An intelligent emergency cut-off protection control system for oil and gas wellheads

Abstract

The present invention discloses an intelligent emergency cut-off protection device and control system for oil and gas wellheads, which relates to the technical field of oil and gas exploitation. It includes a data acquisition module that real-time collects wellhead working condition data, including gas flow data and pressure data; a leakage judgment module that, based on the collected wellhead working condition data, calculates a leakage judgment value using a comprehensive judgment function based on a machine learning algorithm and compares it with a leakage threshold to judge whether leakage occurs; an adaptive cut-off control module that, when leakage occurs, calculates the cut-off force according to the wellhead working condition data and the leakage location and controls the cut-off device to perform a cut-off action according to the cut-off force; a multi-wellhead coordination module that is used for the surrounding wellhead protection devices to adjust their own production and pressure according to a preset strategy and a collaborative working calculation formula. The present invention avoids the problems of slow response, inaccurate judgment, and insufficient coordination in the prior art, and improves the safety, stability, and automation level of the wellhead.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas extraction, and more specifically, to an intelligent emergency cut-off protection control system for oil and gas wellheads. Background Art

[0002] The wellhead refers to the top part of an oil or gas well, that is, the opening of the well, which is the place where it is connected to surface equipment during the entire oil and gas extraction process. The wellhead includes many key facilities, such as valves, pressure monitoring equipment, etc., for controlling the outflow of oil and gas and monitoring the wellhead. The "intelligent emergency cut-off protection device and control system for oil and gas wellheads" incorporates intelligent technologies on the basis of traditional oil and gas wellhead emergency cut-off protection devices to improve its response speed, accuracy, and automation level.

[0003] Deficiencies of the prior art:

[0004] Existing wellhead leakage detection systems usually rely on simple threshold judgments and are easily interfered by environmental changes and noise, resulting in low detection accuracy and long response times, and being unable to reflect changes in wellhead conditions in real time. Most current technologies only perform protection control for a single wellhead, ignoring the synergistic effect between multiple wellheads. This single-wellhead protection may not be able to effectively cope with complex production environments and emergencies.

[0005] When a wellhead leakage occurs, the existing control system may not be able to accurately determine the specific location and severity of the leakage, resulting in inaccurate cut-off control force, and there may be a risk of over-cutting or untimely cutting. Traditional wellhead control systems rely on manual judgment and intervention. Once an abnormality occurs, the response speed and judgment accuracy of humans may lead to untimely or inaccurate control, and it is impossible to achieve rapid automated response. Therefore, the present invention proposes an intelligent emergency cut-off protection control system for oil and gas wellheads to achieve emergency cut-off when a leakage occurs at the oil and gas wellhead.

[0006] In view of the above problems, the present invention proposes a solution. Summary of the Invention

[0007] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent emergency cut-off protection control system for oil and gas wellheads, which performs emergency cut-off when a leakage occurs to solve the problems raised in the above background art.

[0008] To achieve the above object, the present invention provides the following technical solutions:

[0009] An intelligent emergency cut-off protection control system for oil and gas wellheads includes a data acquisition module, a leakage judgment module, an adaptive cut-off control module, and a multi-wellhead collaboration module, and there are connections between the modules:

[0010] A data acquisition module, which is used to collect wellhead working condition data in real time, including gas flow rate data and gas pressure data;

[0011] A leakage judgment module, which is used to calculate a leakage judgment value based on the collected wellhead working condition data by using a comprehensive judgment function based on a machine learning algorithm, and compare it with a leakage threshold to judge whether leakage occurs;

[0012] An adaptive cut-off control module, which is used to calculate the cut-off force according to the wellhead working condition data and the leakage position when leakage occurs, and control the cut-off device to perform a cut-off action according to the cut-off force;

[0013] A multi-wellhead coordination module, which is used when leakage occurs at a wellhead. The control system sends a leakage signal to the surrounding wellhead protection devices. The surrounding wellhead protection devices adjust their own production and pressure according to preset strategies and collaborative working calculation formulas to achieve collaborative protection.

[0014] In a preferred embodiment, the gas flow rate data includes gas concentration, gas emission rate, and flow rate change rate.

[0015] In a preferred embodiment, the process of obtaining the gas concentration is as follows:

[0016] Install a gas concentration sensor at the wellhead. The gas detected by the gas concentration sensor is adsorbed on the surface of the sensitive element, reacts with the oxygen ions adsorbed on the surface of the sensitive element, causes the oxygen ions to obtain electrons, resulting in a change in the electrical properties of the sensitive element, and obtains a change in the resistance value of the sensitive element;

[0017] Calculate the output voltage of the sensor circuit according to the resistance value of the sensitive element;

[0018] Measure the battery voltage under the condition of known gas concentration to obtain the standard battery voltage;

[0019] Measure the temperature of the environment where the sensor is located and convert the Celsius temperature to absolute temperature;

[0020] Determine the number of electron transfers by analyzing the electrochemical reaction equation occurring in the sensor;

[0021] During dynamic measurement, obtain the dynamic response time of the sensor and introduce a time-related function to describe the dynamic response of the sensor to reach a stable output;

[0022] Calculate the gas concentration by combining the relationship between the output voltage and the gas concentration, the standard battery voltage, the absolute temperature, and the dynamic response of the number of electron transfers;

[0023] If there is interfering gas, determine the influence coefficient of the interfering gas on the sensor output and the concentration of the interfering gas through experiments to correct the formula. The specific formula is as follows:

[0024] ;

[0025] In the formula, C is the gas concentration, n is the number of electron transfers, E is the output voltage, is the standard battery voltage, is the influence coefficient of the interfering gas on the sensor output, is the concentration of the interfering gas, F is the Faraday constant, R is the gas constant, T is the absolute temperature, r is the time constant of the sensor, and t is the dynamic response time.

[0026] In a preferred embodiment, the specific process for obtaining the gas pressure data is as follows:

[0027] Obtain the output potential of the pressure sensor and calculate the gas pressure data based on the functional relationship between the gas pressure and the output potential;

[0028] Obtain the standard gas temperature and the gas temperature during actual measurement, and correct the gas pressure data to obtain the gas pressure data. The specific calculation formula is as follows:

[0029] ;

[0030] In the formula, P is the gas pressure data, is the standard gas temperature, is the gas temperature during actual measurement, v is the output potential of the pressure sensor, where k and b are the calibration coefficients of the sensor.

[0031] In a preferred embodiment, the gas outburst rate process is as follows:

[0032] Set a measurement area at the wellhead, and record the area of the measurement area as A;

[0033] Obtain the pressures before and after the orifice plate and the gas pressure, and calculate the pressure difference before and after the orifice plate based on the pressures before and after the orifice plate;

[0034] Use an orifice gas flowmeter to measure the gas flow rate through the measurement area, and calculate the gas outburst rate in combination with the measurement area. The specific calculation formula is:

[0035] ;

[0036] In the formula, v is the gas outburst rate; A is the measurement area; is the flow coefficient of the orifice flowmeter, which is determined according to the structure and installation method of the orifice plate and can be obtained by referring to relevant manuals; is the opening area of the orifice plate, which is determined according to the design dimensions of the orifice plate; is the pressure difference before and after the orifice plate; R is the gas constant, T is the absolute temperature, is the gas pressure data, is the gas flow rate.

[0037] In a preferred embodiment, the process of obtaining the flow rate change rate is as follows:

[0038] Using an orifice gas flowmeter, continuously collect gas flow rate data at regular time intervals;

[0039] Calculate the flow rate change rate according to the gas flow rate data and the collection time interval. The specific calculation formula is as follows:

[0040] ;

[0041] In the formula, b is the flow rate change rate, is the collection time interval, N is the number of collections, is the gas flow rate data collected for the jth time, is the gas flow rate data collected for the jth time;

[0042] where is the flow coefficient of the orifice flowmeter, which is determined according to the structure and installation method of the orifice plate and can be obtained by referring to relevant manuals; is the opening area of the orifice plate, which is determined according to the design dimensions of the orifice plate; is the pressure difference before and after the orifice plate; R is the gas constant, T is the absolute temperature, is the gas pressure data.

[0043] In a preferred embodiment, the leakage judgment value is calculated based on the wellhead working condition data collected by using a comprehensive judgment function based on a machine learning algorithm. The specific calculation formula is as follows:

[0044] ;

[0045] In the formula, F is the leakage judgment value, C is the gas concentration, is the gas concentration weight coefficient, P is the gas pressure data, is the gas pressure data weight coefficient, v is the gas outburst rate, is the gas outburst rate weight coefficient, b is the flow rate change rate, is the flow rate change rate weight coefficient.

[0046] In a preferred embodiment, the process of calculating the cut-off force according to the wellhead working condition data and the leakage location is as follows:

[0047] Monitor gas concentration and gas pressure data, calculate the gas concentration change rate, and the pressure change rate;

[0048] Use a positioning algorithm based on a sensor network to determine the location of the leakage point in the wellhead facility, obtain the distance between the leakage point and the wellhead, and divide the wellhead facility into multiple regions, assigning a location code to each region ;

[0049] And evaluate the leakage severity based on the gas concentration change rate and the pressure change rate using a leakage severity assessment model to obtain the evaluation level S;

[0050] Calculate the cut-off force according to the wellhead working condition data and the leakage location. The specific calculation formula is as follows:

[0051] ;

[0052] In the formula, is the cut-off force, S is the evaluation level, is the evaluation level weight coefficient, is the regional location code, is the regional location code weight coefficient, is the gas concentration change rate, is the gas concentration change weight coefficient, is the pressure change rate, is the pressure change weight coefficient, and L is the distance between the leakage point and the wellhead.

[0053] In a preferred embodiment, the peripheral wellhead protection device adjusts its production and pressure according to a preset strategy and a collaborative work calculation formula as follows:

[0054] The leakage signal at the wellhead is monitored in real time by a sensor. Once a leakage occurs, the abnormal signal detected by the sensor will be transmitted to the control system;

[0055] The control system determines that the signal is a leakage signal through the intelligent control module and immediately sends the leakage information to the protection devices of the peripheral wellheads;

[0056] After receiving the leakage signal, the protection devices of the peripheral wellheads start to work collaboratively according to the preset strategy, and adjust the production and pressure according to the current wellhead leakage situation through the collaborative work calculation formula to ensure the stability of the overall well group.

[0057] In a preferred embodiment, the calculation process of adjusting the production and pressure is as follows:

[0058] Let the number of peripheral wellheads be m, and the distance between the jth peripheral wellhead and the accident wellhead be , the peripheral wellhead protection device adjusts its own production and pressure according to the preset strategy and the collaborative working calculation formula. The specific adjustment formula is as follows:

[0059] ;

[0060] In the formula, is the actual production volume of oil and gas at the j-th peripheral wellhead, is the initial production volume of oil and gas at the j-th peripheral wellhead, is the production volume correlation coefficient, is the distance between the j-th peripheral wellhead and the accident wellhead, and S is the evaluation grade of the leakage severity, is the actual pressure of the j-th peripheral wellhead, is the initial pressure of the j-th peripheral wellhead, is the pressure correlation coefficient, and m is the number of peripheral wellheads.

[0061] The technical effects and advantages of an intelligent oil and gas wellhead emergency cut-off protection control system of the present invention:

[0062] 1. Through the data acquisition module of the present invention, the gas flow rate and pressure data of the wellhead can be collected in real time, which enables the system to more accurately judge the working conditions of the wellhead. Combining with the machine learning algorithm in the leakage judgment module, it can intelligently judge whether there is a leakage at the wellhead based on the collected data. Through the optimization of the comprehensive judgment function, the interference of environmental noise is reduced, and the accuracy and timeliness of judgment are improved. Based on the adaptive ability of the machine learning algorithm, the leakage judgment module can continuously learn and optimize, thereby improving the accuracy of leakage judgment and the ability to adapt to different wellhead working conditions. By comparing the leakage judgment value with the set threshold in real time, the system can automatically judge whether there is a leakage, avoiding the delay and error of traditional manual judgment and improving the response speed. The adaptive cut-off control module calculates the cut-off force according to the wellhead working conditions and the leakage position. This technology can be adaptively adjusted according to the actual leakage situation, avoiding the situation of over-cutting or under-cutting, ensuring the safety of the wellhead while minimizing production losses to the greatest extent. The intelligent oil and gas wellhead emergency cut-off protection device and control system have the advantages of automation, intelligence, high efficiency, safety, etc. It can not only improve the safety of the wellhead, reduce the risk of manual misoperation, but also improve the overall operation efficiency and equipment stability through functions such as remote monitoring and fault diagnosis, which is of great significance for improving the safety management level of the oil and gas industry.

[0063] 2. The present invention solves the problem of collaborative protection among multiple wellheads through the multi-wellhead collaboration module. When a leakage occurs at one wellhead, the system can perform collaborative adjustment with the protection devices of the surrounding wellheads through signal transmission. Through preset strategies and collaborative working calculation formulas, the production and pressure of the surrounding wellheads can be adjusted in real time, avoiding the impact on the overall system when a single wellhead leaks, and improving the overall stability and safety of the system. One of the greatest advantages of this system is automation and intelligence. By using advanced machine learning algorithms and automatic control technologies, the need for manual intervention is reduced, greatly improving the response speed and processing accuracy. This not only enhances the safety of the wellhead but also reduces the risks brought by human operations. Different from the traditional judgment method based on a single threshold, the system combines machine learning algorithms through a comprehensive judgment function, making leakage detection more accurate, cut-off control more efficient, and adaptable to different working conditions. It can flexibly adjust the cut-off strategy, enabling precise control at the initial stage of leakage, reducing the risks of misjudgment and improper handling. Through functions such as data collection, intelligent leakage judgment, automatic cut-off control, and multi-wellhead collaborative work, the efficiency of wellhead leakage detection and emergency handling is significantly improved, avoiding problems such as slow response, inaccurate judgment, and insufficient collaboration in the prior art, and enhancing the safety, stability, and automation level of the wellhead. These advantages make the system more reliable and intelligent in complex production environments, and it is an effective supplement and improvement to the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a schematic structural diagram of an intelligent oil and gas wellhead emergency cut-off protection control system of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0066] Embodiment 1, Figure 1 An intelligent oil and gas wellhead emergency cut-off protection control system of the present invention is provided.

[0067] A data collection module, used for real-time collection of wellhead working condition data, including gas flow data and gas pressure data;

[0068] The gas flow data includes gas concentration, gas outburst rate, and flow rate change rate;

[0069] Methane is the main component of natural gas, and leakage usually leads to an increase in concentration. In order to monitor and judge gas leakage, the wellhead cut-off protection device usually monitors the methane component and its concentration;

[0070] The process of obtaining gas concentration is as follows:

[0071] Install a gas concentration sensor at a suitable position on the wellhead;

[0072] When the gas concentration sensor is exposed to an environment containing the target gas, the gas detected by the gas concentration sensor is adsorbed on the surface of the sensitive element and reacts with the oxygen ions adsorbed on the surface of the sensitive element, causing the oxygen ions to gain electrons and resulting in a change in the electrical properties of the sensitive element, specifically manifested as a change in the resistance value;

[0073] Calculate the output voltage of the sensor circuit based on the resistance value of the sensitive element;

[0074] By measuring the battery voltage under the condition of known gas concentration, obtain the standard battery voltage;

[0075] Measure the temperature of the environment where the sensor is located and convert the Celsius temperature to absolute temperature;

[0076] Determine the number of electron transfers by analyzing the electrochemical reaction equation occurring in the sensor;

[0077] During dynamic measurement, obtain the dynamic response time of the sensor and introduce a time-related function to describe the dynamic response of the sensor to reach a stable output;

[0078] Calculate the gas concentration through the relationship between the output voltage and the gas concentration, combined with the standard battery voltage, absolute temperature, and dynamic response of the number of electron transfers;

[0079] If there are interfering gases, determine the influence coefficient of the interfering gases on the sensor output and the concentration of the interfering gases through experiments to correct the formula. The specific formula is as follows:

[0080] ;

[0081] In the formula, C is the gas concentration, n is the number of electron transfers, E is the output voltage, is the standard battery voltage, is the influence coefficient of the interfering gas on the sensor output, is the concentration of the interfering gas, F is the Faraday constant, R is the gas constant, T is the absolute temperature, r is the time constant of the sensor, and t is the dynamic response time.

[0082] It should be noted that the sensor should be installed at a position where it can fully contact the escaping gas and is not overly interfered by the air flow. For example, it can be installed at a certain height above the wellhead on a vertical pipeline.

[0083] The specific process of obtaining gas pressure data is as follows:

[0084] Obtain the output potential of the pressure sensor and calculate the gas pressure data based on the functional relationship between the gas pressure and the output potential;

[0085] Obtain the standard gas temperature and the gas temperature during actual measurement, and correct the gas pressure data to obtain the gas pressure data. The specific calculation formula is as follows:

[0086] ;

[0087] In the formula, P is the gas pressure data, is the standard gas temperature, is the gas temperature during actual measurement, v is the output potential of the pressure sensor, where k and b are the calibration coefficients of the sensor.

[0088] The process of gas emission rate is as follows: Set a measurement area at the wellhead. This area is a cross-section perpendicular to the gas emission direction, and the area of the measurement area is denoted as A;

[0089] Obtain the pressures before and after the orifice plate and the gas pressure, and calculate the pressure difference before and after the orifice plate according to the pressures before and after the orifice plate;

[0090] Use an orifice plate gas flowmeter to measure the gas flow rate passing through this measurement area, and calculate the gas emission rate in combination with the area of the measurement area. The specific calculation formula is:

[0091] ;

[0092] In the formula, v is the gas emission rate; A is the area of the measurement area; is the flow coefficient of the orifice plate flowmeter, which is determined according to the structure and installation method of the orifice plate and can be obtained by referring to relevant manuals; is the orifice area of the orifice plate, which is determined according to the design dimensions of the orifice plate; is the pressure difference before and after the orifice plate; R is the gas constant, T is the absolute temperature, is the gas pressure data, is the gas flow rate.

[0093] The process of obtaining the flow rate change rate is as follows:

[0094] Use an orifice plate gas flowmeter to continuously collect gas flow rate data at regular time intervals. The time interval for collection is determined according to the sensitivity of the flow rate change to be monitored actually;

[0095] Calculate the flow rate change rate according to the gas flow rate data and the collection time interval. The specific calculation formula is as follows:

[0096] ;

[0097] In the formula, b is the flow rate change rate, is the acquisition time interval, N is the number of acquisitions, is the gas flow rate data collected at the jth acquisition, is the gas flow rate data collected at the jth acquisition;

[0098] where is the flow coefficient of the orifice flowmeter, which is determined according to the structure and installation method of the orifice and can be obtained by referring to relevant manuals; is the orifice opening area, which is determined according to the orifice design size; is the pressure difference before and after the orifice; R is the gas constant, T is the absolute temperature, is the gas pressure data.

[0099] The leakage judgment module is used to calculate the leakage judgment value based on the machine learning algorithm using the comprehensive judgment function according to the collected wellhead working condition data, and compare it with the leakage threshold to judge whether leakage occurs;

[0100] The specific calculation formula for calculating the leakage judgment value based on the machine learning algorithm using the comprehensive judgment function according to the collected wellhead working condition data is as follows:

[0101] ;

[0102] In the formula, F is the leakage judgment value, C is the gas concentration, is the gas concentration weight coefficient, P is the gas pressure data, is the gas pressure data weight coefficient, v is the gas emission rate, is the gas emission rate weight coefficient, b is the flow rate change rate, is the flow rate change rate weight coefficient.

[0103] The process of obtaining the weight coefficient is as follows:

[0104] Collect a large amount of wellhead working condition data, including data under normal working conditions and different types and degrees of leakage working conditions;

[0105] For each set of data, mark whether leakage occurs according to the actual situation. If leakage occurs, mark it as 1, and if no leakage occurs, mark it as 0, and use these data as the training data set;

[0106] The process of determining the weight coefficient in the comprehensive judgment function using the logistic regression algorithm is as follows:

[0107] Divide the training dataset into a training set and a validation set. Use the training set to train the logistic regression model. Continuously adjust the weight coefficients through an iterative optimization algorithm. During the training process, regularly use the validation set to evaluate the model and observe the prediction accuracy of the model on the validation set. When the prediction accuracy of the model on the validation set no longer improves or reaches the expected performance requirements, stop the training to obtain the final weight coefficients.

[0108] It should be noted that the logistic regression algorithm can handle binary classification problems. By learning the relationship between each feature in the training dataset and the annotation results, the weight coefficients are optimized so that the function can accurately classify whether there is a leak at the wellhead. The loss function between the prediction result and the actual annotation result is minimized by continuously adjusting the weight coefficients.

[0109] Compare the leak judgment value with the leak threshold to determine whether a leak has occurred. The process is as follows:

[0110] If the leak judgment value is greater than the preset leak threshold, it is judged that a leak will occur, and a cut-off process is performed according to the adaptive cut-off control module;

[0111] If the leak judgment value is less than the preset leak threshold, it is judged that no leak has occurred, and the wellhead condition data is continuously monitored.

[0112] The adaptive cut-off control module is used to calculate the cut-off force according to the wellhead condition data and the leak location when a leak occurs, and control the cut-off device to perform a cut-off action according to the cut-off force;

[0113] Monitor the gas concentration and gas pressure data, and calculate the gas concentration change rate and the pressure change rate;

[0114] Use a positioning algorithm based on a sensor network to determine the location of the leak point in the wellhead facilities, obtain the distance between the leak point and the wellhead, and divide the wellhead facilities into multiple regions, and assign a location code to each region ;

[0115] And evaluate the leak severity based on the gas concentration change rate and the pressure change rate using a leak severity evaluation model to obtain the evaluation level S;

[0116] The specific calculation formula for calculating the cut-off force according to the wellhead condition data and the leak location is as follows:

[0117] ;

[0118] In the formula, is the cut-off force, S is the evaluation level, is the evaluation level weight coefficient, is the regional location code, is the regional position coding weight coefficient, is the gas concentration change rate, is the gas concentration change weight coefficient, is the pressure change rate, is the pressure change weight coefficient, and L is the distance between the leakage point and the wellhead.

[0119] The process of controlling the cutting device to perform the cutting action according to the cutting force is as follows:

[0120] Convert the cutting force value into a binary digital signal according to the coding rule. Each bit represents different force magnitude information, and transmit the digital signal from the control system to the cutting device;

[0121] The cutting device receives the signal and performs a decoding operation to restore the binary digital signal to the cutting force according to the pre-set coding rule;

[0122] According to the magnitude of the cutting force value, the control system sends corresponding control signals to the control valve and the power source. The control valve adjusts the opening of the valve core according to this signal, thereby changing the flow rate and pressure of the hydraulic oil entering the hydraulic cylinder;

[0123] When the power source receives the power control signal and generates the corresponding driving force, it will drive the gate to move. During the movement, the gate gradually approaches and finally closely fits the valve seat, thereby blocking the gas flow and completing the cutting action.

[0124] The multi-well cooperation module is used to, when a leakage occurs at a wellhead, the control system sends a leakage signal to the surrounding wellhead protection devices. The surrounding wellhead protection devices adjust their production and pressure according to the preset strategy and the cooperation working calculation formula to achieve cooperative protection.

[0125] The leakage signal of the wellhead is monitored in real time by a sensor. Once a leakage occurs, the abnormal signal detected by the sensor will be transmitted to the control system;

[0126] The control system determines that the signal is a leakage signal through the intelligent control module and immediately sends the leakage information to the protection devices of the surrounding wellheads;

[0127] After receiving the leakage signal, the protection devices of the surrounding wellheads start to work cooperatively according to the preset strategy, and adjust the production and pressure according to the cooperation working calculation formula based on the current wellhead leakage situation to ensure the stability of the overall well group and avoid more serious wellhead leakage or other safety problems;

[0128] The calculation process of adjusting the production and pressure is as follows:

[0129] Let the number of surrounding wellheads be m, and the distance between the j-th surrounding wellhead and the accident wellhead be , the peripheral wellhead protection device adjusts its own production and pressure according to the preset strategy and the collaborative working calculation formula. The specific adjustment formula is as follows:

[0130] ;

[0131] In the formula, is the actual production volume of oil and gas at the j-th peripheral wellhead, is the initial production volume of oil and gas at the j-th peripheral wellhead, is the production-related coefficient, is the distance between the j-th peripheral wellhead and the accident wellhead, and S is the evaluation grade of the leakage severity, is the actual pressure at the j-th peripheral wellhead, is the initial pressure at the j-th peripheral wellhead, is the pressure-related coefficient.

[0132] The above formulas are all dimensionless and take their numerical values for calculation. The formula is obtained by collecting a large amount of data for software simulation to get a formula closest to the real situation. The preset parameters in the formula are set by those skilled in the art according to the actual situation.

[0133] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product.

[0134] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0135] In addition, in each embodiment of this application, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0136] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0137] Finally, the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent emergency cut-off protection control system for oil and gas wellheads, characterized in that, It includes a data acquisition module, a leakage judgment module, an adaptive cut-off control module, and a multi-wellhead coordination module. There are connections between the modules: The data acquisition module is used to collect wellhead condition data in real time, including gas flow data and gas pressure data; the gas flow data includes gas concentration, gas emission rate, and flow rate change rate; The leakage judgment module is used to calculate a leakage judgment value based on the collected wellhead condition data using a comprehensive judgment function based on a machine learning algorithm, and compare it with a leakage threshold to determine whether a leakage has occurred; the formula for calculating the leakage judgment value is: ； In the formula, F is the leakage judgment value, C is the gas concentration, is the gas concentration weight coefficient, P is the gas pressure data, is the gas pressure data weight coefficient, v is the gas emission rate, is the gas emission rate weight coefficient, b is the flow rate change rate, is the flow rate change rate weight coefficient; The adaptive cut-off control module is used to calculate the cut-off force according to the wellhead condition data and the leakage location when a leakage occurs. The process is as follows: determine the location of the leakage point in the wellhead facilities, and evaluate the severity of the leakage based on the gas concentration change rate and the pressure change rate using a leakage severity evaluation model, obtain the gas concentration change rate and the pressure change rate, and calculate the cut-off force by combining the leakage location and the leakage severity; and control the cut-off device to perform a cut-off action according to the cut-off force; The multi-wellhead coordination module is used to send a leakage signal to the surrounding wellhead protection devices when a leakage occurs at the wellhead. The surrounding wellhead protection devices adjust their production and pressure according to a preset strategy and a collaborative work calculation formula to achieve collaborative protection.

2. The intelligent onshore oil and gas wellhead emergency shutdown protection control system according to claim 1, characterized in that, The process of obtaining the gas concentration is as follows: Install a gas concentration sensor at the wellhead. The gas detected by the gas concentration sensor adsorbs on the surface of the sensitive element and reacts with the oxygen ions adsorbed on the surface of the sensitive element, causing the oxygen ions to obtain electrons, resulting in a change in the electrical properties of the sensitive element and obtaining a change in the resistance value of the sensitive element; Calculate the output voltage of the sensor circuit according to the resistance value of the sensitive element; Measure the battery voltage under the condition of known gas concentration to obtain the standard battery voltage; Measure the temperature of the environment where the sensor is located and convert the Celsius temperature to absolute temperature; Determine the number of electron transfers by analyzing the electrochemical reaction equation occurring in the sensor; During dynamic measurement, obtain the dynamic response time of the sensor and introduce a time-related function to describe the dynamic response of the sensor to reach a stable output; Calculate the gas concentration by combining the relationship between the output voltage and the gas concentration, the standard battery voltage, the absolute temperature, and the dynamic response of the number of electron transfers; If there are interfering gases, determine the influence coefficient of the interfering gases on the sensor output and the concentration of the interfering gases through experiments to correct the formula. The specific formula is as follows: ； Wherein, C is the gas concentration, n is the number of electron transfers, E is the output voltage, is the standard battery voltage, is the influence coefficient of the interfering gas on the sensor output, is the concentration of the interfering gas, F is the Faraday constant, R is the gas constant, T is the absolute temperature, r is the time constant of the sensor, and t is the dynamic response time.

3. An intelligent emergency cut-off protection control system for oil and gas wellheads according to claim 2, characterized in that, The specific process of obtaining the gas pressure data is as follows: Obtain the output potential of the pressure sensor and calculate the gas pressure data based on the functional relationship between the gas pressure and the output potential; Obtain the standard gas temperature and the gas temperature during actual measurement, and correct the gas pressure data to obtain the gas pressure data. The specific calculation formula is as follows: ； where P is the gas pressure data, is the standard temperature of the gas, is the gas temperature during actual measurement, v is the output potential of the pressure sensor, where k and b are the calibration coefficients of the sensor.

4. An intelligent emergency cut-off protection control system for oil and gas wellheads according to claim 3, characterized in that, The process of the gas emission rate is as follows: Set a measurement area at the wellhead, and record the area of the measurement area as A; Obtain the pressures before and after the orifice plate and the gas pressure, and calculate the pressure difference before and after the orifice plate according to the pressures before and after the orifice plate; The orifice gas flowmeter is used to measure the gas flow rate through the measurement area, and the gas emission rate is calculated by combining the measurement area. The specific calculation formula is as follows: ； Wherein, v is the gas emission rate; A is the area of the measurement region; is the flow coefficient of the orifice flowmeter, which is determined according to the structure and installation method of the orifice plate and can be obtained by referring to relevant manuals; is the orifice area of the orifice plate, which is determined according to the design dimensions of the orifice plate; is the pressure difference before and after the orifice plate; R is the gas constant and T is the absolute temperature, is the gas pressure data, is the gas flow rate.

5. The intelligent emergency cut-off protection control system for oil and gas wellheads according to claim 4, characterized in that, The process of obtaining the flow rate change rate is as follows: Using the orifice gas flowmeter, continuously collect gas flow rate data at a certain time interval; Calculate the flow rate change rate according to the gas flow rate data and the collection time interval. The specific calculation formula is as follows: ； where b is the flow rate change rate, is the acquisition time interval, N is the number of acquisitions, is the gas flow rate data collected at the j-th time, is the gas flow rate data collected at the j-th time; Among them is the flow coefficient of the orifice plate flowmeter, which is determined according to the structure and installation method of the orifice plate and can be obtained by referring to relevant manuals; is the orifice area of the orifice plate, which is determined according to the design dimensions of the orifice plate; is the pressure difference before and after the orifice plate; R is the gas constant and T is the absolute temperature, which is the gas pressure data.

6. The intelligent emergency cut-off protection control system for oil and gas wellheads according to claim 5, characterized in that, The specific calculation formula for calculating the cut-off force according to the wellhead working condition data and the leakage position is as follows: ； In the formula, is the cutting force, S is the evaluation level, is the evaluation level weight coefficient, is the regional location code, is the regional location code weight coefficient, is the gas concentration change rate, is the gas concentration change weight coefficient, is the pressure change rate, is the pressure change weight coefficient, and L is the distance between the leakage point and the wellhead.

7. An intelligent oil and gas wellhead emergency cut-off protection control system according to claim 6, characterized in that, The surrounding wellhead protection device adjusts its own production and pressure according to the preset strategy and the collaborative work calculation formula. The process is as follows: The leakage signal at the wellhead is monitored in real time by a sensor. Once leakage occurs, the abnormal signal detected by the sensor will be transmitted to the control system; The control system determines that the signal is a leakage signal through the intelligent control module and immediately sends the leakage information to the protection devices of the surrounding wellheads; After receiving the leakage signal, the protection devices of the surrounding wellheads start to work collaboratively according to the preset strategy, and adjust the production and pressure according to the current wellhead leakage situation through the collaborative work calculation formula to ensure the stability of the overall well group.

8. An intelligent emergency cut-off protection control system for oil and gas wellheads according to claim 7, characterized in that, The calculation process for adjusting the production and pressure is as follows: Let the number of surrounding wellheads be m, and the distance between the j-th surrounding wellhead and the accident wellhead be . The surrounding wellhead protection device adjusts its own production and pressure according to the preset strategy and the collaborative working calculation formula. The specific adjustment formula is as follows: ； In the formula, is the actual production volume of oil and gas at the j-th peripheral wellhead, is the initial production volume of oil and gas at the j-th peripheral wellhead, is the production volume correlation coefficient, is the distance between the j-th peripheral wellhead and the accident wellhead, and S is the evaluation grade of leakage severity, is the actual pressure at the j-th peripheral wellhead, is the initial pressure at the j-th peripheral wellhead, is the pressure correlation coefficient, and m is the number of peripheral wellheads.

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