Electric submersible pump intermittent oil extraction method based on fuzzy control algorithm and control system

Abstract

The invention discloses an electric submersible pump intermittent oil extraction method based on a fuzzy control algorithm and a control system. The intermittent oil production method of the electric submersible pump comprises the steps that the working condition monitoring device monitors and collects working condition data of the electric submersible pump in real time; the PLC is used for processing and analyzing the working condition data; the PLC controller executes a pre-designed fuzzy control algorithm; generating a corresponding control command according to the current working condition data of the electric submersible pump; sending the generated control command to the frequency converter; the frequency converter adjusts the output frequency according to the received control command; working condition data monitored in real time are fed back to the PLC; the PLC is used for processing the working condition data; and adjusting and optimizing the control strategy according to the feedback data. The electric submersible pump control system has the advantages that high-precision control over operation of the electric submersible pump is achieved through intelligent regulation and control according to working conditions, the stability of the system is kept, the working performance of the electric submersible pump is remarkably improved, and the oil extraction production efficiency is improved.

Description

Technical Field

[0001] The present invention relates to an oil production method for submersible electric pumps, and in particular to an intermittent oil production method and control system for submersible electric pumps based on a fuzzy control algorithm, belonging to the technical field of oil and gas development. Background Art

[0002] A submersible electric pump is a commonly used oil production device in the field of oil and gas development. It drives a centrifugal pump, a screw pump, or a piston pump through a submersible motor to lift the underground crude oil to the ground. The intelligent control system for intermittent oil production uses the new theory of the production supply and discharge relationship of oil wells, and through computer data analysis and processing, organically combines the operation mode of the oil production equipment with the liquid supply condition and displacement of the oil layer, thereby effectively improving the working efficiency of the oil production equipment. At present, the submersible electric pump adopts a constant speed drive mode and cannot adjust the pump speed and pressure difference according to the actual working conditions, resulting in high energy consumption of the submersible electric pump, low oil production efficiency, and high oil production cost. Summary of the Invention

[0003] In order to overcome the above deficiencies existing in the existing oil production process of submersible electric pumps, the present invention provides an intermittent oil production method and control system for submersible electric pumps based on a fuzzy control algorithm.

[0004] The technical solution adopted by the present invention to solve its technical problems is: An intermittent oil production method for submersible electric pumps, and its steps are:

[0005] Start: Enter the initial state of the system;

[0006] S1. Data acquisition: The working condition monitoring device monitors and acquires the working condition data of the submersible electric pump in real time. The working condition data includes the pump speed v and the pressure difference p.

[0007] S2. Data processing: The acquired working condition data is transmitted to the PLC controller, and the PLC controller processes and analyzes the working condition data.

[0008] S3. Execution of control algorithm: Based on the processed and analyzed data, the PLC controller executes the pre-designed fuzzy control algorithm.

[0009] S4. Generation of control command: The fuzzy control algorithm generates corresponding control commands according to the current working condition data of the submersible electric pump.

[0010] S5. Sending of control command: The PLC controller sends the generated control command to the frequency converter.

[0011] S6. Control of frequency converter: The frequency converter adjusts the output frequency according to the received control command to control the motor speed n of the submersible electric pump.

[0012] S7. Monitoring feedback: The working condition monitoring device feeds back the real-time monitored working condition data to the PLC controller.

[0013] S8. Feedback data processing: The PLC controller processes the received operating condition data.

[0014] S9. Control strategy optimization: The PLC controller adjusts and optimizes the control strategy based on the feedback data.

[0015] S10. Return to S2: Loop through S2 - S10 to adjust the motor speed n of the submersible electric pump.

[0016] Furthermore, in step S2, the PLC controller processes and analyzes the operating condition data, including: data verification, data formatting and preprocessing, feature extraction, and status evaluation.

[0017] The data verification includes confirming the accuracy and integrity of the data, ensuring that the data is within a reasonable operating range, and excluding abnormal or incorrect readings.

[0018] The data formatting and preprocessing is to convert the raw data obtained from the sensor into a format suitable for further analysis, and perform normalization, scaling, or transformation on the data.

[0019] The feature extraction is to extract key information from the operating condition data, including the average pump speed, maximum / minimum pressure difference, and identify and calculate parameters that have an important impact on the pump operating condition.

[0020] The status evaluation is to evaluate the operating status of the submersible electric pump according to the extracted features and preset criteria; determine whether there are any potential operating problems or abnormal conditions.

[0021] Furthermore, the symbols and parameters of the fuzzy control algorithm in step S3:

[0022] v - pump speed, the rotational speed of the impeller of the submersible electric pump,

[0023] p - pressure difference, the pressure difference between the suction port and the discharge port of the submersible electric pump,

[0024] f - frequency of the frequency converter,

[0025] n - motor speed of the submersible electric pump,

[0026] Pump speed membership function: a_low, b_low, c_low, a_medium, b_medium, c_medium, a_high, b_high, c_high.

[0027] Pressure difference membership function: a_small, b_small, c_small, a_medium, b_medium, c_medium, a_large, b_large, c_large.

[0028] Adaptive adjustment process of pump speed v based on fuzzy algorithm:

[0029] A1. Calculation of membership degree of pump speed v

[0030] Low-speed membership degree: μ_low(v) = triangle(v, a_low, b_low, c_low).

[0031] Medium-speed membership degree: μ_medium(v) = triangle(v, a_medium, b_medium, c_medium).

[0032] High-speed membership degree: μ_high(v) = triangle(v, a_high, b_high, c_high).

[0033] A2. Calculation of membership degree of pressure difference p

[0034] Small membership degree: μ_small(p) = triangle(p, a_small, b_small, c_small).

[0035] Medium membership degree: μ_medium(p) = triangle(p, a_medium, b_medium, c_medium).

[0036] Large membership degree: μ_large(p) = triangle(p, a_large, b_large, c_large).

[0037] A3. Fuzzy rules according to the operation characteristics of the submersible electric pump

[0038] If the pump speed is low and the pressure difference is small, the frequency of the frequency converter is low;

[0039] If the pump speed is low and the pressure difference is medium, the frequency of the frequency converter is medium;

[0040] If the pump speed is low and the pressure difference is large, the frequency of the frequency converter is high;

[0041] If the pump speed is medium and the pressure difference is small, the frequency of the frequency converter is medium;

[0042] If the pump speed is medium and the pressure difference is medium, the frequency of the frequency converter is medium;

[0043] If the pump speed is medium and the pressure difference is large, the frequency of the frequency converter is high;

[0044] If the pump speed is high and the pressure difference is small, the frequency of the frequency converter is high;

[0045] If the pump speed is high and the pressure difference is medium, then the frequency of the frequency converter is high frequency;

[0046] If the pump speed is high and the pressure difference is large, then the frequency of the frequency converter is high frequency.

[0047] A4. According to the membership degree values of the input variables and the designed fuzzy rules, perform fuzzy inference to determine the fuzzy set of the output variable and its membership degree values; according to the condition part of each rule and the membership degree values of the input variables, calculate the activation degree of each rule:

[0048] Activation degree of rule 1: activation_rule1 = min(μ_low(v), μ_small(p)),

[0049] Activation degree of rule 2: activation_rule2 = min(μ_low(v), μ_medium(p)),

[0050] Activation degree of rule 3: activation_rule3 = min(μ_low(v), μ_large(p)),

[0051] Activation degree of rule 4: activation_rule4 = min(μ_medium(v), μ_small(p)),

[0052] Activation degree of rule 5: activation_rule5 = min(μ_medium(v), μ_medium(p)),

[0053] Activation degree of rule 6: activation_rule6 = min(μ_medium(v), μ_large(p)),

[0054] Activation degree of rule 7: activation_rule7 = min(μ_high(v), μ_small(p)),

[0055] Activation degree of rule 8: activation_rule8 = min(μ_high(v), μ_medium(p)),

[0056] Activation degree of rule 9: activation_rule9 = min(μ_high(v), μ_large(p)).

[0057] A5. According to the rule activation degrees obtained from the fuzzy inference and the membership degree values in the fuzzy rule base, calculate the membership degree values of the output variable in each fuzzy set:

[0058] Membership degree of low frequency of the frequency converter: μ_low(f) = activation_rule1

[0059] Membership degree of medium frequency of the frequency converter: μ_medium(f) = max(activation_rule2, activation_rule4, activation_rule5)

[0060] Membership degree of high frequency of the frequency converter: μ_high(f) = max(activation_rule3, activation_rule6, activation_rule7, activation_rule8, activation_rule9).

[0061] A6. Calculate the final pump speed control quantity according to the above fuzzy control algorithm, and input the result to the PLC controller for adjusting the pump speed of the submersible electric pump,

[0062] Control quantity = (μ_low * Min_Speed + μ_medium * Mid_Speed + μ_high * Max_Speed) / (μ_low + μ_medium + μ_high).

[0063] Where:

[0064] μ_low represents the membership degree value of the pump speed of the submersible electric pump in the low-speed fuzzy set;

[0065] μ_medium represents the membership degree value of the pump speed of the submersible electric pump in the medium-speed fuzzy set;

[0066] μ_high represents the membership degree value of the pump speed of the submersible electric pump in the high-speed fuzzy set;

[0067] Min_Speed represents the minimum value of the pump speed of the submersible electric pump;

[0068] Max_Speed represents the maximum value of the pump speed of the submersible electric pump;

[0069] Mid_Speed represents the intermediate value of the pump speed of the submersible electric pump.

[0070] Furthermore, the pressure difference for the normal operation of the submersible electric pump is x kPa to y kPa,

[0071] When the high pressure difference is greater than y + Δ kPa, the submersible electric pump stops running;

[0072] When the low pressure difference is less than x - Δ′ kPa, the submersible electric pump stops running;

[0073] When the pressure difference of the submersible electric pump for normal operation resumes to x kPa to y kPa, the submersible electric pump resumes operation.

[0074] A control system applying the intermittent oil production method of the submersible electric pump includes a PLC controller. The control system further includes: a working condition monitoring device of the submersible electric pump, and a frequency converter.

[0075] The pressure sensor of the working condition monitoring device is used to monitor the working condition data of the submersible electric pump and transmit the data to the PLC controller.

[0076] The PLC controller receives the transmitted data of the working condition monitoring device and controls the submersible electric pump according to a preset fuzzy control algorithm.

[0077] The frequency converter is connected to the PLC controller and receives the control signal from the PLC controller to adjust the output frequency of the frequency converter and the motor speed of the submersible electric pump.

[0078] Further, the frequency converter is connected to the PLC controller through RS485 communication.

[0079] Further, the working condition monitoring device transmits the monitoring data to the PLC controller through the Modbus RTU protocol.

[0080] The beneficial effects of the present invention are that through intelligent regulation, the operation of the submersible electric pump is precisely controlled according to the working conditions, the stability of the system is maintained, the working performance of the submersible electric pump is significantly improved, the oil production efficiency is increased, the energy consumption is reduced, energy is saved and emissions are reduced, bringing positive economic and environmental benefits to the oil production industry. Description of the Drawings

[0081] Figure 1 is the flow chart of the intermittent oil production method of the submersible electric pump of the present invention.

[0082] Figure 2 is the schematic diagram of the intermittent oil production control system of the submersible electric pump of the present invention.

[0083] In the figure: 1. PLC controller, 2. Working condition monitoring device, 3. Frequency converter. Detailed Embodiments

[0084] The present invention will be further described below in conjunction with the drawings and embodiments. However, those skilled in the art should know that the present invention is not limited to the specific embodiments listed. As long as it conforms to the spirit of the present invention, it should be included within the protection scope of the present invention.

[0085] In the description of the present invention, it should be noted that unless otherwise clearly specified and defined, the terms "set", "installed", "connected", and "coupled" should be understood in a broad sense. For example, the connection can be a fixed connection, a detachable connection, a direct connection, an indirect connection, or an integral connection; it can be a mechanical connection, an indirect connection through an intermediate medium, or a communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0086] See the appendix Figure 1 A method for intermittent oil production of a submersible electric pump according to the present invention has the following steps:

[0087] Start: The initial state of the system;

[0088] S1. Data acquisition: The working condition monitoring device monitors and acquires the working condition data of the submersible electric pump in real time. The working condition data includes the pump speed v and the pressure difference p.

[0089] S2. Data processing: The acquired working condition data is transmitted to the PLC controller, and the PLC controller processes and analyzes the working condition data.

[0090] S3. Execution of control algorithm: Based on the processed and analyzed data, the PLC controller executes a pre-designed fuzzy control algorithm.

[0091] S4. Generation of control command: The fuzzy control algorithm generates corresponding control commands according to the current working condition data of the submersible electric pump.

[0092] S5. Sending of control command: The PLC controller sends the generated control commands to the frequency converter.

[0093] S6. Frequency converter control: The frequency converter adjusts the output frequency according to the received control commands to control the motor speed n of the submersible electric pump.

[0094] S7. Monitoring feedback: The working condition data monitored by the working condition monitoring device in real time is fed back to the PLC controller;

[0095] S8. Processing of feedback data: The PLC controller processes the received real-time working condition data.

[0096] S9. Optimization of control strategy: The PLC controller adjusts and optimizes the control strategy according to the feedback data.

[0097] S10. Return to S2: Steps S2 to S10 are executed in a loop to adjust and control the motor speed n of the submersible electric pump.

[0098] Further, in the step S2, the PLC controller processes and analyzes the working condition data, including: data verification, data formatting and preprocessing, feature extraction, and status evaluation, where:

[0099] The data verification is to confirm the accuracy and integrity of the data, ensure that the data is within a reasonable operating range, and exclude abnormal or incorrect readings.

[0100] The data formatting and preprocessing is to convert the raw data obtained from the sensor into a format that can be used for further analysis, and perform normalization, scaling, or transformation on the data.

[0101] The feature extraction is to extract key information from the working condition data, including the average pump speed, maximum / minimum pressure difference, and identify and calculate parameters that have an important impact on the pump operating condition.

[0102] The status evaluation is to evaluate the operating status of the submersible electric pump according to the extracted features and preset criteria; determine whether there are any potential operating problems or abnormal conditions.

[0103] Further, the symbols and parameters of the fuzzy control algorithm in the step S3:

[0104] v - pump speed, the impeller rotation speed of the submersible electric pump

[0105] p - pressure difference, the pressure difference between the suction port and the discharge port of the submersible electric pump

[0106] f - the frequency of the frequency converter

[0107] n - the motor speed of the submersible electric pump

[0108] In most submersible electric pump systems, especially in direct drive systems without an intermediate drive system (such as a gearbox), the pump speed v is equal to the motor speed n. This means that when the motor speed increases or decreases, the pump speed will also increase or decrease accordingly.

[0109] Pump speed membership function: a_low, b_low, c_low, a_medium, b_medium, c_medium, a_high, b_high, c_high.

[0110] Pressure difference membership function: a_small, b_small, c_small, a_medium, b_medium, c_medium, a_large, b_large, c_large.

[0111] Pump speed adaptive regulation process based on the fuzzy algorithm:

[0112] A1. Calculation of the membership degree of the pump speed v

[0113] Low speed membership degree: μ_low(v) = triangle(v, a_low, b_low, c_low);

[0114] Medium speed membership degree: μ_medium(v) = triangle(v, a_medium, b_medium, c_medium);

[0115] High speed membership degree: μ_high(v) = triangle(v, a_high, b_high, c_high).

[0116] A2. Calculation of the membership degree of the pressure difference p

[0117] Small membership degree: μ_small(p) = triangle(p, a_small, b_small, c_small);

[0118] Medium membership degree: μ_medium(p) = triangle(p, a_medium, b_medium, c_medium);

[0119] Large membership degree: μ_large(p) = triangle(p, a_large, b_large, c_large).

[0120] A3. Fuzzy rules according to the operating characteristics of the submersible electric pump

[0121] If the pump speed is low and the pressure difference is small, then the frequency of the frequency converter is low;

[0122] If the pump speed is low and the pressure difference is medium, then the frequency of the frequency converter is medium;

[0123] If the pump speed is low and the pressure difference is large, then the frequency of the frequency converter is high;

[0124] If the pump speed is medium and the pressure difference is small, then the frequency of the frequency converter is medium;

[0125] If the pump speed is medium and the pressure difference is medium, then the frequency of the frequency converter is medium;

[0126] If the pump speed is medium and the pressure difference is large, then the frequency of the frequency converter is high;

[0127] If the pump speed is high and the pressure difference is small, then the frequency of the frequency converter is high;

[0128] If the pump speed is high and the pressure difference is medium, then the frequency of the frequency converter is high;

[0129] If the pump speed is high and the pressure difference is large, then the frequency of the frequency converter is high.

[0130] A4. According to the membership degree values of the input variables and the designed fuzzy rules, perform fuzzy inference to determine the fuzzy set of the output variable and its membership degree values; according to the condition part of each rule and the membership degree values of the input variables, calculate the activation degree of each rule:

[0131] Activation degree of Rule 1: activation_rule1 = min(μ_low(v), μ_small(p)),

[0132] Activation degree of Rule 2: activation_rule2 = min(μ_low(v), μ_medium(p)),

[0133] Activation degree of Rule 3: activation_rule3 = min(μ_low(v), μ_large(p)),

[0134] Activation degree of Rule 4: activation_rule4 = min(μ_medium(v), μ_small(p)),

[0135] Activation degree of Rule 5: activation_rule5 = min(μ_medium(v), μ_medium(p)),

[0136] Activation degree of Rule 6: activation_rule6 = min(μ_medium(v), μ_large(p)),

[0137] Activation degree of Rule 7: activation_rule7 = min(μ_high(v), μ_small(p)),

[0138] Activation degree of Rule 8: activation_rule8 = min(μ_high(v), μ_medium(p)),

[0139] Activation degree of Rule 9: activation_rule9 = min(μ_high(v), μ_large(p)).

[0140] A5. According to the rule activation degrees obtained from fuzzy inference and the membership degree values in the fuzzy rule base, calculate the membership degree values of the output variable in each fuzzy set:

[0141] Membership degree of low frequency of the frequency converter: μ_low(f) = activation_rule1

[0142] Membership degree in the frequency of the frequency converter: μ_medium(f) = max(activation_rule2, activation_rule4, activation_rule5)

[0143] Membership degree in the high frequency of the frequency converter: μ_high(f) = max(activation_rule3, activation_rule6, activation_rule7, activation_rule8, activation_rule9)

[0144] A6. Calculate the final pump speed control quantity according to the above fuzzy control algorithm, and then input this result to the PLC controller to adjust the pump speed of the submersible electric pump.

[0145] Control quantity = (μ_low * Min_Speed + μ_medium * Mid_Speed + μ_high * Max_Speed) / (μ_low + μ_medium + μ_high)

[0146] Where:

[0147] μ_low represents the membership degree value of the pump speed of the submersible electric pump in the low-speed fuzzy set;

[0148] μ_medium represents the membership degree value of the pump speed of the submersible electric pump in the medium-speed fuzzy set;

[0149] μ_high represents the membership degree value of the pump speed of the submersible electric pump in the high-speed fuzzy set;

[0150] Min_Speed represents the minimum value of the pump speed of the submersible electric pump;

[0151] Max_Speed represents the maximum value of the pump speed of the submersible electric pump;

[0152] Mid_Speed represents the intermediate value of the pump speed of the submersible electric pump.

[0153] The fuzzy control algorithm uses membership functions (μ_low, μ_medium, μ_high) to evaluate the degree of different pump speeds v and pressure differences p. The value ranges of these membership functions in fuzzy logic are usually from 0 to 1, representing the transition from "completely not in line with" to "completely in line with" a certain specific condition.

[0154] μ_low (low-speed membership degree): represents the degree to which the pump speed v belongs to the "low-speed" category, and its value range is between 0 and 1. When the pump speed is very close to the set "low speed", the value of μ_low approaches 1; if the pump speed is far from the "low-speed" definition, the value of μ_low approaches 0.

[0155] μ_medium (medium speed membership degree): It represents the degree to which the pump speed v belongs to the "medium speed" category, and its value range is also between 0 and 1. When the pump speed is in the region between "low speed" and "high speed", the value of μ_medium is relatively high, approaching 1; if the pump speed deviates from this region, the value of μ_medium decreases and approaches 0.

[0156] μ_high (high speed membership degree): It represents the degree to which the pump speed v belongs to the "high speed" category, and its value range is also between 0 and 1. When the pump speed is very close to the set "high speed", the value of μ_high is close to 1; if the pump speed is far from the "high speed" definition, the value of μ_high is close to 0.

[0157] Taking the submersible electric pump speed v defined as 500 - 3000 revolutions per minute as an example, in practical applications, "low speed" may be defined near 500 revolutions per minute, "high speed" may be defined near 3000 revolutions per minute, and "medium speed" may be the speed between the two.

[0158] Value range of the minimum pump speed Min_Speed: It represents the lowest speed that the submersible electric pump can reach. The specific value depends on the pump design, performance, and operating requirements. For example, if the design of this submersible electric pump allows the lowest rotational speed of 500 revolutions per minute, then Min_Speed may be set to 500 revolutions per minute.

[0159] Value range of the maximum pump speed Max_Speed: It represents the highest speed that the submersible electric pump can reach. It also depends on the pump design, performance, and operating requirements. For example, if the design of this submersible electric pump allows the highest rotational speed of 3000 revolutions per minute, then Max_Speed may be set to 3000 revolutions per minute.

[0160] Value range of the intermediate pump speed Mid_Speed: It is usually between Min_Speed and Max_Speed, and may be the average of the two or determined by adjusting according to specific working conditions. For example, if Min_Speed is 500 revolutions per minute and Max_Speed is 3000 revolutions per minute, then Mid_Speed may be set to 1750 revolutions per minute.

[0161] If the pressure difference p during the normal operation of the submersible electric pump is x kPa to y kPa,

[0162] When the high pressure difference of the pressure difference p is greater than y + Δ kPa, the submersible electric pump stops running;

[0163] When the low pressure difference of the pressure difference p is less than x - Δ' kPa, the submersible electric pump stops running;

[0164] When the pressure difference of the submersible electric pump returns to the normal operating range of x kPa to y kPa, the submersible electric pump resumes operation.

[0165] For example: If the normal operating pressure difference of the submersible electric pump is x kPa to y kPa, and x kPa is set to 1000 kPa and y kPa is set to 2000 kPa, the normal pressure difference range of the submersible electric pump is 1000 - 2000 kPa; the excessive pressure difference y + Δ kPa is set to 2500 kPa, and when the pressure difference p exceeds 2500 kPa, the submersible electric pump stops operating; similarly, the low pressure difference x - Δ′ kPa is set to 800 kPa, and when the pressure difference p is lower than 800 kPa, the submersible electric pump stops operating; when the pressure difference p of the submersible electric pump returns to 1000 - 2000 kPa, the submersible electric pump resumes operation.

[0166] A control system for the intermittent oil production method of the submersible electric pump includes a PLC controller 1, a working condition monitoring device 2 of the submersible electric pump, and a frequency converter 3.

[0167] The pressure sensor of the working condition monitoring device 2 is used to monitor the working condition data of the submersible electric pump and transmit the data to the PLC controller 1; the PLC controller 1 receives the transmitted data from the working condition monitoring device 2 and controls the submersible electric pump according to the preset fuzzy control algorithm; the frequency converter 3 is connected to the PLC controller 1 and receives the control signal from the PLC controller 1 to adjust the output frequency of the frequency converter 3 and the motor speed of the submersible electric pump.

[0168] Furthermore, the frequency converter 3 is connected to the PLC controller 1 through RS485 communication; the working condition monitoring device 2 transmits the monitoring data to the PLC controller 1 through the Modbus RTU protocol.

[0169] The intermittent oil production method and control system of the submersible electric pump based on the fuzzy control algorithm of the present invention have the following characteristics:

[0170] 1. Intelligent regulation: By adopting the fuzzy control algorithm and data based on the working condition monitoring of the submersible electric pump, intelligent regulation of the submersible electric pump is realized, improving the working efficiency and performance of the submersible electric pump.

[0171] 2. High-precision control: Using the fuzzy control algorithm to perform fuzzy adjustment on the pump speed and pressure difference of the submersible electric pump, precise control of the submersible electric pump can be achieved. According to the changes in the working conditions, the pump speed and pressure difference are adjusted in real time, enabling the submersible electric pump to maintain the best working state under different working conditions and improving the oil production efficiency.

[0172] 3. Energy conservation and emission reduction: Intelligently regulating the submersible electric pump to avoid excessive or too low pump speed and pressure difference, thereby avoiding energy waste and achieving the purpose of energy conservation and emission reduction.

[0173] 4. Good system stability: By adopting a combined control method, integrating the working condition monitoring device with the frequency converter and conducting linkage control through the PLC controller, the integrated intermittent oil production control system for submersible electric pumps can achieve tight coordination between the pump speed and the pressure difference, respond promptly to changes in working conditions, and improve the response speed of the control system and the operating stability of the submersible electric pumps.

[0174] 5. Improve oil production efficiency: Intelligently regulate the pump speed and pressure difference of the submersible electric pump to achieve intermittent oil production operations, effectively control the production process of the oil well; through reasonable regulation, maximize the oil production efficiency and increase the oil well output and economic benefits.

[0175] The present invention adopts an intelligent control system for intermittent oil production, applies the new theory of the supply and discharge relationship in oil well production, conducts data analysis and processing by computer, and uses automatic control technology to perform intelligent intermittent oil production control on the submersible electric pump, so as to organically combine the operation mode of the submersible electric pump with the liquid supply condition and displacement of the oil reservoir, thereby effectively improving the working efficiency of the submersible electric pump.

[0176] It should be noted that the above embodiments are examples rather than limitations of the present invention, and those skilled in the art will be able to design many alternative embodiments without departing from the scope of the claims of this patent.

Claims

1. An intermittent oil production method for submersible electric pumps, the steps of which are as follows: Start: Enter the initial state of the system; S1. Data acquisition: The working condition monitoring device monitors and acquires the working condition data of the submersible electric pump in real time. The working condition data includes the pump speed v and the pressure difference p; S2. Data processing: The acquired working condition data is transmitted to the PLC controller, and the PLC controller processes and analyzes the working condition data; S3. Execution of control algorithm: Based on the processed and analyzed data, the PLC controller executes a pre-designed fuzzy control algorithm; S4. Generation of control commands: The fuzzy control algorithm generates corresponding control commands according to the current working condition data of the submersible electric pump; S5. Sending of control commands: The PLC controller sends the generated control commands to the frequency converter; S6. Control of the frequency converter: The frequency converter adjusts the output frequency according to the received control commands to control the motor speed n of the submersible electric pump; S7. Monitoring and feedback: The working condition monitoring device feeds back the working condition data monitored in real time to the PLC controller; S8. Processing of feedback data: The PLC controller processes the received working condition data; S9. Optimization of control strategy: The PLC controller adjusts and optimizes the control strategy according to the feedback data; S10. Return to S2: Loop through S2 to S10 to adjust and control the motor speed n of the submersible electric pump.

2. The intermittent oil production method for submersible electric pumps according to claim 1, characterized in that: In the step S2, the PLC controller processes and analyzes the working condition data, including: data verification, data formatting and preprocessing, feature extraction, and state evaluation.

3. The intermittent oil production method for submersible electric pumps according to claim 2, characterized in that: The data verification includes confirming the accuracy and integrity of the data, ensuring that the data is within a reasonable operating range, and excluding abnormal or incorrect readings; The data formatting and preprocessing is to convert the original data obtained from the sensor into a format that can be used for further analysis, and normalize, scale, or transform the data; The feature extraction is to extract key information from the working condition data, including the average pump speed, maximum / minimum pressure difference, and identify and calculate the parameters that have an important impact on the pump operating condition; The state evaluation is to evaluate the operating state of the submersible electric pump according to the extracted features and preset criteria; determine whether there are any potential operating problems or abnormal conditions.

4. The intermittent oil production method for submersible electric pumps according to claim 3, characterized in that: The symbols and parameters of the fuzzy control algorithm in the step S3: v - pump speed, the impeller speed of the submersible electric pump, p - pressure difference, the pressure difference between the suction port and the discharge port of the submersible electric pump, f - the frequency of the frequency converter, n - the motor speed of the submersible electric pump, Pump speed membership function: a_low, b_low, c_low, a_medium, b_medium, c_medium, a_high, b_high, c_high; Pressure difference membership function: a_small, b_small, c_small, a_medium, b_medium, c_medium, a_large, b_large, c_large. Adaptive regulation process of pump speed v based on fuzzy algorithm: A1. Calculation of membership degree of pump speed v Low-speed membership degree: μ_low(v) = triangle(v, a_low, b_low, c_low); Medium-speed membership degree: μ_medium(v) = triangle(v, a_medium, b_medium, c_medium); High-speed membership degree: μ_high(v) = triangle(v, a_high, b_high, c_high); A2. Calculation of membership degree of pressure difference p Small membership degree: μ_small(p) = triangle(p, a_small, b_small, c_small); Medium membership degree: μ_medium(p) = triangle(p, a_medium, b_medium, c_medium); Large membership degree: μ_large(p) = triangle(p, a_large, b_large, c_large); A3. Fuzzy rules based on the operating characteristics of submersible electric pumps If the pump speed is low and the pressure difference is small, the frequency of the frequency converter is low; If the pump speed is low and the pressure difference is medium, the frequency of the frequency converter is medium; If the pump speed is low and the pressure difference is large, the frequency of the frequency converter is high; If the pump speed is medium and the pressure difference is small, the frequency of the frequency converter is medium; If the pump speed is medium and the pressure difference is medium, the frequency of the frequency converter is medium; If the pump speed is medium and the pressure difference is large, the frequency of the frequency converter is high; If the pump speed is high and the pressure difference is small, the frequency of the frequency converter is high; If the pump speed is high and the pressure difference is medium, the frequency of the frequency converter is high; If the pump speed is high and the pressure difference is large, the frequency of the frequency converter is high; A4. Based on the membership degree values of the input variables and the designed fuzzy rules, perform fuzzy inference to determine the fuzzy set of the output variable and its membership degree values; according to the condition part of each rule and the membership degree values of the input variables, calculate the activation degree of each rule: Activation degree of rule 1: activation_rule1 = min(μ_low(v), μ_small(p)), Activation degree of rule 2: activation_rule2 = min(μ_low(v), μ_medium(p)), Activation degree of rule 3: activation_rule3 = min(μ_low(v), μ_large(p)), Activation degree of rule 4: activation_rule4 = min(μ_medium(v), μ_small(p)), Activation degree of rule 5: activation_rule5 = min(μ_medium(v), μ_medium(p)), Activation degree of rule 6: activation_rule6 = min(μ_medium(v), μ_large(p)), Activation degree of Rule 7: activation_rule7 = min(μ_high(v), μ_small(p)), Activation degree of Rule 8: activation_rule8 = min(μ_high(v), μ_medium(p)), Activation degree of Rule 9: activation_rule9 = min(μ_high(v), μ_large(p)); A5. Calculate the membership degree values of the output variable in each fuzzy set according to the rule activation degrees obtained from fuzzy inference and the membership degree values in the fuzzy rule base: Membership degree of low frequency of the frequency converter: μ_low(f) = activation_rule1 Membership degree of medium frequency of the frequency converter: μ_medium(f) = max(activation_rule2, activation_rule4, activation_rule5) Membership degree of high frequency of the frequency converter: μ_high(f) = max(activation_rule3, activation_rule6, activation_rule7, activation_rule8, activation_rule9) A6. Calculate the final pump speed control quantity according to the above fuzzy control algorithm, and input the result to the PLC controller for adjusting the pump speed of the submersible electric pump. Control quantity = (μ_low * Min_Speed + μ_medium * Mid_Speed + μ_high * Max_Speed) / (μ_low + μ_medium + μ_high) Where: μ_low represents the membership degree value of the pump speed of the submersible electric pump in the low-speed fuzzy set; μ_medium represents the membership degree value of the pump speed of the submersible electric pump in the medium-speed fuzzy set; μ_high represents the membership degree value of the pump speed of the submersible electric pump in the high-speed fuzzy set; Min_Speed represents the minimum value of the pump speed of the submersible electric pump; Max_Speed represents the maximum value of the pump speed of the submersible electric pump; Mid_Speed represents the intermediate value of the pump speed of the submersible electric pump.

5. The intermittent oil production method for a submersible electric pump according to claim 4, characterized in that: The pressure difference during the normal operation of the submersible electric pump is x kPa to y kPa. When the high pressure difference is greater than y + Δ kPa, the submersible electric pump stops running; When the low pressure difference is less than x - Δ′ kPa, the submersible electric pump stops running; When the pressure difference of the submersible electric pump returns to the normal operation range of x kPa to y kPa, the submersible electric pump resumes operation.

6. A control system applying the intermittent oil production method for a submersible electric pump according to claim 1, including a PLC controller, characterized in that: The control system further includes: a working condition monitoring device and a frequency converter for the submersible electric pump; The pressure sensor of the working condition monitoring device is used to monitor the working condition data of the submersible electric pump and transmit the data to the PLC controller; The PLC controller receives the transmission data from the working condition monitoring device and controls the submersible electric pump according to the preset fuzzy control algorithm; The frequency converter is connected to the PLC controller and receives the control signal from the PLC controller to adjust the output frequency of the frequency converter and the motor speed of the submersible electric pump.

7. The intermittent oil production control system for a submersible electric pump according to claim 6, characterized in that: The frequency converter is connected to the PLC controller through RS485 communication.

8. The intermittent oil production control system for a submersible electric pump according to claim 7, wherein: The working condition monitoring device transmits the monitoring data to the PLC controller through the Modbus RTU protocol.

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