A rod-pipe eccentric wear diagnosis and early warning method for pumping unit wells under digital conditions

Abstract

The present application belongs to the field of fault early warning, and specifically relates to a pumping unit well rod and tubing eccentric wear diagnosis and early warning method under digital conditions. The method comprises the following steps: predicting the maximum load and the minimum load of a pumping unit well theoretical suspension point dynamometer card based on the working condition data of the pumping unit; obtaining daily cluster dynamometer card data by collecting and processing a ground dynamometer card in real time through oil well field equipment; judging whether the pumping unit well has eccentric wear according to the maximum load and the minimum load of the pumping unit well theoretical suspension point dynamometer card and the daily cluster dynamometer card data; and early warning the eccentric wear of the oil well rod and tubing according to the eccentric wear condition of the pumping unit well. The present application provides method guidance for process monitoring of typical rod and tubing eccentric wear problems, provides a technical means for evaluation of anti-rod and tubing eccentric wear devices and methods, and provides a basic guarantee means for reducing production loss caused by rod and tubing eccentric wear.

Description

Technical Field

[0001] This invention belongs to the field of fault early warning, specifically a method for diagnosing and early warning of rod and tubing wear in oil pumping units under digital conditions. Background Technology

[0002] Due to the long operating distance, slender sucker rod string, and high downward resistance of the pumping unit-deep well pump production system, the sucker rod string and tubing string are highly susceptible to uneven wear. This leads to rod breakage, leakage, and other problems, posing significant risks to production safety, increasing production costs, and severely impacting overall production efficiency. Currently, industry solutions to uneven wear primarily focus on the results of uneven wear, combined with the mechanisms underlying its formation, to design anti-wear tools and process parameters. However, analysis of the process characteristics of uneven wear is relatively limited. Traditional dynamometer card (DDT) analysis relies on the shape and numerical characteristics of a single DDT chart. Because the actual conditions under which uneven wear occurs are highly unstable, it is essentially impossible to obtain effective information reflecting uneven wear from the DDT chart. With the advancement of information technology, many oilfields have already achieved or are in the process of digitization, providing the possibility for real-time monitoring and further quantitative analysis of uneven wear. Typical characteristics of uneven wear are reflected in the large-scale, densely collected time-series clustered DDT chart data. Previously, a single DDT chart could not diagnose uneven wear; however, the characteristic analysis of digitized clustered DDT charts offers a new solution to this problem. Summary of the Invention

[0003] This invention addresses the issue of in-depth data application in the field of oil well digitization by designing a novel quantitative analysis and calculation method for rod and tubing wear problems that integrates real-time data acquisition and the operating mechanism of oil pumps. This method provides guidance for process monitoring of typical rod and tubing wear problems, offers technical means for evaluating rod and tubing wear prevention devices and methods, and provides a fundamental guarantee for reducing production losses caused by rod and tubing wear.

[0004] The technical solution adopted by the present invention to achieve the above objectives is as follows:

[0005] A method for diagnosing and predicting rod and tubing wear in oil pumping units under digital conditions includes the following steps:

[0006] Based on the operating data of the pumping unit, the maximum and minimum loads of the theoretical suspension point dynamometer diagram of the pumping unit well are predicted.

[0007] Daily cluster dynamometer data is obtained by real-time acquisition and processing of surface dynamometer diagrams using on-site equipment at oil wells.

[0008] Based on the maximum and minimum loads of the theoretical suspension point dynamometer diagram of the pumping unit well and the daily cluster dynamometer diagram data, determine whether the pumping unit well is experiencing uneven wear.

[0009] Based on the occurrence of uneven wear in the pumping well, an early warning system for uneven wear of the well rod and tubing is implemented.

[0010] The maximum and minimum loads on the theoretical suspension point dynamometer diagram of the pumping unit well are as follows:

[0011]

[0012]

[0013] W r =L rod q r g

[0014] W′ r =L rod q r g

[0015] W′ l =A P L rod ρ l g

[0016] q′ r =q r *(ρ r -ρ l ) / ρ r

[0017] Among them, P nmax P represents the maximum load on the theoretical suspension point dynamometer diagram. nmin For the theoretical minimum load on the suspension point indicator diagram, W′ r W is the load on the sucker rod string acting on the suspension point during the downstroke. r For the upstroke sucker rod string load, W′ l R is the liquid column load acting on the plunger during the upstroke, R is the crank radius of rotation, and L is the displacement of the piston. rod s is the length of the sucker rod, n is the stroke, and q is the number of strokes. r q′ is the mass of the sucker rod per meter. r A represents the mass of each meter of sucker rod in the well fluid. P Let ρ be the cross-sectional area of ​​the plunger, L be the length of the connecting rod, and ρ be the cross-sectional l ρ is the average density of the liquid inside the pipe. r Let g be the density of the steel, and g be the acceleration due to gravity.

[0018] The process of acquiring and processing surface dynamometer maps in real time using on-site oil well equipment specifically involves:

[0019] At least 48 surface dynamometer maps are collected within 24 hours using digital equipment deployed at the oil well site. After removing the dynamometer maps for start-up and shutdown wells, the remaining dynamometer maps are used to generate a data sample as the daily cluster dynamometer map data.

[0020] The daily cluster operation data includes:

[0021] Mean load P maxave Maximum load P maxmax Minimum load P maxmin Load fluctuation range ΔP max Mean load P minave Maximum lower load P minmax Minimum load P minmin Load fluctuation range ΔP min ,in:

[0022] ΔP max =P maxmax -P maxmin

[0023] ΔP min =P minmax -P minmin .

[0024] The removal of the well start-stop work diagram specifically refers to:

[0025] If the dynamometer card contains information about the well opening / closing, then the dynamometer card for the first half hour after the well is opened is directly removed; if the well opening / closing information cannot be obtained, then the decision to remove the dynamometer card is based on the maximum load value in the dynamometer card, specifically:

[0026] P maxi <γP nmax

[0027] Among them, P maxi γ represents the maximum load value of the i-th dynamometer among the 48 dynamometer charts for that day, and γ is the determination coefficient.

[0028] The determination of whether the pumping unit well has experienced uneven wear is specifically as follows:

[0029] If the daily kinetic energy distribution chart data of a pumping unit well meets the following conditions, then the pumping unit well has experienced uneven wear on that day:

[0030] ΔP max ≤aP maxave

[0031] ΔP min ≥bP minave

[0032] P minmax ≤cP nmin

[0033] Where a, b, and c are all wear coefficients, P maxave P is the average value of all loads on the cluster power map. minave This represents the average load across all loads in the cluster power diagram.

[0034] The aforementioned early warning system for wear-prone oil well tubing specifically includes:

[0035] 1) Wells without anti-wear measures experience wear:

[0036] When the well meets

[0037] ΔP max ≤aP maxave

[0038] ΔP min ≥0.5bP minave

[0039] P minmax ≤cP nmin

[0040] At that time, a suspected wear warning was issued for the well, prompting technicians to analyze the wear condition of the well and take timely preventive measures.

[0041] 2) Wells with anti-wear measures experience uneven wear:

[0042] 2.1) If anti-wear does not eliminate buckling, and eccentric wear persists in the daily data, then the 7 ΔP values ​​from the first week after the well is put into operation should be used. min The average value is used as the benchmark value ΔP minbm In subsequent production, when ΔP on a certain day min In

[0043] 0.9ΔP minbm <ΔP min <1.1ΔP minbm

[0044] At that time, the wear was stable due to uneven wear.

[0045] When ΔP min In

[0046] ΔP min ≤0.9ΔP minbm

[0047] At that time, the wear was reduced due to uneven wear.

[0048] When ΔP min In

[0049] ΔP min ≥1.1ΔΔP minbm

[0050] At this time, an early warning is issued due to increased uneven wear;

[0051] 2.2) If anti-wear measures reduce or eliminate buckling, then during the first three days of implementing anti-wear measures according to the anti-wear design, the ΔP minConduct an inspection, if

[0052] ΔP min >0.15P nmin

[0053] Therefore, the well's anti-wear design is considered substandard.

[0054] The present invention has the following beneficial effects and advantages:

[0055] 1. This invention improves the online digital application level of rod pumping systems, fully leverages the application potential of oilfield digital information systems, and enhances the level of refined management of oil and gas production.

[0056] 2. This invention improves the diagnostic level of wear on oil pumping wells and the monitoring and diagnosis of the wear process, reduces production losses caused by wear on the rod and tubing of oil wells, and lowers oil production costs.

[0057] 3. This invention provides an early assessment method for the effectiveness of anti-wear measures, enabling timely detection of the risk of premature oil well leakage and rod breakage caused by substandard anti-wear measures. Attached Figure Description

[0058] Figure 1 Schematic diagram of daily cluster work graph data sample;

[0059] Figure 2 The wear characteristics of oil wells with insufficient fluid supply, as shown in the daily cluster power chart data;

[0060] Figure 3 The normal operating condition oil well wear characteristic diagram shown by the daily cluster power chart data;

[0061] Figure 4 Schematic diagram of the process for diagnosing and warning of uneven wear of the rod and tubing in oil pumping units. Detailed Implementation

[0062] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0063] like Figure 4 As shown, this invention mainly consists of four functional blocks: theoretical parameter calculation, characteristic parameter acquisition, wear characteristic identification and diagnosis, and wear early warning. Supported by the basic dynamic and static parameters obtained from oilfield digitalization and informatization construction, the technical solution of this invention is described below.

[0064] (1) Calculation of theoretical parameters: theoretical maximum suspension point load, theoretical minimum suspension point load (without eccentric wear)

[0065]

[0066]

[0067] Wr =L rod q r g

[0068] W′ r =L rod q r g

[0069] W l '=A P L rod ρ L g

[0070] q′ r =q r *(ρ r -ρ l ) / ρ r

[0071] Among them, P nmax -The theoretical maximum load on the suspension point dynamometer diagram, kN

[0072] P nmin -Theoretical minimum load for suspension point indicator diagram, kN

[0073] W′ r - Load on the sucker rod string acting at the suspension point during the downstroke, N

[0074] Wr - Top stroke sucker rod string load, N

[0075] W l '-The liquid column load acting on the plunger during the upstroke, N

[0076] R - Crank rotation radius, m

[0077] L rod - Sucker rod length, in meters

[0078] s-stroke, real-time test data, m,

[0079] n - number of strokes, real-time test data, min-1

[0080] q r - Mass of sucker rod per meter, kg / m

[0081] q′ r - Mass of each meter of sucker rod in well fluid, kg / m

[0082] A P -Plunger cross-sectional area, m2

[0083] L - Link length, in meters

[0084] ρ L -Average density of the liquid inside the pipe, kg / m³

[0085] (2) Feature parameter acquisition: At least 48 surface dynamometer maps were collected within 24 hours using digital equipment deployed at the oil well site. After removing the start-up and shutdown dynamometer maps, the remaining dynamometer maps were used to generate a data sample, defined as daily cluster dynamometer map data, or simply "daily data". The main parameters are as follows:

[0086] Mean load P maxave Maximum load P maxmax Minimum load P maxmin Load fluctuation range ΔP max ;

[0087] ΔP max =P maxmax -P maxmin

[0088] Mean underload P minave Maximum lower load P minmax Minimum load P minmin Load fluctuation range ΔP min ;

[0089] ΔP min =P minmax -P minmin

[0090] A sample diagram of daily cluster power graph data, such as Figure 1 As shown.

[0091] The removal of dynamometer cards affected by well shutdowns can be done in two ways: First, if well start / stop information is available, dynamometer cards from the first half hour after well start-up can be directly removed. Second, if start / stop information is unavailable, the following criteria can be applied for removal: When a normally producing oil well is briefly stopped and then restarted, the maximum load on the suspension point dynamometer card will be significantly lower than the value after stable production due to the rise in the dynamic fluid level. Therefore, the criterion for removing dynamometer cards affected by well shutdowns is:

[0092] P maxi <0.8P nmax

[0093] P maxi The maximum load value of a specific power diagram among the 48 power diagrams on that day.

[0094] (3) Identification and diagnosis of wear characteristics

[0095] There are two main types of oil well wear: one is wear at a fixed position caused by a sharp change in wellbore curvature; the other is wear between the sucker rod and the tubing wall caused by buckling deformation due to instability of the lower part of the sucker rod string encountering resistance during descent. While the sucker rod string can also buckle and deform during descent, its impact on the suspension point load is much smaller than that of descent wear due to the tubing's higher stability. In actual production, the second type is more prevalent. The axial component of the frictional force at each contact point in both types of wear significantly reduces the suspension point load. Furthermore, the second type of contact friction is unstable; even with relatively stable production parameters, the contact length and number of contact points can vary randomly. Therefore, in this case, the continuously acquired suspension point dynamometer will show a relatively stable overall shape, with a relatively stable maximum load, while the minimum load fluctuates randomly below the theoretical value. The amplitude of this fluctuation increases as the wear intensifies. Therefore, the daily dynamometer chart of wells experiencing eccentric wear is characterized by a relatively stable maximum load or slight fluctuations, while the minimum load fluctuates downwards at a larger magnitude.

[0096] ΔP max ≤aP maxave

[0097] ΔP min ≥bP minave

[0098] P minmax ≤cP nmin

[0099] The coefficients a, b, and c in the above format are recommended to be obtained by training an artificial intelligence model on a large amount of wear data from a specific oilfield. Alternatively, they can be determined by experts. The recommended initial values ​​are a = 0.15, b = 0.30, and c = 1.

[0100] If the data for a given day meets the above conditions, it can be determined that the well experienced uneven wear on that day.

[0101] Typical wear characteristics are shown in the diagram. Figure 2 , Figure 3 As shown in the figure, the horizontal axis represents displacement and the vertical axis represents load.

[0102] (4) Early warning of rod and tubing wear in oil wells

[0103] Early warnings are issued based on the following categories according to the anti-wear measures implemented in oil wells:

[0104] 1) Wells without anti-wear measures that experience eccentric wear, where the rod string design did not consider anti-wear measures necessary (i.e., wells without weighted rods, centralizers, or other anti-wear measures). For these wells, it is recommended to use the strengthening criterion, when its ΔP... min ≥0.5bPminave If the other two conditions are met, a suspected wear warning will be issued, prompting technicians to analyze the wear condition of the well and take timely preventive measures.

[0105] 2) If wear occurs in wells with anti-wear measures, there are three situations: First, measures such as centralizers and anti-wear couplings are used to prevent wear but do not eliminate buckling, and the focus is on the change in the degree of wear; second, the lower rod string is weighted to reduce or eliminate buckling; and third, a design that adopts both of these anti-wear measures simultaneously.

[0106] Scenario 1: Anti-wear does not eliminate buckling; eccentric wear is always present in daily data. The main focus is on ΔP. min The changing trend, based on the 7 ΔP values ​​during the first week after the well was put into operation. min The average value is the benchmark value ΔP minbm .

[0107] In subsequent production, when ΔP on a certain day min In

[0108] 0.9ΔP minbm <ΔP min <1.1ΔP minbm

[0109] At that time, the wear was stable due to uneven wear.

[0110] When ΔP min In

[0111] ΔP min ≤0.9ΔP minbm

[0112] At that time, the wear was reduced due to uneven wear.

[0113] When ΔP min In

[0114] ΔP min ≥1.1ΔP minbm

[0115] At this time, an early warning is issued due to increased uneven wear.

[0116] In the second and third scenarios, firstly, during the initial three days after the anti-wear design needs to be completed, check ΔP. min Whether it is qualified, if

[0117] ΔP min >0.15P nmin

[0118] If the design for preventing uneven wear is deemed inadequate, then the risks of leakage and rod breakage due to uneven wear should be closely monitored. Otherwise, proceed as in section 1) of this document.

Claims

1. A method for diagnosing and warning of rod and tubing wear in oil wells under digital conditions, characterized in that, Includes the following steps: Based on the operating data of the pumping unit, the maximum and minimum loads of the theoretical suspension point dynamometer diagram of the pumping unit well are predicted. Daily cluster dynamometer data is obtained by real-time acquisition and processing of surface dynamometer diagrams using on-site equipment at oil wells. Based on the maximum and minimum loads of the theoretical suspension point dynamometer diagram of the pumping unit well and the daily cluster dynamometer diagram data, determine whether the pumping unit well is experiencing uneven wear. Based on the occurrence of uneven wear in the pumping well, an early warning system for uneven wear of the well rod and tubing is implemented. The process of acquiring and processing surface dynamometer maps in real time using on-site oil well equipment specifically involves: At least 48 surface dynamometer maps were collected within 24 hours using digital equipment deployed at the oil well site. The dynamometer maps of start-up and shutdown wells were removed, and the remaining dynamometer maps were used to generate a data sample as the daily cluster dynamometer map data. The daily cluster operation data includes: Mean load Maximum load Minimum load Load fluctuation range Average underload Maximum lower load Minimum underload Load fluctuation range ,in: ； ； The removal of the well start-stop work diagram specifically refers to: If the dynamometer card contains well opening / closing information, then the dynamometer cards for the first half hour after well opening are directly removed; if well opening / closing information cannot be obtained, then the decision to remove the dynamometer card is based on the maximum load value in the dynamometer card, specifically: < ； in, This represents the maximum load value of the i-th power diagram out of the 48 power diagrams for that day. The determination coefficient, The theoretical maximum load on the suspension point dynamometer diagram; The determination of whether the pumping unit well has experienced uneven wear is specifically as follows: If the daily kinetic energy distribution chart data of a pumping unit well meets the following conditions, then the pumping unit well has experienced uneven wear on that day: ； ； ； Where a, b, and c are all wear coefficients. This represents the average load across all loads on the cluster power map. This represents the average load across all loads in the cluster power diagram; The aforementioned early warning system for wear-prone oil well tubing specifically includes: 1) Wells without anti-wear measures experience wear: When the well meets ； ； ； At that time, a suspected wear warning was issued for the well, prompting technicians to analyze the wear condition and take timely preventative measures. The minimum load for the theoretical suspension point dynamometer diagram; 2) Wells with anti-wear measures experience uneven wear: 2.1) If anti-wear does not eliminate buckling, and eccentric wear remains in the daily data, then the first seven days after the well is put into operation will be used. The average value is used as the benchmark. In subsequent production, when on a certain day In ； At that time, the wear was stable due to uneven wear. when In ； At this time, the wear is reduced due to uneven wear. when In ； At this time, an early warning is issued due to increased uneven wear; 2.2) If anti-wear measures reduce or eliminate buckling, then during the first three days of implementing anti-wear measures according to the anti-wear design, [the following applies to]... Conduct an inspection, if ； Therefore, the well's anti-wear design is considered substandard.

2. The method for diagnosing and warning of rod and tubing wear in oil wells under digital conditions according to claim 1, characterized in that, The maximum and minimum loads on the theoretical suspension point dynamometer diagram of the pumping unit well are as follows: ； ； = ； ； ； ； in, The theoretical maximum load on the suspension point dynamometer diagram. The minimum load for the theoretical suspension point indicator diagram. This is the load on the sucker rod string acting on the suspension point during the downstroke. The load on the sucker rod string during the upstroke. R is the liquid column load acting on the plunger during the upstroke, and R is the crank radius of rotation. s is the length of the sucker rod, n is the stroke, and s is the number of strokes. Mass per meter of sucker rod This refers to the mass of each meter of sucker rod in the well fluid. Let be the cross-sectional area of ​​the plunger. The length of the link. The average density of the liquid inside the pipe, The density of steel, This is the acceleration due to gravity.

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