications within the scope of the present invention are intended to be covered by the present invention.
Claims (6)
1. The thick oil thermal recovery medium conveying pipeline leakage monitoring method based on virtual sensing is characterized by fully considering the fluid flow parameter change based on a software leakage method, and comprises the following specific steps of:
Step 1, deploying a sensor in an acquisition pipeline, transmitting data acquired by the sensor to a remote upper computer through a remote communication means, and forming an operation and verification data set of physical properties and related characteristic parameters of equipment;
step 2, combining a fluid transient model and a thermodynamic model, and establishing a pipeline virtual model according to the change of the speed, pressure, density and viscosity parameters of the fluid in the pipeline;
Step 3, solving the flow field related data in the pipeline under the boundary condition of the field by using the pipeline virtual model established in the step 2, constructing a field pipeline operation data set and a virtual pipeline simulation data set by using the acquired data and the simulation data,
The on-site pipeline operation data set consists of steam pipeline operation data, the operation data are collected and data transmission is realized through deployed sensors, and the sensors are deployed at the inlet and outlet of the pipeline to monitor inlet and outlet pressure, temperature and speed parameter data in a key way;
The virtual pipeline simulation data set comprises a steam pipeline transportation data set and a steam pipeline leakage data set, wherein the steam pipeline transportation data set is constructed according to parameter data calculated by a pipeline steam medium flow model, and the steam pipeline leakage data set is constructed according to parameter data calculated by a pipeline steam leakage model;
Comparing the data of the on-site pipeline operation data set and the virtual pipeline simulation data set, and comparing the calculated value with the verification data precision to finish leakage identification, leakage quantity estimation and leakage early warning;
performing data association on the leakage identification through field data of known equipment working conditions and model simulation calculation results of corresponding working conditions, determining a normal operation threshold value of the equipment, and performing comparison on the leakage identification through real-time simulation model calculation results and the leakage threshold value to determine the leakage identification;
The leakage quantity estimation is determined through the difference between the mass flow difference of the inlet and the outlet of the pipeline and the leakage threshold value;
The leakage early warning is carried out by judging whether the difference value between the absolute value of the inlet and outlet mass flow difference value of the real-time simulation result and the leakage threshold value is larger than zero or not, and calculating the leakage quantity estimated value and displaying the subsequent result;
The model mainly comprises a pipeline virtual model which is a pipeline steam medium flow model, wherein the continuity equation of steam flow of the pipeline steam medium flow model is that,
In the formula,
Ρ -gas density, kg/m 3;
x-distance of gas along the flow direction of the pipeline, m;
w-flow rate of gas in the pipeline, m/s;
The flow area of the section of the A-pipeline, m 2;
the momentum equation of the steam flow of the pipe steam medium flow model is,
Wherein, p-gas pressure, pa, D-pipe inner diameter, m, lambda-friction resistance coefficient;
The energy equation of the steam flow of the pipeline steam medium flow model is that,
Wherein, the enthalpy value of h-gas, J/kg; The heat exchange rate per unit length of tube of the gas per unit mass flow is W/m 2.
2. The method for monitoring leakage of thick oil thermal recovery medium conveying pipelines based on virtual sensing according to claim 1 is characterized by comprising the steps of dispersing partial differential terms in a pipeline steam medium flow model based on a finite volume and finite difference method, solving a model equation in a set implicit iteration mode based on coefficient nonlinear characteristics of a momentum equation by combining a numerical discrete formula in a high-precision format with a corresponding limiter, obtaining simulation data in time dimension in a pipeline according to internal iteration of the node coefficient equation and external iteration of the equation set and according to residual requirements before and after iteration, mapping the data with real operation data, and obtaining relation between a virtual pipeline and the real pipeline under normal operation conditions, thereby providing support for leakage discrimination early warning.
3. The method for monitoring leakage of thick oil thermal recovery medium conveying pipeline based on virtual sensing as claimed in claim 1, wherein the method comprises the steps of calculating and judging a steam pipeline leakage data set in the step 3 by adopting a pipeline steam leakage model, wherein the pipeline steam leakage model equation is that,
Wherein:
The internal energy of the u-gas, J/kg;
h-enthalpy of gas, J/kg;
ρ -gas density, kg/m 3;
p-gas pressure, pa;
w-flow rate of gas in the pipeline, m/s;
t-is time, s;
x-distance of gas along the flow direction of the pipeline, m;
The flow area of the section of the A-pipeline, m 2;
g - g gravity, m/s 2;
Lambda-coefficient of friction;
d, the inner diameter of the pipeline, m;
-heat exchange rate per unit mass flow of gas per unit tube length, in W/m 2;
Mass leak rate at the M Leakage of -leak location, unit kg/(m.s);
Momentum leak rate at Mv Leakage of -leak location, unit N/m 3;
e Leakage of -the energy leakage rate at the leakage site, in W/m.
4. The method for monitoring leakage of thick oil thermal recovery medium conveying pipeline based on virtual sensing according to claim 3, wherein the calculation flow of the pipeline steam leakage model specifically comprises the following steps:
s1, inputting initial recognition conditions;
s2, setting a fault condition;
S3, reading in fault parameters;
S4, taking pressure, temperature and flow data acquired by the inlet and the outlet into a pipeline steam leakage model for calculation;
S5, carrying out residual judgment on the calculation result, ending calculation when the calculation result meets the condition, and returning to the step S3 when the calculation result does not meet the condition, and carrying out recalculation.
5. The method for monitoring leakage of thick oil thermal recovery medium conveying pipelines based on virtual sensing is characterized in that in the step 3, a field pipeline operation data set and a virtual pipeline simulation data set are compared by adopting a leakage early warning algorithm, the leakage early warning algorithm is used for carrying out preliminary early warning determination by comparing field inlet and outlet data according to inlet and outlet flow calculation of transient results under different working conditions, preliminary judgment is carried out on inlet and outlet simulation data by combining a pressure point analysis method and a mass balance method, after leakage is judged, accurate treatment is carried out on a leakage early warning threshold by combining analysis comparison of field and simulation data, and model establishment of various methods in terms of leakage identification and leakage quantity estimation is realized by a data statistics method.
6. A system for monitoring leakage of a thick oil thermal recovery medium conveying pipeline based on virtual sensing, which is used for executing the thick oil thermal recovery medium conveying pipeline leakage monitoring method based on virtual sensing as set forth in any one of claims 1 to 5, and is characterized by comprising:
The sensor system is arranged on the pipeline system, is arranged at the position of an inlet and an outlet of the pipeline and the position of the pipeline with the pipe diameter change according to the fluid mechanics theory related model, and is used for acquiring corresponding data information and comprises a pressure sensor, a temperature sensor and a flow sensor;
The data acquisition equipment comprises a data processor and an infinite communication module, the sensor performs data transmission with the node controller through serial communication, the node controller consists of a control chip of the data processor and a peripheral circuit and is responsible for signal acquisition and transmission, data acquisition and communication transmission of each node are realized, the data of the sensor is transmitted to the wireless communication module through the node controller, and the wireless communication module packages the data and transmits the data to the cloud server;
The leakage early warning system comprises a pipeline steam medium flow model, a pipeline steam leakage model and a leakage monitoring early warning algorithm, wherein the pipeline steam medium flow model is adopted to perform data simulation, relevant data analysis is performed according to the on-site and simulation results, and leakage judgment, leakage early warning and relevant leakage quantity estimation are performed through the pipeline steam leakage model and the leakage monitoring early warning algorithm;
the man-machine interaction system is used for carrying out normal operation of pipelines, acquisition of related information of leakage accidents and leakage alarm processing by related operators, guiding on-site personnel to take measures and carrying out characteristic processing, noise reduction analysis and signal filtering content on the data acquired by the sensors so as to realize validity processing of the acquired data;
and the database is used for storing and managing operation data, pipeline physical property data and simulation result data related data.
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