A method, device, equipment, medium and product for optimizing pumping unit parameters

Abstract

The present application discloses a method, device, equipment, medium and product for optimizing pumping unit parameters, which relates to the field of oilfield production engineering. The method includes acquiring a stroke phase signal, pressure data and sucker rod string load in real time at each iterative step; determining a stroke stage based on the stroke phase signal; when the stroke stage is an upstroke stage, adjusting the acceleration of the linear motor based on the sucker rod string load and the viscosity parameter of the fluid in the oil pipe until the pump efficiency reaches a pump efficiency threshold, thereby obtaining the optimal upstroke parameters; when the stroke stage is a downstroke stage, adjusting the operating speed of the linear motor based on the pressure data and the pressure fluctuation rate threshold, thereby obtaining the pressure fluctuation amplitude and the optimal downstroke parameters; and adjusting the iterative step size based on the pressure fluctuation amplitude using Fourier transform. The present application can achieve refined control of the pumping unit and solve the problems of low pump efficiency, rod and pipe eccentric wear and energy waste.

Description

Technical Field

[0001] The present application relates to the field of oilfield production engineering, and in particular to a method, device, equipment, medium and product for optimizing pumping unit parameters. Background Art

[0002] In the construction of digital oil fields, pumping unit stroke adjustment is a core link in improving extraction efficiency and equipment reliability. The traditional fixed stroke mode is difficult to adapt to the dynamically changing fluid supply capacity and complex working conditions in the well, which can easily lead to low pump efficiency, eccentric wear of rods and pipes, and energy waste. With the popularization of frequency conversion technology and Internet of Things sensing, variable stroke control has become possible, but its early optimization strategies mostly focused on global stroke adjustment, ignoring the differences in mechanical properties between the upstroke and downstroke: the upstroke needs to overcome the inertia force and viscous resistance of the liquid column, and too high a stroke rate can easily cause pump valve closure delays; too fast a downstroke can easily trigger a liquid hammer effect, exacerbating equipment fatigue damage. Current technology urgently needs to break through the dynamic coupling problem of independent optimization of sub-strokes to achieve refined control. Summary of the Invention

[0003] The purpose of this application is to provide a method, device, equipment, medium and product for optimizing pumping unit parameters, which can realize refined control of the pumping unit and solve the problems of low pump efficiency, eccentric wear of rod and tube and waste of energy.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a method for optimizing pumping unit parameters, comprising:

[0006] At each iteration step, the stroke phase signal, pressure data and sucker rod string load are acquired in real time;

[0007] Determining a stroke phase according to the stroke phase signal; the stroke phase includes an upstroke phase and a downstroke phase;

[0008] When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the sucker rod string load and the viscosity parameter of the fluid in the oil pipe until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameter;

[0009] When the stroke stage is a downstroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold to obtain the pressure fluctuation amplitude and the optimal downstroke parameters;

[0010] The iteration step size is adjusted using Fourier transform according to the pressure fluctuation amplitude.

[0011] In one embodiment, determining the stroke phase according to the stroke phase signal specifically includes:

[0012] determining a first-order difference based on the stroke phase signal;

[0013] If the first-order difference is positive, the stroke phase is an upstroke phase;

[0014] If the first-order difference is negative, the stroke phase is a downstroke phase.

[0015] In one embodiment, when the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the sucker rod string load and the viscosity parameter of the fluid in the tubing until the pump efficiency reaches a pump efficiency threshold, thereby obtaining the optimal upstroke parameters, which specifically include:

[0016] When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted using a fuzzy PID control algorithm according to the sucker rod string load and the viscosity parameters of the fluid in the oil pipe until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameters.

[0017] In one embodiment, when the stroke stage is the downstroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold to obtain the pressure fluctuation amplitude and the optimal downstroke parameters, specifically including:

[0018] When the stroke stage is the downstroke stage, the operating speed of the linear motor is adjusted using an anti-liquid hammer optimization algorithm according to the pressure data and the pressure fluctuation rate threshold to obtain a pressure fluctuation amplitude;

[0019] The pressure fluctuation rate is determined according to the pressure data; when the pressure fluctuation rate is equal to a pressure fluctuation rate threshold, an optimal downstroke parameter is obtained.

[0020] In one embodiment, adjusting the iteration step size using Fourier transform according to the pressure fluctuation amplitude specifically includes:

[0021] Determining vibration frequency characteristics using Fourier transform according to the pressure fluctuation amplitude;

[0022] determining a spectral distortion degree according to the vibration frequency characteristics;

[0023] The iteration step size is dynamically adjusted according to the spectrum distortion degree.

[0024] In one embodiment, after adjusting the iteration step size using Fourier transform according to the pressure fluctuation amplitude, the method further includes:

[0025] Whenever the iteration step reaches the set value, the optimal parameters of the upstroke, the optimal parameters of the downstroke and the corresponding pump diameter are stored in the database.

[0026] In a second aspect, the present application provides an oil pumping unit, comprising: an oil pumping unit system, a fluid supply system, a linear motor system, and an intelligent control system; the intelligent control system applies the oil pumping unit parameter optimization method;

[0027] The pumping unit system is used to send the acquired stroke phase signal, pressure data and sucker rod string load to the intelligent control system; the intelligent control system is used to control the linear motor of the linear motor system according to the stroke stage using the stroke phase signal, pressure data and sucker rod string load.

[0028] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the pumping unit parameter optimization method.

[0029] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which implements the pumping unit parameter optimization method when executed by a processor.

[0030] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which implements the pumping unit parameter optimization method when executed by a processor.

[0031] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0032] The present application provides a method, apparatus, device, medium, and product for optimizing pumping unit parameters. At each iteration step, stroke phase signals, pressure data, and sucker rod string loads are acquired in real time. The stroke phase is determined based on the stroke phase signals. The stroke phases include an upstroke phase and a downstroke phase. When the stroke phase is the upstroke phase, the acceleration of the linear motor is adjusted based on the sucker rod string load and the viscosity parameters of the fluid in the tubing until the pump efficiency reaches a pump efficiency threshold, thereby obtaining optimal upstroke parameters. When the stroke phase is the downstroke phase, the operating speed of the linear motor is adjusted based on the pressure data and the pressure fluctuation rate threshold, thereby obtaining pressure fluctuation amplitude and optimal downstroke parameters. The iteration step is adjusted using Fourier transform based on the pressure fluctuation amplitude. The stroke phase of the pumping unit is determined based on the real-time acquired stroke phase signals and pressure data, and the linear motor is dynamically adjusted to achieve refined control. While ensuring stable fluid production, energy waste and equipment loss are significantly reduced, thereby solving the problems of low pump efficiency, rod and tubing eccentric wear, and energy waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 Flowchart of the pumping unit parameter optimization method.

[0035] Figure 2 Schematic diagram of the oil pumping unit.

[0036] Figure numerals: 100 - pumping unit system, 200 - fluid supply system, 300 - linear motor system, 400 - intelligent control system, 1 - casing, 2 - oil pipe, 3 - sucker rod, 4 - oil pump, 5 - hydraulic servo fluid supply end, 6 - precision slide rail, 7 - cable, 8 - linear motor, 9 - control panel, 10 - program panel, 11 - base. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0038] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0039] In an exemplary embodiment, Figure 1 As shown, a method for optimizing pumping unit parameters is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In an embodiment of the present application, the method includes the following steps.

[0040] Step 101: At each iteration step, the stroke phase signal, pressure data, and sucker rod string load are acquired in real time.

[0041] Step 102: Determine a stroke phase according to the stroke phase signal; the stroke phase includes an upstroke phase and a downstroke phase.

[0042] Step 103: When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the sucker rod string load and the viscosity parameter of the fluid in the oil pipe until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameters.

[0043] Step 104: When the stroke stage is the downstroke stage, the running speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold to obtain the pressure fluctuation amplitude and the optimal downstroke parameters.

[0044] Step 105: Adjust the iteration step size using Fourier transform according to the pressure fluctuation amplitude.

[0045] The stroke phase of the pumping unit is determined by the real-time acquired phase signal and the pressure data, and the linear motor is dynamically adjusted to achieve refined control. While ensuring stable liquid production, energy waste and equipment loss are greatly reduced, thereby solving the problems of low pump efficiency, rod and pipe eccentric wear, and energy waste.

[0046] In an exemplary embodiment, determining the stroke phase according to the stroke phase signal specifically includes:

[0047] A first-order difference is determined according to the stroke phase signal; if the first-order difference is positive, the stroke phase is an upstroke phase; if the first-order difference is negative, the stroke phase is a downstroke phase.

[0048] In practical applications, the stroke phase is determined based on the stroke phase signal collected by the Hall displacement sensor and the real-time pressure data from the pressure transmitter. The first-order difference v(t) is calculated using the displacement x(t). The value is positive when the displacement is upward and negative when the displacement is downward. At the same time, when the upstroke starts, the floating valve closes and the fixed valve opens. The liquid in the oil pipe is sucked out, causing the pressure to drop instantaneously, and the pressure gradient dP / dt is less than 0.

[0049] In an exemplary embodiment, when the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the sucker rod string load and the viscosity parameter of the fluid in the tubing until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameters, which specifically include:

[0050] When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted using a fuzzy PID control algorithm according to the sucker rod string load and the viscosity parameters of the fluid in the oil pipe until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameters; the optimal upstroke parameters are specifically the optimal upstroke number value.

[0051] In practical applications, the fluid viscosity is high, the flow resistance of the oil pipe increases, and the acceleration needs to be increased to shorten the drainage time; the rod load is large, the mechanical load is too high, and the acceleration needs to be reduced to avoid overload. Dynamic adjustment is performed using PID parameters, and the compensation factor f (μ, F) is fitted according to field data. a (t) = K p ×e(t)+K i ×∫e(t)dt+K d×de(t) / dt+f(μ, F)×a0, a0 is the initial acceleration, a(t) is the acceleration, e(t) is the displacement error, displacement error = target displacement - actual displacement, K p , K i , K d The three parameters of the PID controller are the proportional control coefficient, the integral control coefficient, and the differential control coefficient. μ is the viscosity parameter of the fluid in the tubing, and F is the sucker rod string load. Based on a large amount of field data, the empirical formula f(μ, F) = 1 + 0.12ln(μ) - 0.08F is obtained by regression analysis. level +0.05T vis , F level It is the grading index of the column load. When F<30kN, F level =1, when 30kN≤F<60kN, F level =2, when F≥60kN, F level =3;T vis is the viscosity-temperature correction coefficient. When the fluid temperature is 30°C, T vis =0, every 10℃ rise, T vis Increase by 0.01.

[0052] In an exemplary embodiment, when the stroke stage is the downstroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold to obtain the pressure fluctuation amplitude and the optimal downstroke parameters, specifically including:

[0053] When the stroke stage is the downstroke stage, the operating speed of the linear motor is adjusted using an anti-liquid hammer optimization algorithm according to the pressure data and the pressure fluctuation rate threshold to obtain a pressure fluctuation amplitude;

[0054] The pressure fluctuation rate is determined according to the pressure data; when the pressure fluctuation rate is equal to the pressure fluctuation rate threshold, the optimal downstroke parameter is obtained; the optimal downstroke parameter is specifically the optimal stroke number value of the downstroke.

[0055] In an exemplary embodiment, adjusting the iteration step size using Fourier transform according to the pressure fluctuation amplitude specifically includes:

[0056] Determining vibration frequency characteristics using Fourier transform according to the pressure fluctuation amplitude;

[0057] determining a spectral distortion degree according to the vibration frequency characteristics;

[0058] The iteration step size is dynamically adjusted according to the spectrum distortion degree.

[0059] In practical applications, distortion = (||Current spectrum obtained through Fourier transform - Reference spectrum recorded during normal equipment operation||) / (||Reference spectrum recorded during normal equipment operation||) × 100%. When the distortion is less than 10%, the step size ∆f is 0 and no adjustment is required. When the distortion is 10% ≤ ∆f and less than 20%, the step size ∆f is 1.0 Hz. When the distortion is ≥ 20%, the step size ∆f is 1.5 Hz.

[0060] In an exemplary embodiment, after adjusting the iteration step size using Fourier transform according to the pressure fluctuation amplitude, it also includes: whenever the iteration step size reaches a set value, storing the optimal upstroke parameters, the optimal downstroke parameters and the corresponding pump diameter in a database.

[0061] The pumping unit parameter optimization method provided in this application is suitable for the dynamic optimization of the pumping unit stroke parameters in the construction of digital oil fields. It aims to solve the problem that the traditional fixed stroke mode is difficult to adapt to the dynamically changing fluid supply capacity and complex working conditions in the well, which easily leads to low pump efficiency, rod and pipe wear, and energy waste. Compared with the existing technology, this application optimizes the stroke parameters independently by stroke, specifically the optimal stroke value for the upstroke and the optimal stroke value for the downstroke. It can significantly improve the comprehensive performance of the pumping unit system under actual working conditions, and can dynamically adapt to the differentiated load characteristics of the upstroke and downstroke. Compared with the traditional fixed stroke mode, this application can reduce energy waste, extend the service life of components, have good adaptability to working conditions, and achieve stable and efficient operation.

[0062] The present application also provides a specific method for practical application of a pumping unit parameter optimization method, comprising the following steps:

[0063] After assembling the experimental device, import the preset optimization algorithm (such as the fuzzy PID parameter table) through the program panel;

[0064] Start the fluid supply system and set the target formation pressure (e.g. 5MPa);

[0065] PLC collects displacement, load and pressure data in real time and calculates the stroke deviation value;

[0066] Among them, the impulse deviation value Δf stroke Equal to the target impulse f target -Actual stroke frequency f real (unit is Hz), the expression is Δf stroke =f target −f real , f real =1 / ∆t, SPM is the number of strokes, and ∆t is the time difference between the starting points of two adjacent upstrokes.

[0067] In actual application, before determining the stroke stage, the stroke deviation value is first judged. When the stroke deviation value is positive, it indicates that the actual stroke is too high and the stroke should be reduced to avoid overload or equipment wear; when the stroke deviation value is negative, it indicates that the actual stroke is insufficient and the stroke should be increased to compensate for load fluctuations. new = f targe +K×Δf stroke， K is the proportional coefficient, which is set according to the characteristics of the equipment. When the stroke deviation value is 0, the stroke stage is judged.

[0068] Upstroke phase: If a drop in pump efficiency is detected (flow rate < 80% of the pump efficiency threshold), the fuzzy PID automatically increases acceleration to optimize the fill factor; the pump efficiency is the fill factor.

[0069] Among them, the filling coefficient η= (actual displacement V actual / Theoretical displacement V theoretical )×100%, V theoretical =(πD 2 ×S×n) / 4. V actual It can be measured by a flow meter. D is the diameter of the oil pump piston, S is the length of a single stroke, and n is the stroke frequency, which is the number of reciprocating motions per second.

[0070] During the downstroke phase, if the pressure fluctuation rate exceeds the pressure fluctuation rate threshold, the motor speed is immediately reduced to a safe range (e.g., 0.5 m / s²). The pressure fluctuation rate is the rate of change of pressure per unit time (pressure fluctuation rate = (current pressure - previous pressure) / sampling interval). The pressure fluctuation amplitude refers to the maximum range of pressure change within a cycle, that is, the difference between the lowest and highest pressures. The pressure fluctuation rate reflects the dynamic rate of pressure change, while the pressure fluctuation amplitude reflects the static range of pressure change.

[0071] Iterative optimization: After every 10 stroke cycles, the system updates the optimal parameters to the database based on historical data. Among them, the optimal parameters include K p , K i , K d , SPM, a(t).

[0072] This application uses independent optimization technology for each stroke to significantly improve the overall operating efficiency and equipment reliability of the pumping unit system. In the traditional mode, the stroke frequency of the upper and lower strokes is the same. This application uses independent optimization for each stroke, with the upper stroke frequency being faster to reduce leakage, and the lower stroke frequency being slower to reduce friction, reduce eccentric wear losses, and improve pump efficiency. This application uses intelligent sensing of real-time working condition changes in the upper and lower strokes to dynamically adjust the stroke frequency parameters, significantly reducing energy waste and equipment losses while ensuring stable fluid production. Compared to traditional control methods, it can automatically optimize the operating rhythm based on dynamic conditions such as downhole pressure and rod column load, avoiding mechanical shock caused by excessively fast strokes and solving the problem of inefficiency caused by excessively slow strokes. Especially in complex oil wells with high sand content and high gas-liquid ratio, this technology can adaptively adjust the stroke rhythm, reduce the risk of failures such as pump jamming and eccentric wear, extend the pump inspection cycle, and reduce maintenance costs.

[0073] Based on the same inventive concept, embodiments of the present application also provide a pumping unit device for implementing the aforementioned pumping unit parameter optimization method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more pumping unit device embodiments provided below can be found in the aforementioned limitations of the pumping unit parameter optimization method and will not be further elaborated here.

[0074] In an exemplary embodiment, Figure 2 As shown, a pumping unit device is provided, comprising: a pumping unit system 100, a fluid supply system 200, a linear motor system 300, and an intelligent control system 400; the intelligent control system 400 applies the pumping unit parameter optimization method;

[0075] The pumping unit system 100 is used to send the acquired stroke phase signal, pressure data and sucker rod string load to the intelligent control system 400; the intelligent control system 400 is used to control the linear motor of the linear motor system 300 according to the stroke stage using the stroke phase signal, pressure data and sucker rod string load.

[0076] In actual applications, the intelligent control system 400 transmits program instructions to the linear motor system 300. After receiving the instructions, the linear motor system 300 drives the pumping unit system 100 to optimize parameters.

[0077] As a preferred structure, the pumping unit system 100 includes a casing 1, an oil pipe 2, a sucker rod 3, and a pump 4. The pump 4 can be replaced to study the effects of different pump diameters. The modular pump barrel assembly can be quickly replaced and includes casing tail ends with different pump diameter specifications (Φ28mm to Φ95mm) connected to the liquid supply system through a pipeline.

[0078] Similarly, the fluid supply system 200 consists of a hydraulic servo fluid supply end 5 and a precision slide 6. The height of the hydraulic servo fluid supply end is adjustable and controlled by the precision slide. It can be used to simulate the supply side formation pressure and can be used to simulate 0.5-15MPa formation pressure. The pressure regulation resolution reaches 0.1MPa.

[0079] In a specific embodiment of the present application, the linear motor system 300 includes a linear motor 8 and a cable 7. The linear motor 8 is controlled by an intelligent control system 400, thereby driving the pumping unit system 100. The cable 7 is a submersible watertight cable with longitudinal watertight characteristics.

[0080] The intelligent control system includes a control panel 9 and a program panel 10. The control panel 9 is used to control the operation of the linear motor 8. The program panel 10 stores a stroke optimization algorithm module. According to different programs, the stroke parameters of the upstroke and downstroke can be optimized separately, and the upstroke and downstroke parameters can be adjusted. This achieves differentiated stroke control of the upstroke and downstroke, and the upstroke and downstroke parameters can be adjusted.

[0081] The oil pumping unit further includes a base 11 , on which the oil pumping unit system 100 , the liquid supply system 200 , the linear motor system 300 and the intelligent control system 400 are all arranged.

[0082] The control principle is as follows: the Hall displacement sensor installed at the end of the sucker rod 3 collects stroke phase signals in real time, and simultaneously receives real-time pressure data from the pressure transmitter 200 of the liquid supply system (range 0-20MPa, accuracy 0.5%FS). When the upstroke is detected, the PLC calls the preset fuzzy PID control algorithm, and dynamically adjusts the acceleration curve of the linear motor 8 according to the viscosity parameters of the fluid in the tubing 2 and the current rod column load, so that the upstroke frequency is adaptively adjusted within the range of 0.5-8 times / minute; during the downstroke stage, the anti-liquid hammer optimization algorithm is activated. By monitoring the pressure fluctuation rate at the tail end of the casing 1, when the pressure fluctuation amplitude exceeds the set threshold (default 5MPa / s), the motor speed is immediately reduced, and the vibration spectrum characteristics are analyzed through Fourier transform to complete the iterative optimization of the stroke frequency parameters within 0.2 seconds. Specifically, f new =f safe +∆f,f safe is the center frequency of the safe frequency band, f safe is the adjusted center frequency, and the step size ∆f is dynamically adjusted according to the degree of spectrum distortion.

[0083] The linear motor 8 is connected to the PLC via a variable frequency drive. The PLC outputs a PWM control signal that is optically isolated and then drives the IGBT power module, achieving precise control of the motor thrust within a ±7kN range. The program panel 10 includes a built-in stroke parameter optimization database containing optimal stroke combination parameters for different pump diameters (Φ28mm to Φ95mm). When the oil well pump 4 is replaced, the system automatically recognizes the pump barrel RFID tag and loads the corresponding control parameter set.

[0084] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, memory, an input / output (I / O) interface, and a communication interface. The processor, memory, and I / O interface are connected via a system bus, and the communication interface is connected to the system bus via the I / O interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device stores pumping unit parameter optimization data. The I / O interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via a network connection. When executed by the processor, the computer program implements a method for optimizing pumping unit parameters.

[0085] Those skilled in the art will understand that the structure shown in this application is merely a block diagram of a portion of the structure related to the solution of this application and does not constitute a limitation on the computer device to which the solution of this application is applied. A specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the above-mentioned method embodiments when executing the computer program.

[0086] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the above-mentioned method embodiments when executed by a processor.

[0087] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the above method embodiments are implemented.

[0088] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0089] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0090] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0091] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0092] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0093] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for optimizing pumping unit parameters, characterized in that: The pumping unit parameter optimization method comprises: At each iteration step, the stroke phase signal, pressure data and sucker rod string load are acquired in real time; Determining a stroke phase according to the stroke phase signal; the stroke phase includes an upstroke phase and a downstroke phase; When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the sucker rod string load and the viscosity parameter of the fluid in the oil pipe until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameter, specifically comprising: when the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the sucker rod string load and the viscosity parameter of the fluid in the oil pipe using a fuzzy PID control algorithm until the pump efficiency reaches the pump efficiency threshold, thereby obtaining the optimal upstroke parameter; When the stroke stage is the downstroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold to obtain the pressure fluctuation amplitude and the optimal downstroke parameters, specifically including: when the stroke stage is the downstroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold using an anti-liquid hammer optimization algorithm to obtain the pressure fluctuation amplitude; determining the pressure fluctuation rate according to the pressure data; and obtaining the optimal downstroke parameters when the pressure fluctuation rate is equal to the pressure fluctuation rate threshold; The iteration step size is adjusted using Fourier transform according to the pressure fluctuation amplitude.

2. The method for optimizing pumping unit parameters according to claim 1, characterized in that: Determining the stroke phase according to the stroke phase signal specifically includes: determining a first-order difference based on the stroke phase signal; If the first-order difference is positive, the stroke phase is an upstroke phase; If the first-order difference is negative, the stroke phase is a downstroke phase.

3. The method for optimizing pumping unit parameters according to claim 1, characterized in that: The iterative step size is adjusted using Fourier transform according to the pressure fluctuation amplitude, specifically including: Determining vibration frequency characteristics using Fourier transform according to the pressure fluctuation amplitude; determining a spectral distortion degree according to the vibration frequency characteristics; The iteration step size is dynamically adjusted according to the spectrum distortion degree.

4. The method for optimizing pumping unit parameters according to claim 1, wherein: After adjusting the iteration step size by Fourier transform according to the pressure fluctuation amplitude, the method further includes: Whenever the iteration step reaches the set value, the optimal parameters of the upstroke, the optimal parameters of the downstroke and the corresponding pump diameter are stored in the database.

5. A pumping unit, characterized in that: The oil pumping unit device comprises: an oil pumping unit system, a fluid supply system, a linear motor system and an intelligent control system; the intelligent control system applies the oil pumping unit parameter optimization method according to any one of claims 1 to 4; The pumping unit system is used to send the acquired stroke phase signal, pressure data and sucker rod string load to the intelligent control system; the intelligent control system is used to control the linear motor of the linear motor system according to the stroke stage using the stroke phase signal, pressure data and sucker rod string load.

6. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the pumping unit parameter optimization method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for optimizing pumping unit parameters according to any one of claims 1 to 4 is implemented.

8. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for optimizing pumping unit parameters according to any one of claims 1 to 4 is implemented.

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