Pumping unit parameter optimization method, device, equipment, medium and product

Abstract

The invention discloses a pumping unit parameter optimization method and device, equipment, a medium and a product, and relates to the field of oil field oil production engineering.The method comprises the steps that under each iteration step length, stroke phase signals, pressure data and sucker rod column loads are obtained in real time; determining a stroke phase according to the stroke phase signal; when the stroke stage is an upstroke stage, the acceleration of the linear motor is adjusted according to the rod column load of the sucker rod and the viscosity parameter of fluid in an oil pipe till the pump efficiency reaches a pump efficiency threshold value, and the optimal upstroke parameter is obtained; when the stroke stage is a down-stroke stage, the running speed of the linear motor is adjusted according to the pressure data and the pressure fluctuation rate threshold value, and the pressure fluctuation amplitude and the optimal down-stroke parameter are obtained; and adjusting the iteration step length by using Fourier transform according to the pressure fluctuation amplitude. According to the invention, fine control of the oil pumping unit can be realized, and the problems of low pump efficiency, eccentric wear of the rod and the pipe and energy waste are solved.

Description

Technical Field

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

[0002] In the construction of digital oilfields, the adjustment of pumping unit strokes is a core link to improve production efficiency and equipment reliability. The traditional fixed stroke mode is difficult to adapt to the dynamically changing liquid supply capacity and complex working conditions underground, which easily leads to low pump efficiency, rod-tubing eccentric wear and energy consumption waste. With the popularization of frequency conversion technology and Internet of Things sensors, variable stroke control has become possible. However, its early optimization strategies mainly focused on global stroke adjustment, ignoring the mechanical property differences between the upstroke and the downstroke: the upstroke needs to overcome the inertial force of the liquid column and viscous resistance, and too high a stroke frequency is likely to cause delayed closing of the pump valve; too fast a downstroke is likely to trigger a water hammer effect, exacerbating equipment fatigue damage. The current technology urgently needs to break through the dynamic coupling problem of independent optimization of each stroke to achieve refined control. Summary of the Invention

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

[0004] To achieve the above object, the present application provides the following solutions: In a first aspect, the present application provides a method for optimizing pumping unit parameters, including: At each iteration step, stroke phase signals, pressure data and the load of the sucker rod string are obtained in real time; Determine the stroke stage according to the stroke phase signal; the stroke stage includes the upstroke stage and the downstroke stage; When the stroke stage is the upstroke stage, adjust the acceleration of the linear motor according to the load of the sucker rod string and the fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold to obtain the optimal upstroke parameters; When the stroke stage is the downstroke stage, adjust the running speed of the linear motor according to the pressure data and the pressure volatility threshold to obtain the pressure fluctuation amplitude and the optimal downstroke parameters; Adjust the iteration step according to the pressure fluctuation amplitude by using Fourier transform.

[0005] In an embodiment, determining the stroke stage according to the stroke phase signal specifically includes: Determine the first-order difference according to the stroke phase signal; If the first-order difference is positive, the stroke stage is the upstroke stage; If the first-order difference is negative, the stroke stage is the downstroke stage.

[0006] 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 fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and the optimal upstroke parameters are obtained. Specifically, it includes: 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 fluid viscosity parameter in the tubing by using the fuzzy PID control algorithm until the pump efficiency reaches the pump efficiency threshold, and the optimal upstroke parameters are obtained.

[0007] In one embodiment, 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, and the pressure fluctuation amplitude and the optimal downstroke parameters are obtained. Specifically, it includes: 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 by using the anti-water hammer optimization algorithm to obtain the pressure fluctuation amplitude; 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 parameters are obtained.

[0008] In one embodiment, the iteration step size is adjusted according to the pressure fluctuation amplitude by using Fourier transform. Specifically, it includes: The vibration frequency characteristics are determined according to the pressure fluctuation amplitude by using Fourier transform; The spectrum distortion degree is determined according to the vibration frequency characteristics; The iteration step size is dynamically adjusted according to the spectrum distortion degree.

[0009] In one embodiment, after the iteration step size is adjusted according to the pressure fluctuation amplitude by using Fourier transform, it further includes: Whenever the iteration step size reaches the set value, the optimal upstroke parameters, the optimal downstroke parameters and the corresponding pump diameter are stored in the database.

[0010] In a second aspect, the present application provides a pumping unit, including: a pumping unit system, a liquid supply system, a linear motor system and an intelligent control system; the intelligent control system applies the pumping unit parameter optimization method; The pumping unit system is used to send the obtained 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 by using the stroke phase signal, pressure data and sucker rod string load.

[0011] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the pumping unit parameter optimization method described above.

[0012] In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the pumping unit parameter optimization method described above.

[0013] In a fifth aspect, the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the pumping unit parameter optimization method described above.

[0014] According to the specific embodiments provided by the present application, the following technical effects are disclosed: The present application provides a pumping unit parameter optimization method, device, equipment, medium, and product. At each iteration step, the stroke phase signal, pressure data, and sucker rod string load are obtained in real time; the stroke stage is determined according to the stroke phase signal; the stroke stage includes the upstroke stage and the downstroke stage; 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 fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and the optimal upstroke parameters are obtained; 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, and the pressure fluctuation amplitude and the optimal downstroke parameters are obtained; the iteration step is adjusted by using Fourier transform according to the pressure fluctuation amplitude. By determining the stroke stage of the pumping unit according to the real-time obtained stroke phase signal and the pressure data, the linear motor is dynamically adjusted to achieve refined control, while ensuring stable liquid production, significantly reducing energy waste and equipment loss, thereby solving the problems of low pump efficiency, rod-tube eccentric wear, and energy consumption waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or in the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a flowchart of the pumping unit parameter optimization method.

[0017] Figure 2 It is a schematic diagram of the pumping unit device.

[0018] Reference numerals: 100 - pumping unit system, 200 - liquid supply system, 300 - linear motor system, 400 - intelligent control system, 1 - casing, 2 - tubing, 3 - sucker rod, 4 - submersible pump, 5 - hydraulic servo liquid supply end, 6 - precision slide rail, 7 - cable, 8 - linear motor, 9 - control panel, 10 - program panel, 11 - base. Detailed implementation manners

[0019] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the protection scope of the present application.

[0020] To make the above objects, features, and advantages of the present application more obvious and understandable, the present application will be further described in detail below with reference to the accompanying drawings and specific implementation manners.

[0021] In an exemplary embodiment, as Figure 1 shown, a method for optimizing pumping unit parameters is provided. This method is executed by a computer device, and specifically, it can be executed alone by a computer device such as a terminal or a server, or jointly executed by a terminal and a server. In the embodiments of the present application, the method includes the following steps.

[0022] Step 101: At each iteration step, the stroke phase signal, pressure data, and sucker rod string load are obtained in real time.

[0023] Step 102: Determine the stroke stage according to the stroke phase signal; the stroke stage includes the upstroke stage and the downstroke stage.

[0024] Step 103: When the stroke stage is the upstroke stage, adjust the acceleration of the linear motor according to the sucker rod string load and the fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and obtain the optimal parameters for the upstroke.

[0025] Step 104: When the stroke stage is the downstroke stage, adjust the running speed of the linear motor according to the pressure data and the pressure fluctuation rate threshold to obtain the pressure fluctuation amplitude and the optimal parameters for the downstroke.

[0026] Step 105: Adjust the iteration step according to the pressure fluctuation amplitude by using Fourier transform.

[0027] Determine the stroke stage of the pumping unit based on the real-time acquired stroke phase signal and the pressure data, dynamically adjust the linear motor, achieve refined control, while ensuring stable liquid production, significantly reduce energy waste and equipment wear, thus solving the problems of low pump efficiency, rod-tubing eccentric wear and energy consumption waste.

[0028] In an exemplary embodiment, determining the stroke stage according to the stroke phase signal specifically includes: Determine the first-order difference according to the stroke phase signal; if the first-order difference is positive, the stroke stage is the upstroke stage; if the first-order difference is negative, the stroke stage is the downstroke stage.

[0029] In practical applications, judge the stroke stage according to the stroke phase signal collected by the Hall displacement sensor and the real-time pressure data of the pressure transmitter. Calculate the first-order difference v(t) through the displacement x(t), with upward being positive and downward being negative. At the same time, when the upstroke starts, the traveling valve closes and the fixed valve opens, and the liquid in the tubing is sucked, resulting in an instantaneous drop in pressure, and the pressure gradient dP / dt < 0.

[0030] In an exemplary embodiment, when the stroke stage is the upstroke stage, adjust the acceleration of the linear motor according to the load of the sucker rod string and the fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and obtain the optimal parameters for the upstroke, specifically including: When the stroke stage is the upstroke stage, use the fuzzy PID control algorithm to adjust the acceleration of the linear motor according to the load of the sucker rod string and the fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and obtain the optimal parameters for the upstroke; the optimal parameters for the upstroke are specifically the optimal stroke frequency value for the upstroke.

[0031] In practical applications, when the fluid viscosity is high, the flow resistance in the tubing increases, and the acceleration needs to be increased to shorten the liquid discharge time; when the rod string load is large and the mechanical load is too high, the acceleration needs to be reduced to avoid overload. Use the PID parameters for dynamic adjustment, fit the compensation factor f(μ, F) according to the on-site data, a(t) = K p ×e(t) + K i ×∫e(t)dt + K d ×de(t) / dt + f(μ, F)×a0, where a0 is the initial acceleration, a(t) is the acceleration, e(t) is the displacement error, the displacement error = target displacement - actual displacement, K p 、K i 、K d are the three parameters of the PID controller, which are the proportional regulation coefficient, integral regulation coefficient, and differential regulation coefficient respectively. μ is the fluid viscosity parameter in the tubing, and F is the load of the sucker rod string. Based on a large amount of on-site data, the empirical formula f(μ, F) = 1 + 0.12ln(μ) - 0.08F is obtained by using the regression analysis method.level +0.05T vis , F level is the grading index of the rod string load. When F < 30 kN, F level = 1. When 30 kN ≤ F < 60 kN, F level = 2. When F ≥ 60 kN, F level = 3; T vis is the viscosity-temperature correction coefficient. When the fluid temperature is 30 °C, T vis = 0. For every 10 °C increase, T vis increases by 0.01.

[0032] In an exemplary embodiment, when the stroke stage is the downward stroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure volatility threshold to obtain the pressure fluctuation amplitude and the optimal parameters for the downward stroke, specifically including: When the stroke stage is the downward stroke stage, the operating speed of the linear motor is adjusted according to the pressure data and the pressure volatility threshold by using the anti-water hammer optimization algorithm to obtain the pressure fluctuation amplitude; Determine the pressure volatility according to the pressure data; when the pressure volatility is equal to the pressure volatility threshold, obtain the optimal parameters for the downward stroke; the optimal parameters for the downward stroke are specifically the optimal stroke frequency value for the downward stroke.

[0033] In an exemplary embodiment, the iteration step size is adjusted according to the pressure fluctuation amplitude by using Fourier transform, specifically including: Determine the vibration frequency characteristics according to the pressure fluctuation amplitude by using Fourier transform; Determine the spectral distortion degree according to the vibration frequency characteristics; Dynamically adjust the iteration step size according to the spectral distortion degree.

[0034] In practical applications, the distortion degree = (||the current spectrum obtained by Fourier transform - the reference spectrum recorded during normal operation of the device||) / (||the reference spectrum recorded during normal operation of the device||) × 100%. When the distortion degree < 10%, the step size ∆f is 0 and no adjustment is required. When 10% ≤ the distortion degree < 20%, the step size ∆f is 1.0 Hz. When the distortion degree ≥ 20, the step size ∆f is 1.5 Hz.

[0035] In an exemplary embodiment, after adjusting the iteration step size according to the pressure fluctuation amplitude by using Fourier transform, it further includes: whenever the iteration step size reaches the set value, store the optimal parameters for the upward stroke, the optimal parameters for the downward stroke, and the corresponding pump diameter in the database.

[0036] The pumping unit parameter optimization method provided by this application is applicable to the dynamic optimization of the pumping unit stroke frequency parameters in the construction of digital oilfields, aiming to solve the problems that the traditional fixed stroke frequency mode is difficult to adapt to the dynamic underground liquid supply capacity and complex working conditions, which easily leads to low pump efficiency, rod-tube eccentric wear and energy consumption waste. Compared with the prior art, this application independently optimizes the stroke frequency parameters by sub-strokes, specifically the optimal stroke frequency value for the upstroke and the optimal stroke frequency value for the downstroke, which can significantly improve the comprehensive performance of the pumping unit system under actual working conditions, dynamically adapt to the differential load characteristics of the upstroke and downstroke. Compared with the traditional fixed stroke frequency mode, this application can reduce energy consumption waste, extend the service life of components, has good working condition adaptability, and realizes stable and efficient operation.

[0037] This application also provides a specific implementation method of the pumping unit parameter optimization method in actual application, including the following steps: After assembling the experimental device, import the preset optimization algorithm (such as the fuzzy PID parameter table) through the program panel; Start the liquid supply system and set the target formation pressure (such as 5 MPa); The PLC collects displacement, load, and pressure data in real time and calculates the stroke frequency deviation value; Among them, the stroke frequency deviation value Δf stroke is equal to the target stroke frequency f target - the actual stroke frequency f real (in the unit of Hz), and the expression is Δf stroke =f target −f real , f real =1 / ∆t, . SPM is the stroke frequency, and ∆t is the time difference between the starting points of two adjacent upstrokes.

[0038] In actual application, before determining the stroke stage, first judge the stroke frequency deviation value. When the stroke frequency deviation value is positive, it indicates that the actual stroke frequency is too high, and the stroke frequency should be reduced to avoid overload or equipment wear; when the stroke frequency deviation value is negative, it indicates that the actual stroke frequency is insufficient, and the stroke frequency should be increased to compensate for the load fluctuation, f new = f targe +K×Δf stroke， K is the proportionality coefficient, which is set according to the equipment characteristics. When the stroke frequency deviation value is 0, judge the stroke stage.

[0039] Upstroke stage: If it is detected that the pump efficiency drops (flow rate < 80% of the pump efficiency threshold), the fuzzy PID automatically increases the acceleration to optimize the filling coefficient; the pump efficiency is the filling coefficient.

[0040] Among them, the filling coefficient η = (actual displacement V actual / theoretical displacement V theoretical ) × 100%, V theoretical= (πD 2 × S × n) / 4. V actual can be measured by a flowmeter. D is the diameter of the piston of the sucker rod pump, S is the length of a single stroke, and n is the stroke frequency, that is, the number of reciprocating motions per second.

[0041] Downstroke stage: If the pressure volatility > the pressure volatility threshold, immediately reduce the motor speed to the safe range (such as 0.5 m / s²); the pressure volatility is the rate of change of pressure per unit time, and the pressure volatility = (current pressure - pressure at the previous moment) / sampling time interval; the pressure fluctuation amplitude refers to the maximum change range of pressure within one cycle, that is, the difference between the lowest pressure and the highest pressure. The pressure volatility reflects the dynamic rate of pressure change, and the pressure fluctuation amplitude reflects the static range of pressure change.

[0042] Iterative optimization: Every time 10 stroke cycles are completed, the system updates the optimal parameters to the database according to historical data. Among them, the optimal parameters include K p 、K i 、K d 、SPM、a(t).

[0043] Through the independent optimization technology for each stroke, this application can significantly improve the comprehensive operation efficiency and equipment reliability of the sucker rod pump system. In the traditional mode, the stroke frequencies of the upstroke and downstroke are the same. In this application, with independent optimization for each stroke, the stroke frequency of the upstroke is fast, reducing the leakage volume, and the stroke frequency of the downstroke is slow, reducing the number of frictions and minimizing eccentric wear and improving the pump efficiency. By intelligently perceiving the real-time working condition changes of the upstroke and downstroke and dynamically adjusting the stroke frequency parameters, this application can greatly reduce energy waste and equipment loss while ensuring stable liquid production. Compared with the traditional control method, it can automatically optimize the operation rhythm according to dynamic conditions such as downhole pressure and rod string load, avoiding both mechanical impacts caused by too fast stroke frequencies and the problem of low efficiency caused by too slow stroke frequencies. 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 faults such as pump jamming and eccentric wear, extend the pump inspection period, and reduce the maintenance cost.

[0044] Based on the same inventive concept, the embodiment of this application also provides a sucker rod pump device for implementing the sucker rod pump parameter optimization method involved above. The solution provided by this device to solve the problem is similar to the solution recorded in the above method. Therefore, the specific limitations in one or more embodiments of the sucker rod pump device provided below can refer to the limitations on the sucker rod pump parameter optimization method in the above text, and will not be repeated here.

[0045] In an exemplary embodiment, such as Figure 2As shown in the figure, a pumping unit is provided, which includes a pumping unit system 100, a liquid 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. The pumping unit system 100 is used to send the obtained 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 phase signal, pressure data, and sucker rod string load in the stroke stage.

[0046] In practical applications, the intelligent control system 400 sends 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 the parameters.

[0047] As a preferred structure, the pumping unit system 100 includes a casing 1, a tubing 2, a sucker rod 3, and a sucker rod pump 4. The sucker rod pump 4 can be replaced to study the influence under different pump diameters. A modular pump barrel assembly that can be quickly replaced, including different pump diameter specifications (from Φ28mm to Φ95mm). The tail end of the casing is connected to the liquid supply system through a pipeline.

[0048] Similarly, the liquid supply system 200 consists of a hydraulic servo liquid supply end 5 and a precision slide rail 6. The height of the hydraulic servo liquid supply end is adjustable and is controlled by the precision slide rail. It can be used to simulate the formation pressure on the supply side and can simulate the formation pressure of 0.5 - 15 MPa, with a pressure adjustment resolution of 0.1 MPa.

[0049] 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 the intelligent control system 400, and then drives the pumping unit system 100. The cable 7 is a submersible oil - tight cable with longitudinal oil - tight characteristics.

[0050] 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 sub - stroke optimization algorithm module, which can optimize the stroke parameters of the up - stroke and down - stroke respectively according to different programs, and the up - stroke and down - stroke are variable. It realizes differential stroke control of the up - stroke and down - stroke, and the up - stroke and down - stroke are variable.

[0051] The pumping unit further includes a base 11, and the pumping unit system 100, the liquid supply system 200, the linear motor system 300, and the intelligent control system 400 are all arranged on the base 11.

[0052] Its control principle is as follows: The stroke phase signal is collected in real time by the Hall displacement sensor installed at the end of the sucker rod 3, and at the same time, the real-time pressure data of the pressure transmitter (range 0 - 20 MPa, accuracy 0.5% FS) of the liquid supply system 200 is received. When the start of 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 fluid viscosity parameter in the tubing 2 and the current rod string load, so that the upstroke frequency is adaptively adjusted within the range of 0.5 - 8 strokes per minute; in the downstroke stage, the anti - water hammer optimization algorithm is enabled. By monitoring the pressure volatility at the end of the casing 1, when the pressure fluctuation amplitude exceeds the set threshold (default 5 MPa / s), the motor operating 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 spectrum distortion degree.

[0053] The linear motor 8 is connected to the PLC through a variable - frequency driver. The PWM control signal output by the PLC is optically isolated and then drives the IGBT power module to achieve precise control of the motor thrust within the range of ±7 kN. The program panel 10 has an optimized database of stroke parameters, which contains the optimal stroke frequency combination parameters corresponding to different pump diameters (from Φ28 mm to Φ95 mm). When the oil pump 4 is replaced, the system automatically identifies the pump barrel RFID tag and loads the corresponding control parameter group.

[0054] In an exemplary embodiment, a computer device is provided. The computer device can be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O), and a communication interface. Among them, the processor, the memory, and the input / output interface are connected through the system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non - volatile storage medium and an 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 the computer program in the non - volatile storage medium. The database of the computer device is used to store the optimized data of the pumping unit parameters. The input / output 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 through a network connection. The computer program, when executed by the processor, implements a method for optimizing the parameters of a pumping unit.

[0055] Those skilled in the art can understand that the structures shown in this application are merely block diagrams of some structures related to the solution of this application, and do not constitute a limitation on the computer devices to which the solution of this application is applied. The specific computer devices may include more or fewer components than those shown in the figures, or combine some components, or have different component arrangements. In an exemplary embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory, and when the processor executes the computer program, the above-mentioned method embodiments are implemented.

[0056] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the above-mentioned method embodiments are implemented.

[0057] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above-mentioned method embodiments are implemented.

[0058] 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 for analysis, stored data, displayed data, etc.) involved in this application are all information and data that have been authorized by the user or fully authorized by all parties, and the collection, use, and processing of relevant data need to comply with relevant regulations.

[0059] In this application, all actions of obtaining signals, information, or data are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where the location is located and obtaining the authorization given by the owner of the corresponding device.

[0060] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing 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 embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memories. 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), magnetoresistive 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 can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0061] The databases involved in the embodiments provided in this application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in this application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logics, data processing logics based on quantum computing, etc., without limitation.

[0062] The technical features of the above embodiments can be combined arbitrarily. For the sake of concise description, 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, it should be considered to be within the scope described in this specification.

[0063] In this article, specific examples are used to elaborate on the principles and implementation manners of this application. The description of the above embodiments is only used to help understand the method and its core idea of this application; at the same time, for those of ordinary skill in the art, according to the idea of this application, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to this application.

Claims

1. A method for optimizing the parameters of a pumping unit, characterized in that, The parameter optimization method for the pumping unit includes: At each iteration step, the stroke phase signal, pressure data, and the load of the sucker rod string are acquired in real time; The stroke stage is determined according to the stroke phase signal; the stroke stage includes the upstroke stage and the downstroke stage; When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the load of the sucker rod string and the fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and the optimal parameters for the upstroke are obtained; 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 volatility threshold, and the pressure fluctuation amplitude and the optimal parameters for the downstroke are obtained; The iteration step is adjusted according to the pressure fluctuation amplitude by using Fourier transform.

2. The method for optimizing the parameters of the pumping unit according to claim 1, wherein Determining the stroke stage according to the stroke phase signal specifically includes: Determining the first-order difference according to the stroke phase signal; If the first-order difference is positive, the stroke stage is the upstroke stage; If the first-order difference is negative, the stroke stage is the downstroke stage.

3. The pumping unit parameter optimization method according to claim 1, wherein, When the stroke stage is the upstroke stage, adjusting the acceleration of the linear motor according to the load of the sucker rod string and the fluid viscosity parameter in the tubing until the pump efficiency reaches the pump efficiency threshold, and obtaining the optimal parameters for the upstroke, specifically includes: When the stroke stage is the upstroke stage, the acceleration of the linear motor is adjusted according to the load of the sucker rod string and the fluid viscosity parameter in the tubing by using the fuzzy PID control algorithm until the pump efficiency reaches the pump efficiency threshold, and the optimal parameters for the upstroke are obtained.

4. The pumping unit parameter optimization method according to claim 1, wherein When the stroke stage is the downstroke stage, adjusting the operating speed of the linear motor according to the pressure data and the pressure volatility threshold, and obtaining the pressure fluctuation amplitude and the optimal parameters for the downstroke, specifically includes: 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 volatility threshold by using the anti-water hammer optimization algorithm to obtain the pressure fluctuation amplitude; The pressure volatility is determined according to the pressure data; when the pressure volatility is equal to the pressure volatility threshold, the optimal parameters for the downstroke are obtained.

5. The pumping unit parameter optimization method according to claim 1, wherein Adjusting the iteration step according to the pressure fluctuation amplitude by using Fourier transform specifically includes: Determining the vibration frequency characteristics according to the pressure fluctuation amplitude by using Fourier transform; Determining the spectral distortion degree according to the vibration frequency characteristics; Dynamically adjusting the iteration step according to the spectral distortion degree.

6. The pumping unit parameter optimization method according to claim 1, characterized in that, After adjusting the iteration step according to the pressure fluctuation amplitude by using Fourier transform, it further includes: Whenever the iteration step reaches the set value, the optimal parameters for the upstroke, the optimal parameters for the downstroke, and the corresponding pump diameter are stored in the database.

7. A pumping unit, characterized in that, The pumping unit device includes: a pumping unit system, a liquid supply system, a linear motor system, and an intelligent control system; the intelligent control system applies the pumping unit parameter optimization method according to any one of claims 1-6; The pumping unit system is used to send the acquired stroke phase signal, pressure data, and the load of the sucker rod string 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 phase signal, pressure data, and the load of the sucker rod string according to the stroke stage.

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

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the pumping unit parameter optimization method according to any one of claims 1-6.

10. A computer program product comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the pumping unit parameter optimization method according to any one of claims 1-6.

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