Pumping unit stroke parameter optimization method based on pumping unit motor feedback parameters

Abstract

The invention discloses a pumping unit stroke parameter optimization method based on pumping unit motor feedback parameters, and belongs to the technical field of oil wells. The optimization method comprises the following steps: S1, acquiring an electric parameter fed back by a motor of the oil pumping unit; s2, establishing an electric parameter-torque-suspension center load mathematical model according to the obtained electric parameters; s3, drawing a multi-parameter curve chart according to the mathematical model and a numerical integration method, feeding back the current pump submergence degree in real time according to the multi-parameter curve chart, dynamically optimizing at least one parameter of the operation stroke frequency and the stroke speed of the oil pumping unit; according to the method, the degree of dependence on the indicator and the sensor is reduced, the defects caused by dependence on the indicator are avoided, the sensing data error is reduced, the pump submergence degree can be monitored in real time, and then independent dynamic optimization of the stroke frequency, the upstroke speed and the downstroke speed of the pumping unit is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of oil wells, and particularly relates to a method for optimizing the stroke parameters of a pumping unit based on the feedback parameters of the pumping unit motor. Background Art

[0002] Currently, in the field of oil well technology, the dynamometer is generally relied on. The dynamometer is used as the core tool for diagnosing oil well production, mainly for collecting and analyzing the load-displacement change curve (i.e., the dynamometer card) of the polished rod of the pumping unit, so as to evaluate the working state of the downhole pump, diagnose faults, and optimize production parameters such as the pumping speed and speed of the pumping unit. However, the collection of dynamometer data mainly relies on load sensors and displacement sensors. On the one hand, this increases the usage cost of the sensors. On the other hand, the configuration operations such as upgrading and debugging of the dynamometer need to be carried out after the well is shut down, which not only causes the interruption of oil well production, affects the crude oil output, but also may increase the mechanical loss due to frequent start-stop of the equipment and reduce the production efficiency.

[0003] Based on the above analysis, the present application designs a method for optimizing the stroke parameters of a pumping unit based on the feedback parameters of the pumping unit motor. Summary of the Invention

[0004] The object of the present invention is to provide a method for optimizing the stroke parameters of a pumping unit based on the feedback parameters of the pumping unit motor. This method uses the electrical parameters feedback by the pumping unit motor to draw a multi-parameter curve graph, and determines the current pump immersion depth according to the multi-parameter curve graph, and then dynamically optimizes at least one of the pumping speed and the stroke speed of the pumping unit that is fast up and slow down, so as to achieve the purpose of improving the pump efficiency and achieving supply-demand balance, and reducing the dependence on the dynamometer and sensing data.

[0005] To solve the above problems, the present application provides a method for optimizing the stroke parameters of a pumping unit based on the feedback parameters of the pumping unit motor, which includes the following steps: Step S1: Obtain the electrical parameters feedback by the pumping unit motor, and the electrical parameters at least include current, voltage and frequency; Step S2: Establish a mathematical model of electrical parameter - torque - polished rod load according to the obtained electrical parameters; Step S3: Draw a multi-parameter curve graph according to the mathematical model and the numerical integration method. The parameters of the vertical coordinate of the multi-parameter curve graph at least include load and current, and the parameter of the horizontal coordinate includes displacement. And according to the multi-parameter curve graph, the current pump immersion depth is fed back in real time, and then at least one of the pumping speed and the stroke speed of the pumping unit is dynamically optimized.

[0006] As a preferred solution of the present application: In step S2, the specific steps of establishing a mathematical model of electrical parameter - torque - polished rod load according to the obtained electrical parameters include: Step S21: Establish a calculation model for the output torque of the pumping unit motor : Among them, is the active power of the motor, is the motor conversion efficiency, is the power factor, is the voltage in the electrical parameters, is the current in the electrical parameters; is the motor speed, is the number of pole pairs of the motor, is the frequency in the electrical parameters; Step S22: Establish a calculation model for the polished rod load of the pumping unit : Among them, is the motor transmission efficiency, is the crank radius of the four-bar mechanism of the pumping unit, is the length of the front arm of the walking beam of the pumping unit, is the crank angle of the four-bar mechanism of the pumping unit; Step S23: Establish a calculation model for the polished rod displacement : Among them, is the crank radius of the four-bar mechanism of the pumping unit, is the length of the front arm of the walking beam of the pumping unit, is the crank angle of the four-bar mechanism of the pumping unit.

[0007] As a preferred solution of the present application: In step S3, the specific method for real-time monitoring of the pump immersion depth according to the multi-parameter curve graph includes: Determine the current pump immersion depth according to the curve shape of at least one of the load-displacement curve and the current-displacement curve in the multi-parameter curve graph, and then mainly optimize the stroke parameters by dynamically adjusting the pumping speed to a reasonable range, and supplemented by dynamically adjusting the stroke speed of fast up and slow down to a reasonable range.

[0008] As a preferred solution of the present application: The specific method for determining the current pump immersion depth according to the curve shape of at least one of the load-displacement curve and the current-displacement curve in the multi-parameter curve graph includes: When using the load-displacement curve, determine whether the load-displacement curve graph is a complete parallelogram. If not, determine the abnormal curve deformation rate, and then determine the current pump immersion depth level according to the preset relationship between the curve deformation rate and the pump immersion depth; When using the current-displacement curve, determine the current peak oscillation volatility of the current-displacement curve within one cycle, and then determine the current pump immersion depth level according to the preset relationship between the current peak oscillation volatility and the pump immersion depth.

[0009] As a preferred solution of the present application: Adopt a combined method of the load-displacement curve and the current-displacement curve to judge the current immersion depth state, where Qualitatively judge the pump immersion depth through the load-displacement curve, and verify and quantify the level of the pump immersion depth through the current-displacement curve.

[0010] As a preferred solution of the present application: In step S3, the numerical integration method includes at least one of the trapezoidal rule, Simpson's rule, and Romberg integration.

[0011] Compared with the prior art, the beneficial effects of the present invention are as follows: This stroke parameter optimization method in this solution uses the electrical parameters fed back by the pumping unit motor to draw a multi-parameter curve graph, and determines the current pump immersion depth according to the multi-parameter curve graph, and then dynamically optimizes (regulates) at least one of the stroke frequency and the stroke speed with fast up and slow down of the pumping unit; that is, this method uses electrical parameters such as current, voltage, and frequency fed back by the pumping unit motor as basic monitoring data, and uses the numerical integration method to draw a multi-parameter curve graph with this basic monitoring data, and uses this multi-parameter curve graph to replace the traditional indicator diagram to optimize production parameters such as the stroke frequency and speed of the pumping unit. In this way, on the one hand, the dependence on the indicator instrument and sensors is reduced, the disadvantages of relying on the indicator instrument are avoided, and various errors brought by the sensors are eliminated. On the other hand, real-time monitoring of the pump immersion depth is realized, and then independent dynamic regulation of the stroke frequency, up-stroke speed, and down-stroke speed of the pumping unit is realized, achieving the purpose of improving the pump efficiency and supply-demand balance. At the same time, ensure that the speeds of the up and down strokes meet the requirements of fast up and slow down. Description of the Drawings

[0012] Figure 1 It is a flow chart of the pumping unit stroke parameter optimization method based on the parameters fed back by the pumping unit motor provided by the embodiment of the present invention.

[0013] Figure 2The multi-parameter curve graph provided by the embodiment of the present invention. Detailed implementation manners

[0014] The present invention will be further described in detail below in conjunction with the detailed implementation manners and with reference to the accompanying drawings. It should be emphasized that the following description is merely exemplary and is not intended to limit the scope and its applications of the present invention.

[0015] Example 1: As Figure 1 shown, a flow chart of an optimization method for the stroke parameters of a pumping unit based on the feedback parameters of the pumping unit motor is provided for this embodiment. The method specifically includes the following steps: Step S1: Obtain the electrical parameters feedback by the pumping unit motor; In this step, the electrical parameters are obtained at a certain frequency. The obtained electrical parameters mainly include the current I, voltage U, and frequency f feedback by the motor. Specifically, in this embodiment, the Nyquist criterion is used to sample the electrical parameters (the sampling frequency is twice the highest frequency of the signal, specifically 100 ms) to ensure that the signal does not aliase during the sampling process. At the same time, the integrity and accuracy of the signal are ensured.

[0016] Step S2: Establish a mathematical model of electrical parameters - torque - polished rod load; This step is used to associate the electrical parameters with the polished rod load and provide a basis for subsequent optimization of the stroke parameters. The specific steps for establishing the mathematical model include: Step S21: Establish a calculation model for the output torque of the pumping unit motor: Among them, is the active power of the motor: is the motor conversion efficiency, is the power factor, is the voltage in the electrical parameters feedback by the motor, is the current in the electrical parameters feedback by the motor; is the motor speed: is the number of pole pairs of the motor, is the frequency in the electrical parameters feedback by the motor; According to the above model, it can be seen that the motor torque is proportional to the active power of the motor and is proportional to the motor speed is inversely proportional. Therefore, according to the acquired electrical parameter current , voltage and frequency the output torque of the motor can be calculated ; Step S22: Establish a calculation model for the polished rod load of the pumping unit : Among them, is the motor transmission efficiency, is the crank radius of the four-bar mechanism of the pumping unit, is the length of the front arm of the walking beam of the pumping unit, is the crank angle of the four-bar mechanism of the pumping unit; According to the above model, it can be known that the polished rod load of the pumping unit is related to the motion model of the four-bar mechanism of the pumping unit and the motor torque . Through the establishment of the above model, the electrical parameters can be effectively associated with the polished rod load, and then the changes in the electrical parameters can be reflected through the polished rod load. That is, the establishment of this model in this embodiment enables the acquisition of polished rod load data without relying on load sensors and dynamometers, reducing the dependence on sensing data; Step S23: Establish a calculation model for the polished rod displacement : Among them, is the crank radius of the four-bar mechanism of the pumping unit, is the length of the front arm of the walking beam of the pumping unit, is the crank angle of the four-bar mechanism of the pumping unit; According to the above model, it can be known that the polished rod displacement mainly depends on the motion model of the four-bar mechanism of the pumping unit. In the motion model of the four-bar mechanism, the parameters and are fixed values, is a variable, which can be directly obtained through an encoder set on the crank or indirectly calculated through the motor speed and reduction ratio; By calculating the polished rod displacement, the current stroke stage of the polished rod can be determined, and then combined with the polished rod load or current data, the pump efficiency of the pumping unit can be judged and optimized. It can be understood that the changes in the load or current at different stroke stages can directly reflect the state of the pump fullness, and the changes in the pump fullness state can reflect the changes in the pump immersion depth.

[0017] Step S3: Draw a multi-parameter curve graph according to the mathematical model and the numerical integration method. The parameters on the vertical coordinate of the multi-parameter curve graph include at least load and current, and the parameters on the horizontal coordinate include displacement. Determine or feedback the current pump immersion depth in real time according to the multi-parameter curve graph, and then select an appropriate stroke parameter optimization strategy according to the current pump immersion depth to dynamically optimize at least one of the running strokes and stroke speed of the pumping unit.

[0018] Specifically, convert the electrical parameters into load F and power P through the mathematical model established in step S2, calculate and obtain the polished rod displacement S through the data parameters of the four-bar mechanism of the pumping unit, then use at least one numerical integration rule among the trapezoidal rule, Simpson's rule, and Romberg integration to obtain continuous data, and finally draw a multi-parameter curve according to the obtained continuous data. As Figure 2 shown, it is a multi-parameter curve graph (also called a dynamometer card) drawn by the system when this solution is applied to the pumping well with well number 4604 in this embodiment. In this parameter curve graph, the vertical coordinate includes load (kM), current (A), and power (kW), and the horizontal coordinate is displacement (M). That is, in this curve graph, it includes a load-displacement curve graph, a current-displacement curve graph, and a power-displacement curve graph. Among them, the load-displacement curve graph and the current-displacement curve can replace the traditional dynamometer card. Determine the current pump immersion depth according to at least one of the curve shapes of the load-displacement curve or the current-displacement curve in the multi-parameter curve graph. That is, realize the visualization of faults through the load-displacement curve or the current-displacement curve, and then realize the feedback and determination of the pump immersion depth. In this embodiment, the power-displacement curve is mainly used to display the real-time power consumption of the pumping unit, and it is not used as the basis for monitoring the pump immersion depth in this embodiment for the time being.

[0019] In this embodiment, the specific method for determining the current pump immersion depth according to at least one of the curve shapes of the load-displacement curve and the current-displacement curve in the multi-parameter curve graph includes: judge the change of the curve shape by comparing the curve drawn based on the electrical parameters with the preset normal curve, and then determine the current pump immersion depth according to the change of the curve shape. In this embodiment, the deformation state of the multi-parameter curve usually directly reflects the dynamic liquid level depth (DFL) of the oil well, and the pump immersion depth can be deduced through the relationship between the pump immersion depth, the dynamic liquid level height, and the pump setting depth. Specifically, the pump immersion depth (S) = pump setting depth (H) - dynamic liquid level depth (DFL).

[0020] When using the load-displacement curve, the normal load-displacement curve is a parallelogram. Judge whether the load-displacement curve graph is a complete parallelogram. If not, judge the deformation rate of the abnormal curve (it can be understood that this deformation rate can be calculated by comparing with the normal curve). This abnormal curve usually includes two situations: the lower part of the curve is missing or deformed, and the top of the curve is smooth or the area is reduced. According to the structure of the dynamometer card, as Figure 2As shown, the lower part of the curve is the section near the horizontal axis. This curve section reflects the change in load from the end of the downward stroke to the beginning of the upward stroke. If there is a missing or deformed part, it indicates that the pump immersion depth is insufficient (less than 50 m), resulting in the inability to establish the normal load during the downward stroke. The top curve is the curve section on the side far from the horizontal axis. This curve section reflects the load state of the plunger lifting the liquid in the later stage of the upward stroke. If there is an arc at the top of the curve or the enclosed area of the curve decreases, it indicates the presence of gas locking (the immersion depth is relatively low, less than 100 m), which further leads to a decrease in load and insufficient lifting force. Finally, the current pump immersion depth level is determined according to the relationship between the preset curve deformation rate and the pump immersion depth. It can be understood that the relationship between the curve deformation rate and the pump immersion depth needs to be determined through multiple experiments or existing experience. In this embodiment, the abnormal levels of the pump immersion depth usually include three levels, namely, less than 50 m for the first level, between 50 - 100 m for the second level, and greater than 200 m for the third level. This embodiment only applies to the first two levels. For the third level, more cautious adjustment is required. It can be understood that different pump immersion depth levels determine different optimization strategies for the running stroke frequency and stroke speed of the pumping unit. In this embodiment, it is preferred that after determining the pump immersion depth or the immersion depth level, existing traditional optimization or adjustment strategies can be used for optimization.

[0021] When using the current-displacement curve, mainly observe the fluctuation degree of the current curve. Specifically, judge the current peak oscillation volatility of the current-displacement curve within one cycle, and then determine the current pump immersion depth level according to the relationship between the preset current peak oscillation volatility and the pump immersion depth. It can be understood that the current peak oscillation volatility can be calculated by comparing with the normal current curve, and the relationship between the current peak oscillation volatility and the pump immersion depth can be formulated based on multiple experiments or existing experience. In this embodiment, it is preferred that when the obtained current peak oscillation volatility is between 15% - 20%, the corresponding pump immersion depth level is the second level, that is, the pump immersion depth is between 50 - 100 m. When the obtained current peak oscillation volatility is between 20% - 40%, the corresponding pump immersion depth level is the first level, that is, the pump immersion depth is less than 50 m. Finally, select a suitable optimization strategy to adjust or optimize the stroke frequency and stroke speed according to the determined immersion depth level. In this embodiment, the preferred optimization strategy can be an existing traditional debugging strategy.

[0022] Specifically, in the current-displacement curve, such as Figure 2As shown, within one cycle under normal conditions, the curve from the starting lowest point to the highest point is the upstroke stage, which is the lifting stage after loading. Therefore, the current gradually increases, generally with a relatively stable change. When the curve falls from the highest point back to the lowest point, it is the downstroke stage, which is the liquid suction stage. Therefore, the change in the current amplitude is sometimes large, and there are spikes or mutations in some cases. It can be seen that the change in the current directly reflects the smoothness of the load, and the smoothness of the load in turn reflects the state of the pump immersion depth. For example, in the upstroke stage, when the peak oscillation amplitude of the current curve changes significantly (the current peak oscillation volatility is greater than 15%), it indicates insufficient liquid suction, a low fullness degree of the pump, and a smaller torque required for lifting, which then leads to a sudden decrease in the current. In the downstroke stage, when the peak oscillation amplitude of the current curve changes significantly, it indicates that the pump barrel is not filled with liquid due to the immersion depth, and then the work done by the plunger on the liquid decreases, resulting in a decrease in the current. Therefore, according to the current peak oscillation volatility reflected by the current-displacement curve, the pump immersion depth level can be obtained intuitively and relatively accurately, providing more precise conditions for subsequent stroke parameter optimization.

[0023] In this embodiment, it is preferably to use a combination of load-displacement curve and current-displacement curve to judge the current immersion depth state. Among them, the pump immersion depth is qualitatively judged through the load-displacement curve, that is, first, it is judged whether there is a problem of abnormal pump immersion depth (whether it is evacuated / air locked) through the load-displacement curve, and then the level of the pump immersion depth is verified and quantified through the current-displacement curve. For example, whether the pump immersion depth is less than 50m, or between 50 - 100m. Then, at least one of the stroke frequency and the stroke speed is dynamically optimized according to the judgment result. Specifically, mainly dynamically adjust the stroke frequency to a reasonable range, and supplemented by dynamically adjusting the up-fast and down-slow stroke speed to a reasonable range for stroke parameter optimization. That is, first adjust the stroke frequency according to the pump immersion depth, and then adjust the upstroke speed or the downstroke speed as needed to ensure that the requirement of up-fast and down-slow is met.

[0024] In this embodiment, after speed regulation, ensure that the upstroke speed does not exceed the maximum allowable acceleration of the equipment (to avoid exceeding the inertial load limit), and the downstroke speed needs to ensure that the motor does not stall (the minimum frequency is usually ≥30Hz); in addition, it is preferably to review the pump immersion depth every 24 hours to avoid over-adjustment.

[0025] The following is an explanation of the effect of applying the optimization method of this embodiment to an actual oil well and combining with the existing optimization strategy to adjust the operating parameters of the pumping unit: For example, when it is determined that the pump immersion depth is at level two, that is, it is deduced that the immersion depth drops from 150m to 80m (insufficient liquid supply), and the original parameters are: the stroke frequency is 6 times per minute, and the upstroke and downstroke speeds are 55Hz and 50Hz respectively. The adjustment steps include: First, reduce the stroke frequency: from 6 to 4 times per minute (a reduction of 33%); Then adjust the speed: During the upstroke: increase the speed from 55 Hz to 65 Hz (a 20% increase); During the downstroke: decrease the speed from 50 Hz to 35 Hz (a 30% decrease); Verify the effect: After parameter optimization, in the multi-parameter curve graph, the load-displacement curve tends to be a parallelogram, indicating that the pump fullness has been improved (the lower part is fully filled). At the same time, the current-displacement curve tends to be stable, and the current fluctuation is reduced by 10%.

[0026] At the same time, the following is a comparison table of the effects before and after the application of the above optimization method provided in this embodiment in different oil wells: In summary, it can be seen from the above analysis that the stroke parameter optimization method of this solution uses the electrical parameters fed back by the pumping unit motor as the basic monitoring data, without the need to rely on sensors such as load and displacement. It uses the electrical parameters to draw a multi-parameter curve graph, and determines the current pump immersion depth according to the multi-parameter curve graph (first determine the dynamic liquid level depth, and then calculate the pump immersion depth based on the dynamic liquid level depth), and then dynamically adjusts and optimizes at least one of the pumping unit's stroke frequency and the stroke speed with a faster upstroke and a slower downstroke; that is, this method uses electrical parameters such as current, voltage, and frequency fed back by the pumping unit motor as the basic monitoring data, and uses this basic monitoring data to draw a multi-parameter curve graph, and uses this multi-parameter curve graph to replace the traditional indicator diagram to optimize production parameters such as the pumping unit's stroke frequency and speed. In this way, not only the dependence on the dynamometer is reduced, the disadvantages of relying on the dynamometer are avoided, but also the real-time monitoring of the pump immersion depth can be realized, and then the independent dynamic control of the pumping unit's stroke frequency, upstroke speed, and downstroke speed can be achieved, realizing the purpose of improving the pump efficiency and achieving supply and production balance. At the same time, the power consumption of the pumping unit system is also significantly reduced.

[0027] The above are only embodiments of the present invention, and common general knowledge such as specific structures and characteristics in the solution is not described in detail here. It should be pointed out that for those skilled in the art, several improvements can be made without departing from the present invention, and these should also be regarded as the protection scope of the present invention, which will not affect the implementation effect of the present invention and the practicality of the patent. The protection scope required by this application should be subject to the content of the claims, and the specific implementation manners described in the specification can be used to explain the content of the claims.

Claims

1. A method for optimizing the stroke parameters of an oil pump based on the feedback parameters of an oil pump motor, characterized in that: The following steps are involved: Step S1: obtaining electrical parameters fed back by the motor of the oil pump, wherein the electrical parameters at least include current, voltage and frequency; Step S2: establishing a mathematical model of electrical parameter-torque-suspension point load according to the acquired electrical parameters; Step S3: Draw a multi-parameter curve graph according to the mathematical model and the numerical integration method, wherein the parameters of the vertical axis of the multi-parameter curve graph include at least load and current, and the parameters of the horizontal axis include displacement, and the current pump sinking degree is fed back in real time according to the multi-parameter curve graph, thereby dynamically optimizing at least one of the parameters of the pumping unit's operating stroke frequency and stroke speed.

2. The method for optimizing the stroke parameters of an oil pumping unit based on the feedback parameters of an oil pumping unit motor according to claim 1, characterized in that: In step S2, the specific steps of establishing a mathematical model of electric parameter-torque-suspension point load according to the acquired electric parameters include: Step S21: Establishing the output torque of the pumping unit motor The calculation model is: in, is the motor active power, is the motor conversion efficiency, is the power factor, is the voltage in the electrical parameter, is the current in the electrical parameter; is the motor speed, is the number of motor pole pairs, is the frequency in the electrical parameter; Step S22: Establishing the oil pumping unit suspension point load The calculation model is: in, is the motor transmission efficiency, is the crank radius of the four-bar linkage of the oil pumping unit, is the length of the forearm of the pumping unit walking beam, is the crank angle of the four-bar linkage of the oil pump; Step S23: Establishing the suspension point displacement The calculation model is: in, is the crank radius of the four-bar linkage of the oil pumping unit, is the length of the forearm of the pumping unit walking beam, is the crank angle of the four-bar linkage of the oil pump.

3. The method for optimizing the stroke parameters of an oil pumping unit based on the feedback parameters of an oil pumping unit motor according to claim 1, characterized in that: In step S3, the specific method of real-time monitoring the pump sinking degree according to the multi-parameter curve graph includes: The current pump submergence is determined based on the curve shape of at least one of the load-displacement curve and the current-displacement curve in the multi-parameter curve diagram, and the stroke parameters are optimized mainly by dynamically adjusting the stroke frequency to a reasonable range and supplemented by dynamically adjusting the stroke speed to a reasonable range.

4. The method for optimizing the stroke parameters of an oil pumping unit based on the feedback parameters of an oil pumping unit motor according to claim 3, characterized in that: The specific method for determining the current pump submergence according to the curve shape of at least one of the load-displacement curve and the current-displacement curve in the multi-parameter curve graph comprises: When the load-displacement curve is used, it is determined whether the load-displacement curve is a complete parallelogram. If not, the abnormal curve deformation rate is determined, and then the current pump submergence level is determined according to the preset relationship between the curve deformation rate and the pump submergence level; When the current-displacement curve is used, the current peak oscillation fluctuation rate of the current-displacement curve within one cycle is determined, and then the current pump submergence level is determined based on the relationship between the preset current peak oscillation fluctuation rate and the pump submergence level.

5. The method for optimizing the stroke parameters of an oil pumping unit based on the feedback parameters of an oil pumping unit motor according to claim 4, characterized in that: The current sinking state is judged by combining the load-displacement curve and the current-displacement curve, where: The pump submergence is qualitatively determined by the load-displacement curve, and the level of pump submergence is verified and quantified by the current-displacement curve.

6. The method for optimizing the stroke parameters of an oil pumping unit based on the feedback parameters of an oil pumping unit motor according to claim 1, characterized in that: In step S3, the numerical integration method includes at least one of the trapezoidal rule, the Simpson's rule and the Romberg integral.

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