Pumping unit effective stroke identification method based on improved cubic spline interpolation

Abstract

The invention provides a pumping unit effective stroke identification method based on improved cubic spline interpolation, which comprises the following steps: performing conversion processing on a ground indicator diagram through a Gibbs fluctuation model to obtain initial pump indicator diagram data points; fitting processing is carried out on the initial pump indicator diagram data points through an improved cubic spline fitting formula, and a closed fitting curve is obtained; the length of the fitting curve is calculated, the number of sampling data points is set for sampling, uniform pump indicator diagram data points are obtained, and the Euclidean distances between every two adjacent points are equal; and a five-point curvature method and uniform pump indicator diagram data points are used for recognizing a traveling valve closing point and a traveling valve opening point in the lower load area, and the effective stroke of the pump is determined. According to the method, the accuracy of effective stroke recognition is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of petroleum engineering, and particularly to a method for identifying the effective stroke of a pumping unit based on improved cubic spline interpolation. Background Art

[0002] In China, more than 90% of oil wells use beam pumping units for production, and the measurement of the liquid production of each oil well is a difficult point in oil well production. At present, the methods for measuring the oil well production in China include the following two. The first is to transport the oil from each oil well to the metering station for measurement. The second is to convert the dynamometer card into a pump dynamometer card to measure the production. Measuring production by dynamometer card simplifies the surface process compared with small station measurement, and is of great significance for continuous calculation of production and cost saving.

[0003] Cubic spline interpolation is widely used in smooth curve fitting. It constructs a cubic polynomial to fit data points, divides the data points into multiple segments by the method of cubic spline interpolation, and finally forms a cubic spline fitting curve by fitting and splicing each small segment. Cubic spline interpolation fitting has wide application value in retaining the original curve characteristics and resampling to optimize data points. However, traditional cubic spline interpolation fitting must satisfy that the abscissas of data points are strictly increasing, and cannot fit a closed curve such as a dynamometer card.

[0004] Therefore, in the prior art, when calculating the effective stroke of a pump from a pump dynamometer card, due to the uneven distribution of image data points, the opening and closing points of the pump valve identified by the five-point curvature method are inaccurate, resulting in deviation in the calculation of the effective stroke and inaccurate production calculation. Summary of the Invention

[0005] In view of this, the present invention provides a method for identifying the effective stroke of a pumping unit based on improved cubic spline interpolation to solve the above problems.

[0006] The present invention provides a method for identifying the effective stroke of a pumping unit based on improved cubic spline interpolation, including: performing conversion processing on a surface dynamometer card through a Gibbs fluctuation model to obtain initial pump dynamometer card data points; performing fitting processing on the initial pump dynamometer card data points through an improved cubic spline fitting formula to obtain a closed fitting curve; calculating the length of the fitting curve, setting the number of sampled data points for sampling to obtain uniform pump dynamometer card data points, where the Euclidean distance between adjacent two points is equal; using the five-point curvature method and the uniform pump dynamometer card data points to identify the closing point and opening point of the traveling valve in the download load area, and determining the effective stroke of the pump.

[0007] In another implementation manner of the present invention, the Gibbs fluctuation model is expressed as:

[0008]

[0009] Among them, U(x,t) is the displacement function of the sucker rod at different times t in the x section; a is the velocity of stress wave propagation in the sucker rod string; c is the viscous damping coefficient.

[0010] In another implementation manner of the present invention, the fitting process of the initial pump dynamometer card data by improving the cubic spline to obtain a closed fitting curve includes: calculating the distance and cumulative distance of each initial pump dynamometer card data point; dividing the function interval according to the cumulative distance, and performing fitting processing on the function of each interval through the improved cubic spline fitting formula; setting the curvature of the starting and ending points of each curve, and smoothing the starting and ending points of the curve to obtain a closed fitting curve.

[0011] In another implementation manner of the present invention, the cumulative distance is expressed as:

[0012]

[0013] Among them, i is the i-th segment of the function; s(i) is the cumulative distance function of the i-th segment; x(i) is the displacement coordinate of the i-th data point in the initial pump dynamometer card data; y(i) is the load coordinate of the i-th data point in the initial pump dynamometer card data.

[0014] In another implementation manner of the present invention, the improved cubic spline fitting formula is expressed as:

[0015] y(x) = a i +b i (x - x i+1 ) + c i (x - x i+1 ) 2 +d i (x - x i+1 ) 3 , s ∈ (s(i - 1), s(i))

[0016] Among them, x i+1 is the x-axis coordinate of the (i + 1)-th data point; a i , b i , c i , d i are all the coefficients to be determined of the function in the i-th segment interval.

[0017] In another implementation manner of the present invention, the Euclidean distance is expressed as:

[0018]

[0019] Among them, s is the total length of the curve; n is the number of sampling points.

[0020] In another implementation manner of the present invention, the five-point curvature method formula is:

[0021]

[0022] δK i =|K i+1 -K i |

[0023] δK′ i =(δK i-2 +δK i-1 +δK i +δK i+1 +δK i+2 ) / 5

[0024] Wherein, for any point P i (s i , f i ) on the curve, adjacent points P i-2 (s i-2 , f i-2 ), P i-1 (s i-1 , f i-1 ), P i (s i , f i ), P i+1 (s i+1 , f i+1 ), P i+2 (s i+2 , f i+2 ); K i is the curvature value of point P i , Δθ i is the rotation angle from P i-2 P i to P i P i+2 , Δl i is the arc length of the curve, δK i is the change in curvature between curvature P i and P i+1 , and δK i ' is the change in curvature averaged over five points.

[0025] In another implementation of the present invention, the effective stroke formula is expressed as:

[0026] L stoke =x close -x open

[0027] Wherein, x close is the displacement at the closing point of the traveling valve, and x open is the displacement at the opening point of the traveling valve.

[0028] The effective stroke identification method of a pumping unit based on improved cubic spline interpolation according to the present invention. Compared with the traditional cubic spline that can only fit a curve with strictly increasing abscissa, the improved cubic spline fitting can fit a closed curve, and the line is smoother. The improved cubic spline well preserves the shape characteristics of the dynamometer card, making the judgment of the pump valve in the dynamometer card for calculating production more accurate, and effectively improving the accuracy of effective stroke identification. Description of the Drawings

[0029] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. By reading the detailed description of the following embodiments, the advantages and benefits in the solutions become clear to those skilled in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. In the drawings:

[0030] Figure 1 Schematic flow diagram of the effective stroke identification method of a pumping unit based on improved cubic spline interpolation according to an embodiment of the present invention.

[0031] Figure 2 Schematic diagram of the cumulative distance division function interval according to an embodiment of the present invention.

[0032] Figure 3 Schematic diagram of the curvature geometric model according to an embodiment of the present invention.

[0033] Figure 4 Schematic diagram of the opening and closing points of the traveling valve under the download load according to an embodiment of the present invention.

[0034] Figure 5 Schematic diagram of the fitting effect of the GT1 improved cubic spline according to an embodiment of the present invention.

[0035] Figure 6 Schematic diagram of the comparison between the GT1 original data points and the resampled data points according to an embodiment of the present invention.

[0036] Figure 7 Schematic diagram of the comparison of the pump valve identification effects before and after the improvement of GT1 according to an embodiment of the present invention.

[0037] Figure 8 Schematic diagram of the fitting effect of the GT2 improved cubic spline according to an embodiment of the present invention.

[0038] Figure 9 Schematic diagram of the comparison between the GT2 original data points and the resampled data points according to an embodiment of the present invention.

[0039] Figure 10 Schematic diagram of the comparison of the pump valve identification effects before and after the improvement of GT2 according to an embodiment of the present invention.

[0040] Figure 11 Schematic diagram of the improved cubic spline fitting effect of GT3 according to an embodiment of the present invention.

[0041] Figure 12 Schematic diagram of the comparison between the resampled data points and the original data points of GT3 according to an embodiment of the present invention.

[0042] Figure 13 Schematic diagram of the comparison of the pump valve recognition effects before and after the improvement of GT3 according to an embodiment of the present invention. Detailed implementation manners

[0043] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and detailedly described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art shall fall within the protection scope of the embodiments of the present invention.

[0044] Figure 1 Schematic diagram of the flow of a method for identifying the effective stroke of a pumping unit based on improved cubic spline interpolation provided by an embodiment of the present invention. As Figure 1 shown, this embodiment mainly includes:

[0045] S101. Perform conversion processing on the ground dynamometer card through the Gibbs fluctuation model to obtain initial pump work diagram data points.

[0046] S102. Perform fitting processing on the initial pump work diagram data points through an improved cubic spline fitting formula to obtain a closed fitting curve.

[0047] S103. Calculate the length of the fitting curve, set the number of sampled data points for sampling to obtain uniform pump work diagram data points, where the Euclidean distance between adjacent two points is equal.

[0048] Exemplarily, by calculating the total cumulative length of the fitting curve, setting the number of re-sampled data points for segmentation, ensuring that the Euclidean distance between adjacent two points is equal, and combining with the cubic spline fitting function for interpolation to obtain uniform pump work diagram data points.

[0049] S104. Use the five-point curvature method and the uniform pump work diagram data points to identify the closing point and opening point of the traveling valve in the download load area, and determine the effective stroke of the pump.

[0050] The effective stroke identification method of the pumping unit based on improved cubic spline interpolation according to the present invention, compared with the traditional cubic spline that can only fit a curve with strictly increasing abscissa, the improved cubic spline fitting can fit a closed curve, and the line is smoother. The improved cubic spline is used to well retain the shape characteristics of the dynamometer card, making the judgment of the pump valve in the dynamometer card for calculating production more accurate, and effectively improving the accuracy of effective stroke identification.

[0051] In another implementation manner of the present invention, the Gibbs fluctuation model is expressed as:

[0052]

[0053] where U(x,t) is the displacement function of the sucker rod at different times t at the x section; a is the velocity of the stress wave propagating in the sucker rod string; c is the viscous damping coefficient.

[0054] In another implementation manner of the present invention, the initial pump dynamometer card data is fitted by the improved cubic spline to obtain a closed fitting curve, including: calculating the distance and cumulative distance of each segment of the initial pump dynamometer card data points; dividing the function interval according to the cumulative distance, and fitting the function of each interval by the improved cubic spline fitting formula; setting the curvature of the starting and ending points of each segment of the curve, and smoothing the starting and ending points of the curve to obtain a closed fitting curve.

[0055] Exemplarily, in order to be able to fit a closed curve such as the oil well pump dynamometer card, when performing cubic spline interpolation, the cumulative distance s is used as the independent variable of the interpolation to fit the displacement and load of each segment of the curve. Using the displacement and load coordinates as the independent variables and the cumulative distance s as the parameter to fit the curve follows the path more naturally and maintains the actual distance relationship between points.

[0056] The cubic spline fitting method based on the cumulative distance s is as follows: calculate the distance and cumulative distance of each segment of data points to divide the function interval. Fit the function of each interval by cubic spline, and construct a cubic polynomial through each data point in each interval. Set the curvature of the starting and ending points of each segment of the curve, and smooth the starting and ending points of the curve.

[0057] When performing cubic spline interpolation and fitting, in order to smooth the starting and ending points of the curve, it is necessary to set the curvature of the starting and ending points of the interpolation curve, and set the second-order derivatives of the starting and ending points and to be 0. Select a pump dynamometer card data, and use the improved cubic spline to perform interpolation and fitting on the pump dynamometer card data points. As Figure 3 shown, in the figure, the blue one is the dynamometer card drawn by the original data, and the green one is the dynamometer card obtained by the improved cubic spline interpolation and fitting. The improved cubic spline well retains the shape characteristics of the dynamometer card.

[0058] Compared with the traditional cubic spline that can only fit a curve with strictly increasing abscissa, the improved cubic spline fitting can fit a closed curve, and the line is smoother.

[0059] In another implementation of the present invention, the cumulative distance is expressed as:

[0060]

[0061] where i is the i-th segment function; s(i) is the cumulative distance function of the i-th segment; x(i) is the displacement coordinate of the i-th data point in the initial pump work diagram data points; y(i) is the load coordinate of the i-th data point in the initial pump work diagram data points.

[0062] In another implementation of the present invention, the improved cubic spline fitting formula is expressed as:

[0063] y(x) = a i + b i (x - x i+1 ) + c i (x - x i+1 ) 2 + d i (x - x i+1 ) 3 , s ∈ (s(i - 1), s(i))

[0064] where x i+1 is the x-axis coordinate of the (i + 1)-th data point; a i , b i , c i , d i are all coefficients to be determined for the i-th segment interval function.

[0065] In another implementation of the present invention, the Euclidean distance is expressed as:

[0066]

[0067] where s is the total length of the curve; n is the number of sampling points.

[0068] In another implementation of the present invention, the cumulative distance formula between the resampled data points and the initial points is:

[0069] s re (i) = (n i - 1)d

[0070] where s re (i) is the cumulative distance function of the resampled data points, used to determine the interval of the cubic spline function for the resampled data points, n iis the i-th data among the n resampled data points.

[0071] Set the number of resampling points. In the present invention, the number of resampled data points is set to 200, and the total length of the curve is evenly segmented, with the distance of each segment being the distance between adjacent points.

[0072] In another implementation manner of the present invention, the five-point curvature method formula is:

[0073]

[0074] δK i =|K i+1 -K i |

[0075] δK′ i =(δK i-2 +δK i-1 +δK i +δK i+1 +δK i+2 ) / 5

[0076] Wherein, any point P i (s i , f i ) on the curve, adjacent points P i-2 (s i-2 , f i-2 ), P i-1 (s i-1 , f i-1 ), P i (s i , f i ), P i+1 (s i+1 , f i+1 ), P i+2 (s i+2 , f i+2 ); K i is the curvature value of point P i , Δθ i is the rotation angle from P i-2 P i to P i P i+2 P i is the curve arc length, δK i is the curvature change amount between curvature P i and P i+1 , δK i ' is the curvature change amount obtained by taking the average value of five points.

[0077] Exemplarily, any point P i (s i , fi ) The curvature calculation is based on its adjacent P i-2 (s i-2 , f i-2 ), P i-1 (s i-1 , f i-1 ), P i (s i , f i ), P i+1 (s i+1 , f i+1 ), P i+2 (s i+2 , f i+2 ). The geometric model is constructed from these five points.

[0078] In another implementation of the present invention, the effective stroke formula is expressed as:

[0079] L stoke = x close - x open

[0080] where x close is the displacement at the closing point of the traveling valve, and x open is the displacement at the opening point of the traveling valve.

[0081] Exemplarily, the curvature change amount of each point is calculated by the five-point curvature method, the closing point and the opening point of the traveling valve in the download load area are identified, and the effective stroke is obtained by calculating the difference between the abscissas of these two points.

[0082] As Figure 4 shown, the closing point of the traveling valve is in the lower left area of the work diagram, where the curvature is the largest. Set the first thirty percent of the smaller pump work diagram load array and less than the mean value of the displacement array as boundary conditions to judge the closing point of the traveling valve.

[0083] The opening point of the traveling valve is in the lower right area of the work diagram, where the curvature is the largest. Set the first seventy percent of the larger pump work diagram load array and greater than the mean value of the displacement array as boundary conditions to judge the opening point of the traveling valve.

[0084] The GT1 pump work diagram is analyzed using improved cubic spline interpolation fitting, and the fitting effect is as Figure 5 shown. The comparison between the resampled data points and the original data points is as Figure 6 shown. The comparison of the traveling valve opening and closing points identified by the improved cubic spline interpolation and the original data using the five-point curvature algorithm is as Figure 7 shown.

[0085] The GT2 pump work diagram is analyzed using improved cubic spline interpolation fitting, and the fitting effect is as Figure 8As shown. Comparison between resampled data points and original data points Figure 9 As shown. Comparison between the improved cubic spline interpolation and the original data for identifying the opening and closing points of the traveling valve using the five-point curvature algorithm Figure 10 As shown.

[0086] Analyze the GT3 pump dynamometer card using the improved cubic spline interpolation fitting, and the fitting effect is as Figure 11 As shown. Comparison between resampled data points and original data points Figure 12 As shown. Comparison between the improved cubic spline interpolation and the original data for identifying the opening and closing points of the traveling valve using the five-point curvature algorithm Figure 13 As shown.

[0087] In the present invention, by analyzing a large number of pump dynamometer cards of multiple wells, it is obtained that the accuracy of the pump valve identification method based on the improved cubic spline interpolation of the dynamometer card is higher than that of the traditional pump valve identification method.

[0088] On the other hand of the present invention, the electronic device includes: a processor, a memory, and a communication bus and a communication interface.

[0089] Wherein:

[0090] The processor, the memory, and the communication interface complete communication with each other through the communication bus.

[0091] The communication interface is used to communicate with other electronic devices or servers.

[0092] The processor is used to execute a program, and specifically can execute the steps of any one of the sucker rod pumping unit effective stroke identification methods based on the improved cubic spline interpolation in the above embodiments.

[0093] Specifically, the program may include program code, and the program code includes computer operation instructions.

[0094] The processor may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present application. One or more processors included in the intelligent device may be of the same type of processor, such as one or more CPUs; or may be of different types of processors, such as one or more CPUs and one or more ASICs.

[0095] The memory is used to store the program. The memory may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0096] The program can specifically be used to enable a processor to execute steps for implementing any one of the pumping unit effective stroke identification methods based on improved cubic spline interpolation described in the embodiments. For the specific implementation of each step in the program, reference can be made to the steps and corresponding descriptions in the units executed by any one of the pumping unit effective stroke identification methods based on improved cubic spline interpolation in the above steps, which will not be elaborated here. Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described devices and modules can refer to the corresponding process descriptions in the foregoing method embodiments.

[0097] The method according to the embodiments of the present invention can be implemented in a server equipped with a central processing unit (CPU) and an image processing unit (GPU).

[0098] So far, specific embodiments of the present invention have been described. Other embodiments are within the scope of the appended claims. In some cases, the actions recited in the claims can be performed in a different order and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result.

[0099] It should be noted that all directional indications (such as up, down, left, right, back...) in the embodiments of the present invention are only used to explain the relative positional relationship between components in a specific order (as shown in the drawings). If the specific order changes, the directional indications will also change accordingly.

[0100] In the description of the present invention, the terms "first" and "second" are only used for conveniently describing different components or names, and cannot be understood as indicating or implying an order relationship, relative importance, or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature.

[0101] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0102] It should be noted that although the specific embodiments of the present invention have been described in detail in conjunction with the accompanying drawings, it should not be construed as a limitation on the protection scope of the present invention. Within the scope described in the claims, various modifications and deformations that can be made by those skilled in the art without creative labor still belong to the protection scope of the present invention.

[0103] The examples of the embodiments of the present invention are intended to concisely illustrate the technical features of the embodiments of the present invention, so that those skilled in the art can intuitively understand the technical features of the embodiments of the present invention, and shall not be used as an improper limitation of the embodiments of the present invention.

[0104] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying the effective stroke of an oil pump based on improved cubic spline interpolation, characterized in that: include: The ground dynamometer diagram is converted and processed by the Gibbs wave model to obtain the initial pump dynamometer diagram data points; The initial pump performance diagram data points are fitted by improving the cubic spline fitting formula to obtain a closed fitting curve; Calculating the length of the fitting curve, setting the number of sampling data points for sampling, and obtaining uniform pump performance diagram data points, wherein the Euclidean distances between two adjacent points are equal; The five-point curvature method and the uniform pump work diagram data points are used to identify the traveling valve closing point and the traveling valve opening point in the lower load region to determine the effective stroke of the pump.

2. The method according to claim 1, characterized in that The Gibbs fluctuation model is expressed as: Among them, U(x,t) is the displacement function of the sucker rod at different times t in the x section; a is the speed of stress wave propagation in the sucker rod string; c is the viscous damping coefficient.

3. The method according to claim 1, characterized in that: The fitting process of the initial pump performance diagram data by improving the cubic spline to obtain a closed fitting curve includes: Calculate the distance and cumulative distance of each initial pump performance diagram data point; Dividing the function interval according to the cumulative distance, and fitting the function of each interval by improving the cubic spline fitting formula; Set the curvature of the start and end points of each curve, smooth the start and end points of the curve, and obtain a closed fitting curve.

4. The method according to claim 3, characterized in that The cumulative distance is expressed as: Where i is the i-th segment function; s(i) is the i-th segment cumulative distance function; x(i) is the displacement coordinate of the i-th data point in the initial pump performance diagram data points; y(i) is the load coordinate of the i-th data point in the initial pump performance diagram data points.

5. The method according to claim 4, characterized in that The improved cubic spline fitting formula is expressed as: y(x)=a i +b i (x-x i+1 )+c i (x-x i+1 ) 2 +d i (x-x i+1 ) 3 ,s∈(s(i-1),s(i)) Among them, x i+1 is the x-axis coordinate of the i+1th data point; a i 、b i 、c i ,d i These are the coefficients to be determined for the i-th interval function.

6. The method according to claim 1, characterized in that The Euclidean distance is expressed as: Where s is the total length of the curve and n is the number of sampling points.

7. The method according to claim 6, characterized in that The five-point curvature method formula is: δk i =|K i+1 -K i | δk′ i =(δK i-2 +δK i-1 +δK i +δk i+1 +δk i+2 ) / 5 Among them, any point P on the curve i (s i , f i ), adjacent point P i-2 (s i-2 , f i-2 ), P i-1 (s i-1 , f i-1 ), P i (s i , f i ), P i+1 (s i+1 , f i+1 ), P i+2 (s i+2 , f i+2 );K i It's point P i The curvature value, Δθ i YesP i-2 P i To P i P i+2 Rotation angle, Δl i is the arc length of the curve, δK i is the curvature P i and P i+1 The curvature change, δK i ' is the change in curvature of the average of five points.

8. The method according to claim 1, characterized in that The effective stroke formula is expressed as: L stoke =x close -x open Among them, x close is the displacement of the traveling valve at the closing point, x open is the displacement of the floating valve at the opening point.

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