Casing friction coefficient calculation method, application, device, equipment and medium

Abstract

The application provides a casing running friction coefficient calculation method, application, device, equipment and medium, and the method comprises the following steps: acquiring data, including well trajectory parameters, through bottom hole assembly parameters, drilling fluid parameters, through well load data and well depth data; screening data, performing data interpolation on the through bottom hole assembly structure segmentation points, confirming the well depth, well inclination angle and azimuth angle at any position; calculating the dogleg and / or curvature corresponding to the segmentation of the bottom hole assembly structure and the standard drill pipe according to the well depth, well inclination angle and azimuth angle at the any position; confirming the axial load and friction coefficient of each segment, establishing a hook load model, and confirming the hook load; measuring the actual through well hook load data, inverting the optimal comprehensive friction coefficient according to the hook load and the actual through well hook load data; and confirming the casing running friction coefficient according to the optimal comprehensive friction coefficient. The prediction data of the application has high accuracy, and the safety of drilling operation can be improved, and the casing running construction operation can be quickly completed.

Description

Technical Field

[0001] This invention relates to the field of oil drilling engineering, and more specifically, to a method for calculating the friction coefficient of running casing, an application of the method for calculating the friction coefficient of running casing, a device for calculating the friction coefficient of running casing, and equipment and computer-readable storage medium for implementing the method for calculating the friction coefficient of running casing. Background Technology

[0002] With the development of unconventional oil and gas wells, the number of horizontal and extended-reach wells is increasing. The horizontal sections are becoming longer and the wellbore trajectories are more complex, making it difficult to run the casing to the designed depth. Whether the casing can be run to the designed depth is related to its stiffness. The frictional resistance of the casing not only affects whether it can be run to the designed depth but also affects whether the casing buckles and its future lifespan. Therefore, predicting and controlling the frictional resistance is crucial for the successful implementation of extended-reach and horizontal wells, and the value of the frictional resistance coefficient directly affects the applicability of the prediction results. Because the frictional resistance coefficient is affected by many factors such as drilling fluid properties, formation lithology, wellbore trajectory, and cuttings, it is not easy to calculate directly. Therefore, the frictional resistance coefficient is usually obtained by back-calculation using empirical wellbore values ​​and field measurements. Currently, the frictional resistance coefficient can be back-calculated using the following three methods. The methods include: 1) back-calculating using measured drilling torque and drill string suspended weight; 2) back-calculating using measured normal lifting and lowering suspended weight of the drill string in the open hole and upper casing; and 3) back-calculating using measured normal lifting and lowering suspended weight of the casing string in the open hole and upper casing. While the inverse calculation of the friction coefficient after casing installation provides some reference for subsequent casing installations, it cannot accurately guide the casing installation operation for every well due to differences in drilling fluid properties, wellbore trajectory, formation lithology, and cuttings. For example, invention patent CN109869132A discloses a method for calculating the friction coefficient of casing installation. This method obtains friction coefficient values ​​for different types of centralizers and calculates the friction coefficient value through real-time monitoring of hook load data, only allowing calculation of the friction coefficient during actual casing installation. Chinese patent application CN114254499A discloses a method for monitoring drilling operations based on friction coefficient. This method monitors wellbore conditions and operating conditions during drilling operations based on a target friction coefficient. However, the target friction coefficient is the friction coefficient during drilling, and its relationship with the casing friction coefficient is unclear, so it cannot directly guide the prediction and control of casing friction. Summary of the Invention

[0003] The purpose of this invention is to address at least one of the aforementioned shortcomings of the existing technology. For example, one objective of this invention is to provide a method for calculating the casing friction coefficient. This method can calculate the casing friction coefficient based on wellbore friction, thereby improving the accuracy of the casing friction coefficient and providing technical support for the prediction and control of casing friction in horizontal wells and extended reach wells.

[0004] To achieve the above objectives, the present invention provides a method for calculating the friction coefficient of a lower bushing, the method comprising the following steps:

[0005] S1. Acquire data, which may include wellbore trajectory parameters, bottom hole drill string assembly parameters, drilling fluid parameters, well load data, and well depth data.

[0006] S2. Filter the data and perform data interpolation on the segment points of the drilling tool assembly structure at the bottom of the well to confirm the well depth, inclination angle, and azimuth angle at any location.

[0007] S3. Based on the well depth, inclination angle, and azimuth angle at any given location, the dogleg degree and / or curvature of the bottom drill string assembly structure and the corresponding segments of the standard drill pipe can be calculated.

[0008] S4. Confirm the axial load and friction coefficient of each segment, establish the hook load model, and the hook load can be confirmed.

[0009] S5. Measure the actual wellbore hook load data. Based on the hook load and the actual wellbore hook load data, the optimal comprehensive friction coefficient can be derived.

[0010] S6. The friction coefficient of the lower casing can be determined based on the optimal comprehensive friction coefficient.

[0011] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, the data screening may include: taking the average value of the hook load data for well depths less than 100m as the reference load; removing data with hook loads less than 1.1 times the reference load; removing data with rotation speed greater than 1RPM, torque greater than 0.1KN.m, displacement greater than 1L / S, or pressure greater than 0.5MPa; when the well depth is the same, only the data with the largest hook load may be retained; when the well depth trend changes, data with a trend consistent with the two well depth data following the stated well depth data may be retained.

[0012] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, the data interpolation can be linear interpolation, and the well depth, inclination angle, and azimuth angle at any location can be determined according to the well depth model, inclination angle model, and azimuth angle model, respectively. The model can be as follows:

[0013] Well depth model: L = L i +Δl. (1)

[0014] Well inclination angle model:

[0015] Azimuth model:

[0016] Among them, L iLet be the known well depth (m) of measuring point i in the wellbore trajectory; Δl be the distance L to the location to be determined. i Length, m; α i , φ i Given the inclination angle and azimuth angle of measuring point i in the wellbore trajectory, in °; ΔL i Δα is the well depth distance between two adjacent measuring points at the desired location in the wellbore trajectory, in meters; i Δφ represents the change in inclination angle between two adjacent measuring points at the desired location in the wellbore trajectory, in degrees. i Let be the change in azimuth angle between two adjacent measuring points at the location to be determined in the wellbore trajectory, in °.

[0017] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, the dogleg and curvature can be established according to the deformation characteristics of the tubing string in the three-dimensional wellbore, respectively, using a dogleg model and a curvature model. The models can be as follows:

[0018] Dog-like behavior model:

[0019] Curvature model:

[0020] Where γ is the dogleg degree, ° / 30m; α i , φ i For the known inclination angle and azimuth angle of measuring point i in the wellbore trajectory, in °; K is the curvature, ° / m; L i Let be the known well depth (m) of measuring point i in the wellbore trajectory.

[0021] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, the hook load model can be:

[0022]

[0023] in,

[0024]

[0025] T n The axial load at the wellhead is kN; ΔL i γ is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i For measurement point i, the dogleg degree is ° / 30m; q i The weight of the tubular line is expressed in kN / m. The average well inclination angle for this section is α, in degrees. i The well inclination angle at this point is °; μ is the comprehensive friction coefficient; E is the elastic modulus of the tubing string, Pa; I is the moment of inertia of this section of the tubing string, m. 4 k is the curvature, ° / m; T i Let i be the axial load at measuring point i, in kN.

[0026] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, step S5 may include: using an Euler-type optimization algorithm to inversely derive the optimal comprehensive friction coefficient.

[0027] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, step S5 may include: dividing the well into three sections—vertical well section, inclined well section, and horizontal well section—and performing inversion to confirm the optimal comprehensive friction coefficient.

[0028] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, step S5 may include: confirming the initial value and step size of the comprehensive friction coefficient; taking the absolute value of the difference between the hook load and the actual wellbore hook load data as the hook load error; when the hook load error is greater than 0.5, the comprehensive friction coefficient can be iterated; when the hook load error is less than or equal to 0.5, the iteration ends, and the optimal value of the comprehensive friction coefficient can be obtained; when the hook load error is within 0-1, the optimal value of the comprehensive friction coefficient can be the comprehensive friction coefficient when the hook load error is minimized.

[0029] In an exemplary embodiment of the casing friction coefficient calculation method of the present invention, step S6 may include: establishing a friction coefficient model based on the optimal comprehensive friction coefficient to confirm the casing friction coefficient, wherein the friction coefficient model may be:

[0030] μ=S×f e (9)

[0031] Where μ is the friction coefficient of the lower bushing; f e The optimal value for the comprehensive friction coefficient is given by S; S is the influence coefficient of the casing centralizer. When there is one swirl rigid centralizer under each casing, S = 1.0.

[0032] In another aspect, this invention provides a method for calculating the friction coefficient of the lower casing and its application in the prediction and control of lower casing friction.

[0033] In another aspect, the present invention provides a device for calculating the friction coefficient of the lower casing. The device may include a data acquisition module, a data processing module, a dogleg degree confirmation module, a hook load confirmation module, an optimal comprehensive friction coefficient confirmation module, and a lower casing friction coefficient confirmation module.

[0034] The data acquisition module can be configured to acquire wellbore trajectory parameters, bottom hole drill string assembly parameters, drilling fluid parameters, well load data, and well depth data.

[0035] The data processing module can be connected to the data acquisition module and can be configured to filter the data and interpolate the data to determine the well depth, inclination angle, and azimuth angle at any location.

[0036] The dogleg confirmation module can be connected to the data processing module and can be configured to calculate the dogleg and / or curvature of the bottom drill string assembly structure and the corresponding segments of the standard drill pipe based on the well depth, inclination angle, and azimuth angle at any location.

[0037] The hook load confirmation module can be connected to the dogleg confirmation module and can be configured to confirm the axial load and friction coefficient of each segment, establish the hook load model, and confirm the hook load.

[0038] The optimal comprehensive friction coefficient confirmation module can be connected to the hook load confirmation module and can be configured to measure the actual wellbore hook load data, and derive the optimal comprehensive friction coefficient based on the hook load and the actual wellbore hook load data.

[0039] The lower casing friction coefficient confirmation module can be connected to the optimal comprehensive friction coefficient confirmation module and can be configured to confirm the lower casing friction coefficient based on the optimal comprehensive friction coefficient.

[0040] In another aspect, the present invention provides an apparatus comprising:

[0041] Processor; memory storing a computer program that, when executed by the processor, implements at least one of the methods described above for calculating the lower bushing friction coefficient and for applying the lower bushing friction coefficient calculation method in the prediction and control of lower bushing friction.

[0042] In another aspect, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements at least one of the methods described above for calculating the lower bushing friction coefficient and for applying the lower bushing friction coefficient calculation method in the prediction and control of lower bushing friction.

[0043] Compared with the prior art, the beneficial effects of the present invention include at least one of the following:

[0044] (1) The method for calculating the friction coefficient of casing provided by the present invention uses the data of the load of the well hook before casing to inversely derive the friction coefficient of well cleaning, and then confirms the friction coefficient of casing based on the friction coefficient of well cleaning. Therefore, the friction coefficient of casing can be predicted and control measures can be formulated in advance for the well, providing scientific and reasonable opinions and necessary technical support for casing of horizontal wells, extended reach wells and other wells.

[0045] (2) The prediction data of the casing friction coefficient calculation method provided by the present invention has high accuracy, which can effectively improve the safety of drilling operations in oil fields and quickly complete the casing construction operation. Attached Figure Description

[0046] The above and other objects and / or features of the present invention will become clearer from the following description taken in conjunction with the accompanying drawings, in which:

[0047] Figure 1 A schematic diagram illustrating the steps of an example of the method for calculating the friction coefficient of the lower bushing according to the present invention is shown.

[0048] Figure 2 A schematic diagram of the comprehensive friction coefficient inversion process is shown as an example of the method for calculating the friction coefficient of the lower casing according to the present invention.

[0049] Figure 3 A schematic diagram of an example of the device for calculating the friction coefficient of the lower bushing according to the present invention is shown.

[0050] Explanation of reference numerals in the attached figures:

[0051] 100 - Data acquisition module; 110 - Data processing module; 120 - Dogleg degree confirmation module; 130 - Hook load confirmation module; 140 - Optimal comprehensive friction coefficient confirmation module; 150 - Lower casing friction coefficient confirmation module. Detailed Implementation

[0052] In the following sections, the method, application, apparatus, device, and medium for calculating the lower bushing friction coefficient of the present invention will be described in detail with reference to exemplary embodiments.

[0053] It should be noted that "Step 1", "Step 2", "Step 3", etc., are merely for ease of description and distinction, and should not be construed as indicating or implying relative importance. The terms "S1", "S2", "S3", etc., used in this invention are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0054] Currently, extended reach drilling and horizontal drilling are becoming increasingly common. However, due to factors such as the weight of the tubing string and wellbore curvature, tubing strings in highly deviated and horizontal wells exhibit high frictional resistance. Accurate calculation of casing frictional resistance is essential in the completion design and construction of highly deviated and horizontal wells because: ① improving wellbore profile design minimizes casing string running resistance; ② predicting the likelihood of casing string running into the actual drilled wellbore facilitates the selection of the running method; ③ accurately calculating the axial load on the casing string is crucial for casing string strength design and verification. Therefore, accurately predicting the frictional coefficient of the running casing is vital for oil and gas well development.

[0055] To address the aforementioned issues, the inventors proposed a method for calculating the casing friction coefficient. This method can inversely derive the wellbore friction coefficient from the segmented data of the wellbore hook load before casing installation, and then confirm the casing friction coefficient based on the wellbore friction coefficient. The casing friction coefficient predicted using this method has high accuracy.

[0056] To achieve the above objectives, the present invention provides a method for calculating the friction coefficient of a lower casing. In an exemplary embodiment of the method for calculating the friction coefficient of a lower casing according to the present invention, the method may include:

[0057] S1. Acquire data, which may include wellbore trajectory parameters, bottom hole assembly parameters, drilling fluid parameters, well load data, and well depth data.

[0058] S2. Data filtering allows for data interpolation of the segment points of the drilling tool assembly structure at the bottom of the well, confirming the well depth, inclination angle, and azimuth angle at any location.

[0059] Furthermore, the average value of the hook load data for well depths less than 100m can be used as the benchmark load. Data with hook loads less than 1.1 times the benchmark load, as well as data with rotation speeds greater than 1 RPM, torques greater than 0.1 KN.m, displacements greater than 1 L / S, or pressures greater than 0.5 MPa, can be discarded. When the well depth is the same, only the data with the highest hook load can be retained. When the well depth trend changes, only the data with the same trend as the two well depth data following the well depth data can be retained; otherwise, they can be discarded.

[0060] Furthermore, data interpolation can be linear interpolation, and the well depth, inclination angle, and azimuth angle at any location can be determined based on the well depth model, inclination angle model, and azimuth angle model, respectively. The models can be as follows:

[0061] Well depth model: L = L i +Δl. (1)

[0062] Well inclination angle model:

[0063] Azimuth model:

[0064] Among them, L i Let be the known well depth (m) of measuring point i in the wellbore trajectory; Δl be the distance L to the location to be determined. i Length, m; α i , φ i Given the inclination angle and azimuth angle of measuring point i in the wellbore trajectory, in °; ΔL i Δα is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i Δφ represents the change in inclination angle between two adjacent measuring points at the desired location in the wellbore trajectory, in degrees. i Let be the change in azimuth angle between two adjacent measuring points at the location to be determined in the wellbore trajectory, in °.

[0065] S3. Based on the well depth, inclination angle, and azimuth angle at any location, the dogleg degree and / or curvature of the bottom drill string assembly structure and the corresponding segments of the standard drill pipe can be calculated.

[0066] Furthermore, based on the deformation characteristics of the tubing string in a three-dimensional wellbore, dogleg and curvature models can be established separately, as follows:

[0067] Dog-like behavior model:

[0068] Curvature model:

[0069] Where γ is the dogleg degree, ° / 30m; α i , φ i For the known inclination angle and azimuth angle of measuring point i in the well trajectory, in °; K is the curvature, ° / m; L i Let be the known well depth (m) of measuring point i in the wellbore trajectory.

[0070] S4. Confirm the axial load and friction coefficient of each segment, establish the hook load model, and the hook load can be confirmed.

[0071] Furthermore, the load model for the large hook can be:

[0072]

[0073] in,

[0074]

[0075] T n The axial load at the wellhead is kN; ΔL i γ is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i For measurement point i, the dogleg degree is ° / 30m; q i The weight of the tubular line is expressed in kN / m. The average well inclination angle for this section is α, in degrees. i The well inclination angle at this point is °; μ is the comprehensive friction coefficient; E is the elastic modulus of the tubing string, Pa; I is the moment of inertia of this section of the tubing string, m. 4 k is the curvature, ° / m; T i Let i be the axial load at measuring point i, in kN.

[0076] S5. Measure the actual wellbore hook load data. Based on the hook load and the actual wellbore hook load data, the optimal comprehensive friction coefficient can be derived.

[0077] Furthermore, the optimal overall friction coefficient can be derived by using an Euler-type optimization algorithm.

[0078] Furthermore, by performing inversion on three sections—vertical well, inclined well, and horizontal well—the optimal comprehensive friction coefficient can be confirmed.

[0079] Furthermore, confirm the initial value and step size of the comprehensive friction coefficient; the absolute value of the difference between the hook load and the actual wellbore hook load data can be taken as the hook load error. When the hook load error is greater than 0.5, the comprehensive friction coefficient can be iterated; when the hook load error is less than or equal to 0.5, the iteration ends and the optimal value of the comprehensive friction coefficient can be obtained; when the hook load error is within 0-1, the optimal value of the comprehensive friction coefficient can be taken as the comprehensive friction coefficient with the smallest hook load error.

[0080] S6. The friction coefficient of the lower casing can be determined based on the optimal comprehensive friction coefficient.

[0081] Furthermore, the friction coefficient can be determined by establishing a friction coefficient model based on the optimal comprehensive friction coefficient. The friction coefficient model can be:

[0082] μ=S×f e (9)

[0083] Where μ is the friction coefficient of the lower bushing; f e The optimal value for the comprehensive friction coefficient is given by S; S is the influence coefficient of the casing centralizer. When there is one swirl rigid centralizer under each casing, S = 1.0.

[0084] According to another aspect of the present invention, the application of the method for calculating the friction coefficient of the lower casing in the prediction and control of the friction of the lower casing is also provided.

[0085] According to another aspect of the present invention, a device for calculating the friction coefficient of a lower bushing is also provided.

[0086] In an exemplary embodiment of the casing friction coefficient calculation device of the present invention, the casing friction coefficient calculation device may include: a data acquisition module, a data processing module, a dogleg degree confirmation module, a hook load confirmation module, an optimal comprehensive friction coefficient confirmation module, and a casing friction coefficient confirmation module.

[0087] The system includes several modules: a data acquisition module, configured to acquire wellbore trajectory parameters, bottom hole assembly parameters, drilling fluid parameters, well load data, and well depth data; a data processing module, connected to the data acquisition module, configured to filter data and interpolate data to confirm well depth, inclination angle, and azimuth at any location; a dogleg determination module, connected to the data processing module, configured to calculate the dogleg and / or curvature of the bottom hole assembly structure and corresponding segments of the standard drill pipe based on well depth, inclination angle, and azimuth at any location; a hook load determination module, connected to the dogleg determination module, configured to confirm the axial load and friction coefficient of each segment, establish a hook load model, and confirm the hook load; and an optimal comprehensive friction coefficient determination module, connected to the hook load determination module, configured to measure actual well hook load data and derive the optimal comprehensive friction coefficient based on the hook load and actual well hook load data. The lower casing friction coefficient confirmation module can be connected to the optimal comprehensive friction coefficient confirmation module and can be configured to confirm the lower casing friction coefficient based on the optimal comprehensive friction coefficient.

[0088] According to another aspect of the present invention, a computer device is also provided. The computer device includes a processor and a memory. The memory stores a computer program. The computer program is executed by the processor, causing the processor to perform at least one of the computer program for calculating the lower bushing friction coefficient according to the present invention and its application in lower bushing friction prediction and control.

[0089] According to another aspect of the invention, a computer-readable storage medium storing a computer program is also provided. This computer-readable storage medium stores a computer program, when executed by a processor, that causes the processor to perform at least one of the method for calculating the lower bushing friction coefficient according to the invention and its application in lower bushing friction prediction and control. This computer-readable recording medium is any data storage device capable of storing data readable by a computer system. Examples of computer-readable recording media include: read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, optical data storage device, and carrier waves (such as data transmission via the Internet through wired or wireless transmission paths).

[0090] To better understand the exemplary embodiments of the present invention described above, further explanation is provided below with reference to specific examples and accompanying drawings, but the examples given are not intended to limit the present invention.

[0091] Example 1

[0092] In this example, such as Figure 1 As shown, the method for calculating the friction coefficient of the lower bushing can be achieved through the following steps:

[0093] S1. Acquire data, including wellbore trajectory parameters, bottom hole drill string assembly parameters, drilling fluid parameters, wellbore load data, and well depth data;

[0094] More specifically, wellbore trajectory parameters include wellbore diameter, depth, inclination angle, and azimuth. Bottom Hole Assembly (BHA) parameters refer to the geometric dimensions and basic material parameters of the BHA assembly, such as the inner and outer diameters, section lengths, wall thicknesses, densities, unit linear weights, and elastic moduli of the drill bit, stabilizer, drill collars, and drill pipe. Drilling fluid parameters include density and rheological properties.

[0095] More preferably, logging software is used to export logging point data, including well depth, hook load, rotation speed, torque, displacement, and pressure.

[0096] S2. Filter the data and interpolate the data at the segment points of the drilling tool assembly structure at the bottom of the well to confirm the well depth, inclination angle, and azimuth angle at any location.

[0097] More specifically, the average value of the hook load data for well depths less than 100m is taken as the benchmark load; all data with hook loads lower than 1.1 times the benchmark load are discarded; all data with rotational speed greater than 1 RPM, torque greater than 0.1 KN.m, displacement greater than 1 L / S, or pressure greater than 0.5 MPa are discarded; for well depths of the same type, only the maximum hook load value is retained. When the well depth trend changes, only data with a trend consistent with the two well depth data following the current well depth data are retained; otherwise, they are discarded.

[0098] More preferably, after the data screening is completed, a hook load data table corresponding to the well depth location is generated.

[0099] S3. Calculate the dogleg degree and / or curvature of the bottom drill string assembly structure and the corresponding segments of the standard drill pipe based on the well depth, inclination angle, and azimuth angle at any location.

[0100] More specifically, the data interpolation is linear interpolation, and the well depth, inclination angle, and azimuth angle at any location are determined based on the well depth model, inclination angle model, and azimuth angle model, respectively, as follows:

[0101] Well depth model: L = L i +Δl. (1)

[0102] Well inclination angle model:

[0103] Azimuth model:

[0104] Among them, L i Let be the known well depth (m) of measuring point i in the wellbore trajectory; Δl be the distance L to the location to be determined.i Length, m; α i φ i Given the inclination angle and azimuth angle of measuring point i in the wellbore trajectory, in °; ΔL i Δα is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i Δφ represents the change in inclination angle between two adjacent measuring points at the desired location in the wellbore trajectory, in degrees. i Let be the change in azimuth angle between two adjacent measuring points at the location to be determined in the wellbore trajectory, in °.

[0105] More specifically, after interpolating to obtain basic parameters such as well depth, inclination angle, and azimuth angle of the BHA structure segment, the dogleg degree or curvature K of the corresponding segments of the BHA structure and standard drill pipe is calculated using the Lubinsiki recommended formula, based on the deformation characteristics of the tubing string in the three-dimensional wellbore. The calculation model is as follows:

[0106] Dog-like behavior model:

[0107] Curvature model:

[0108] Where γ is the dogleg degree, ° / 30m; α i φ i For the known inclination angle and azimuth angle of measuring point i in the well trajectory, in °; K is the curvature, ° / m; L i Let be the known well depth (m) of measuring point i in the wellbore trajectory.

[0109] S4. Confirm the axial load and friction coefficient of each segment, establish the hook load model, and confirm the hook load.

[0110] The load model for the large hook is as follows:

[0111]

[0112] in,

[0113]

[0114]

[0115] The first term of the recursive formula is:

[0116]

[0117] The intermediate term of the recursive formula is:

[0118]

[0119] T n The axial load at the wellhead is kN; ΔL iγ is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i For measurement point i, the dogleg degree is ° / 30m; q i The weight of the tubular line is expressed in kN / m. The average well inclination angle for this section is α, in degrees. i The well inclination angle at this point is °; μ is the comprehensive friction coefficient; E is the elastic modulus of the tubing string, Pa; I is the moment of inertia of this section of the tubing string, m. 4 k is the curvature, ° / m; T i Let i be the axial load at measuring point i, in kN.

[0120] Generally, T0 = 0, and the axial load and friction coefficient for each segment are known quantities. Substituting these into the above formula, the hook load T at the wellhead can be calculated. n .

[0121] S5. Measure the actual wellbore hook load data, and deduce the optimal comprehensive friction coefficient based on the hook load and actual wellbore hook load data. The wellbore comprehensive friction coefficient deduction process is as follows: Figure 2 As shown, input data (wellbore trajectory and basic tubing parameters, measured hook load data at well depth), confirm the initial value of the friction coefficient, the fixed step size, and the set number of iterations. Update the friction coefficient according to the fixed step size. Calculate the hook load corresponding to the friction coefficient based on the tubing mechanical model. Confirm the optimal friction coefficient based on the hook load error.

[0122] Alternatively, the optimal overall friction coefficient can be derived by using an Euler-type optimization algorithm.

[0123] More specifically, step S5 may also include:

[0124] S51. Establish the hook load error model, which is shown in the following formula:

[0125]

[0126] Where F0 is the calculated value of the hook load, in kN; The actual hook load is measured in KN.

[0127] S52. Iteration of the comprehensive friction coefficient: The comprehensive friction coefficient f is updated by increasing at a fixed step size h, i.e.

[0128] f = f0 + nh. (12)

[0129] f0 is the initial value of the overall friction coefficient; n is a natural number, taking values ​​of 0, 1, 2, ...

[0130] More preferably, based on calculation experience, f0 is greater than 0.12.

[0131] S53. Obtain the optimal overall friction coefficient, if the error Within a reasonable range (i.e.) This can be considered as reaching the optimal level, at which point the overall friction coefficient f is... e That is the optimal value. Otherwise, the calculation error during the optimization process may be relatively large, when 0 <f e <1, and make the error When the minimum value is reached, the overall friction coefficient f is... e That is the optimal value.

[0132] More preferably, the optimal comprehensive friction coefficient can be confirmed by inversion in three sections: vertical well section, inclined well section, and horizontal well section.

[0133] S6. Determine the friction coefficient of the lower casing based on the optimal comprehensive friction coefficient.

[0134] More specifically, the friction coefficient model is as follows:

[0135] μ=S×f e (13)

[0136] Where μ is the friction coefficient of the lower bushing; f e The optimal value for the comprehensive friction coefficient is given by S; S is the influence coefficient of the casing centralizer. When there is one swirl rigid centralizer under each casing, S = 1.0.

[0137] Example 2

[0138] This example provides a method for calculating the friction coefficient of the lower bushing. The technical solution in this example is as follows:

[0139] Step 1: Data input and data processing.

[0140] Data input includes wellbore trajectory parameters, such as wellbore diameter, well depth, inclination angle, and azimuth angle. The obtained data is shown in Table 1. The well depth in this case is 6320m, KOP point is 2656m, point A is 3110m, and point B is 6320m.

[0141] Table 1 Wellbore Trajectory Parameters

[0142]

[0143]

[0144] Data input may also include the geometric dimensions and basic material parameters of the wellbore BHA assembly, such as the inner and outer diameters, section lengths, wall thicknesses, densities, unit linear weights, and elastic moduli of the drill bit, stabilizer, drill collar, stabilizer, and drill pipe. The geometric dimensions and basic material parameters of the wellbore BHA assembly collected in this example are as follows: Φ215.9mm drill bit (inner diameter 72mm) × 0.35m + double-female return valve (inner diameter 72mm) × 0.5m + Φ165.1mm drill collar (inner diameter 72mm) × 9.5m + Φ213.0mm centralizer (inner diameter 72mm) × 1.2m + Φ165.1mm drill collar (inner diameter 72mm) × 9.35m + Φ210.0mm centralizer (inner diameter 72mm) × 1.2m + Φ165.1mm drill collar (inner diameter 72mm) × 9.35m + Φ139.7mm (inner diameter 121mm) × 6290m

[0145] Data input may also include inputting basic drilling fluid parameters such as density and rheology. In this example, the density of the white oil-based drilling fluid is 2.06 g / cm³. 3 .

[0146] More preferably, the data input can also export logging point data from the logging software, including well depth, hook load, rotation speed, torque, displacement, and pressure.

[0147] Data processing can be used to filter out hook load data, or software can be used to automatically filter out hook load data. Data filtering should follow these principles:

[0148] 1. Take the average value of the hook load data for wells with a depth of less than 100m. This value is the reference load.

[0149] 2. All data with hook loads lower than 1.1 times the reference load will be removed.

[0150] 3. All data with a rotational speed greater than 1 RPM, torque greater than 0.1 KN.m, displacement greater than 1 L / S, or pressure greater than 0.5 MPa will be removed.

[0151] 4. For wells with the same depth, only the maximum load value of the hook is retained.

[0152] 5. When the well depth trend changes, only retain the data whose trend is consistent with the two well depth data following the current well depth data; otherwise, discard them.

[0153] Based on the above principles, the hook load data corresponding to the well depth position are obtained as follows.

[0154] Table 2 Hook Load Data Table

[0155]

[0156] Step 2: Interpolate the data for the segment points of the BHA structure.

[0157] Specifically, linear interpolation is performed based on the well depth, inclination angle, and azimuth angle of the corresponding endpoints of each segment of the BHA structure:

[0158] Well depth at any location: L = L i +Δl. (1)

[0159] Inclination angle at any location:

[0160] Orientation angle at any position:

[0161] Among them, L i Let be the known well depth (m) of measuring point i in the wellbore trajectory; Δl be the distance L to the location to be determined. i Length, m; α i φ i Given the inclination angle and azimuth angle of measuring point i in the wellbore trajectory, in °; ΔL i Δα is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i Δφ represents the change in inclination angle between two adjacent measuring points at the desired location in the wellbore trajectory, in degrees. i Let be the change in azimuth angle between two adjacent measuring points at the location to be determined in the wellbore trajectory, in °.

[0162] Step 3: Calculate the dogleg degree of the BHA structure segments. After interpolation to obtain the basic parameters such as well depth, inclination angle, and azimuth angle of the BHA structure segments, calculate the dogleg degree or curvature K of the corresponding segments of the BHA structure and standard drill pipe according to the deformation characteristics of the tubing string in the three-dimensional wellbore, using the Lubinsiki recommended formula. The calculation method is as follows:

[0163]

[0164]

[0165] Where γ is the dogleg degree, ° / 30m; α i φ i For the known inclination angle and azimuth angle of measuring point i in the well trajectory, in °; K is the curvature, ° / m; L i Let be the known well depth (m) of measuring point i in the wellbore trajectory.

[0166] Step 4: Calculate the hook load. The hook load calculation model is as follows:

[0167]

[0168] in,

[0169]

[0170] The first term of the recursive formula is:

[0171]

[0172] The intermediate term of the recursive formula is:

[0173]

[0174] T n The axial load at the wellhead is kN; ΔL i γ is the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; i For measurement point i, the dogleg degree is ° / 30m; q i The weight of the tubular line is expressed in kN / m. The average well inclination angle for this section is α, in degrees. i The well inclination angle at this point is °; μ is the comprehensive friction coefficient; E is the elastic modulus of the tubing string, Pa; I is the moment of inertia of this section of the tubing string, m. 4 k is the curvature, ° / m; T i Let i be the axial load at measuring point i, in kN.

[0175] Generally, T0 = 0, and the axial load and friction coefficient for each segment are known quantities. Substituting these into the above formula, the hook load T at the wellhead can be calculated. n .

[0176] Step 5: Friction coefficient inversion. Friction inversion is performed in three segments: vertical well, inclined well, and horizontal well. The comprehensive friction coefficient is iterated using the inversion formula to obtain the friction coefficient: f. e z = 0.27, f e x = 0.38, f e s = 0.41.

[0177] Step 6: Determine the casing friction coefficient. Since each casing in the horizontal section of this well has one roller rigid centralizer, the centralizer influence coefficient S = 1.0. The casing friction coefficient can be: μ z＝S× fz = 0.27, μ x＝S× f e x = 0.38, μ s＝S× f e s = 0.41.

[0178] The calculation results based on the method for calculating the friction coefficient of the lower bushing provided in this example are shown in Table 3 below. It can be seen that the friction coefficient predicted by this method for each section has a high accuracy and a small error compared with the actual measured friction coefficient.

[0179] Table 3 shows the calculation results of the friction coefficient of the lower casing.

[0180]

[0181] Example 3

[0182] This example demonstrates the application of the method for calculating the lower casing friction coefficient according to the present invention. This method for calculating the lower casing friction coefficient can be the method used in Example 1 or 2.

[0183] This application may include prediction and control of bushing friction, as detailed below:

[0184] Step 1: Obtain the lower casing friction coefficient by inversion as in Example 1 or Example 2. The calculation results of the lower casing friction coefficient in this example are shown in Table 4 below.

[0185] Table 4 shows the calculation results of the lower casing friction coefficient in an example.

[0186]

[0187] Step 2: Input the casing string. The casing string data is shown in Table 5 below.

[0188] Table 5. Data Table of Lower Bushing String

[0189]

[0190]

[0191] Step 3: Interpolate the data at the segment points of the bushing string structure. The interpolation method in this example can be the same as the data interpolation method in Example 1 or 2.

[0192] Step 4: Calculate the dogleg of the casing string structure segments. After interpolation to obtain the basic parameters such as well depth, inclination angle, and azimuth angle of the casing string structure segments, calculate the dogleg or curvature K of the corresponding segments of the casing string structure and standard drill pipe using the Lubinsiki recommended formula, based on the deformation characteristics of the tubing string in the three-dimensional wellbore. The calculation method of the dogleg or curvature K in this example can be the calculation method of Example 1 or 2.

[0193] Step 5: Based on the predicted friction coefficient μ of the lower casing z =0.27, μ x =0.38, μ s =0.41, predicting the lower casing friction and hook load. The predicted lower casing friction and hook load data obtained in this example are shown in Table 6 below.

[0194] Table 6. Predicted data on casing friction and hook load.

[0195]

[0196] Step 6: Based on the budget, the frictional resistance when the casing is in place is 507.31KN and the load on the hook is 498.60KN. Therefore, it is determined that the conventional casing lowering process can be used, and the floating casing lowering process is not necessary.

[0197] Example 4

[0198] This example provides a device for calculating the friction coefficient of a lower bushing, such as... Figure 3 As shown, the device includes a data acquisition module 100, a data processing module 110, a dogleg degree confirmation module 120, a hook load confirmation module 130, an optimal comprehensive friction coefficient confirmation module 140, and a lower sleeve friction coefficient confirmation module 150.

[0199] The data acquisition module 100 is configured to acquire wellbore trajectory parameters, bottom hole drill string assembly parameters, drilling fluid parameters, well load data, and well depth data.

[0200] The data processing module 110 is connected to the data acquisition module 100 and is configured to filter data and interpolate data to confirm the well depth, inclination angle, and azimuth angle at any location.

[0201] The dogleg confirmation module 120 is connected to the data processing module 110 and is configured to calculate the dogleg degree and / or curvature of the bottom drill string assembly structure and the corresponding segment of the standard drill pipe based on the well depth, inclination angle, and azimuth angle at any location.

[0202] The hook load confirmation module 130 is connected to the dogleg degree confirmation module 120 and is configured to confirm the axial load and friction coefficient of each segment, establish the hook load model, and confirm the hook load.

[0203] The optimal comprehensive friction coefficient confirmation module 140 is connected to the hook load confirmation module 130 and is configured to measure the actual wellbore hook load data and deduce the optimal comprehensive friction coefficient based on the hook load and the actual wellbore hook load data.

[0204] The lower bushing friction coefficient confirmation module 150 is connected to the optimal comprehensive friction coefficient confirmation module 140 and is configured to confirm the lower bushing friction coefficient based on the optimal comprehensive friction coefficient.

[0205] Example 5

[0206] This exemplary embodiment provides a computer device, including:

[0207] At least one processor;

[0208] A memory storing program instructions configured to be executed by the at least one processor, the program instructions including instructions for executing the method for calculating the lower bushing friction coefficient according to Example 1 or 2, or instructions for executing the application of the method for calculating the lower bushing friction coefficient according to Example 3.

[0209] Example 6

[0210] This exemplary embodiment provides a computer-readable storage medium.

[0211] The storage medium stores a computer program. When the computer program instructions are executed by a processor, they implement the method for calculating the lower bushing friction coefficient as described in Example 1 or 2, or implement the application of the method for calculating the lower bushing friction coefficient as described in Example 3.

[0212] The computer-readable storage medium can be any data storage device that stores data that can be read by a computer system. Examples of computer-readable storage media include: read-only memory, random access memory, read-only optical disc, magnetic tape, floppy disk, optical data storage device, and carrier waves (such as data transmission via the Internet through wired or wireless transmission paths).

[0213] In summary, the beneficial effects of the present invention include:

[0214] (1) The method for calculating the friction coefficient of casing provided by the present invention uses the data of the load of the well hook before casing to inversely derive the friction coefficient of well cleaning, and then confirms the friction coefficient of casing based on the friction coefficient of well cleaning. Therefore, the friction coefficient of casing can be predicted and control measures can be formulated in advance for the well, providing scientific and reasonable opinions and necessary technical support for casing of horizontal wells, extended reach wells and other wells.

[0215] (2) The prediction data of the casing friction coefficient calculation method provided by the present invention has high accuracy, which can effectively improve the safety of drilling operations in oil fields and quickly complete the casing construction operation.

[0216] Although the present invention has been described above in conjunction with exemplary embodiments and accompanying drawings, those skilled in the art should understand that various modifications can be made to the above embodiments without departing from the spirit and scope of the claims.

Claims

1. A method for calculating the friction coefficient of a lower bushing, characterized in that, The method includes the following steps: S1. Acquire data, including wellbore trajectory parameters, bottom hole drilling tool assembly parameters, drilling fluid parameters, wellbore load data, and well depth data; S2. Filter the data and perform data interpolation on the segment points of the drilling tool assembly structure at the bottom of the well to confirm the well depth, inclination angle, and azimuth angle at any location; S3. Calculate the dogleg degree and / or curvature of the bottom drill string assembly structure and the corresponding segments of the standard drill pipe based on the well depth, inclination angle, and azimuth angle at any location. S4. Confirm the axial load and friction coefficient of each segment, establish the hook load model, and confirm the hook load. S5. Measure the actual wellbore hook load data, and deduce the optimal comprehensive friction coefficient based on the hook load and the actual wellbore hook load data. S6. Determine the friction coefficient of the lower casing based on the optimal comprehensive friction coefficient; Step S5 includes: using an Euler-type optimization algorithm to inversely find the optimal overall friction coefficient; Step S5 includes: dividing the well into three sections—vertical well section, inclined well section, and horizontal well section—and performing inversion to confirm the optimal comprehensive friction coefficient; Step S5 includes: confirming the initial value and step size of the comprehensive friction coefficient; taking the absolute value of the difference between the hook load and the actual wellbore hook load data as the hook load error; when the hook load error is greater than 0.5, iterating the comprehensive friction coefficient; when the hook load error is less than or equal to 0.5, the iteration ends, and the optimal value of the comprehensive friction coefficient is obtained; when the hook load error is within 0-1, the optimal value of the comprehensive friction coefficient is the comprehensive friction coefficient when the hook load error is minimized. Step S6 includes: establishing a friction coefficient model based on the optimal comprehensive friction coefficient to confirm the friction coefficient of the lower casing, wherein the friction coefficient model is: ； （9） in, The friction coefficient of the lower bushing; This represents the optimal value for the overall friction coefficient. S is the influence coefficient of the casing centralizer. When there is one vortex rigid centralizer under each casing, S=1.

0.

2. The method for calculating the friction coefficient of the lower bushing according to claim 1, characterized in that, The filtering of the data includes: For wells with a depth of less than 100m, the average value of the hook load data is taken as the benchmark load. Data with hook load less than 1.1 times the benchmark load are removed, as are data with rotation speed greater than 1 RPM, torque greater than 0.1 KN.m, displacement greater than 1 L / S, or pressure greater than 0.5 MPa. When the well depth is the same, only the data with the largest hook load is retained; When the well depth trend changes, retain the data whose trend is consistent with the two well depth data that follow the stated well depth data.

3. The method for calculating the friction coefficient of the lower bushing according to claim 1, characterized in that, The data interpolation is linear interpolation. The well depth, inclination angle, and azimuth angle at any location are determined based on the well depth model, inclination angle model, and azimuth angle model, respectively. The models are as follows: Ibuka Model: (1) Well inclination angle model: ; (2) Azimuth model: ; (3) in, Known in the wellbore trajectory i Measurement point well depth, m; Distance to the location to be determined L i The length, in meters; , Known in the wellbore trajectory i The inclination angle and azimuth angle of the measuring well are in degrees. Let be the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; The change in inclination angle between two adjacent measuring points at the location to be determined in the wellbore trajectory is expressed in degrees. Let be the change in azimuth angle between two adjacent measuring points at the location to be determined in the wellbore trajectory, in degrees.

4. The method for calculating the friction coefficient of the lower bushing according to claim 1, characterized in that, The dogleg and curvature are established based on the deformation characteristics of the tubing string in a three-dimensional wellbore, respectively, using dogleg and curvature models, as follows: Dog-like behavior model: ; （4） Curvature model: (5) Among them, Dogleg degree, ° / 30m; , Known in the wellbore trajectory i The inclination angle and azimuth angle of the measuring well are in degrees. Curvature, ° / m; Known in the wellbore trajectory i Measurement point well depth, m.

5. The method for calculating the friction coefficient of the lower bushing according to claim 1, characterized in that, The load model for the large hook is as follows: ； （6） in, , , ； （7） ； （8） The axial load at the wellhead is in kN. Let be the well depth distance between two adjacent measuring points at the location to be determined in the wellbore trajectory, in meters; for i Measuring point dogleg degree, ° / 30m; The weight of the tubular line is expressed in kN / m. The average well inclination angle for this section is in degrees. The inclination angle at this point is in degrees; The overall friction coefficient; Let be the elastic modulus of the tubular column, in Pa; Let m be the moment of inertia of this section of the tubing. 4 ; Curvature, ° / m; for i Axial load at the measuring point, kN.

6. The application of the method for calculating the friction coefficient of the lower casing as described in any one of claims 1-5 in the prediction and control of lower casing friction.

7. A device for calculating the friction coefficient of a lower bushing, characterized in that, The device is used to implement the method for calculating the friction coefficient of the lower casing as described in any one of claims 1-5, and includes a data acquisition module, a data processing module, a dogleg degree confirmation module, a hook load confirmation module, an optimal comprehensive friction coefficient confirmation module, and a lower casing friction coefficient confirmation module, wherein, The data acquisition module is configured to acquire wellbore trajectory parameters, bottom hole assembly parameters, drilling fluid parameters, well load data, and well depth data. The data processing module is connected to the data acquisition module and is configured to filter the data and interpolate the data to confirm the well depth, inclination angle, and azimuth angle at any location; The dogleg determination module is connected to the data processing module and is configured to calculate the dogleg degree and / or curvature of the bottom drill string assembly structure and the corresponding segment of the standard drill pipe based on the well depth, inclination angle, and azimuth angle at any location. The hook load confirmation module is connected to the dogleg degree confirmation module and is configured to confirm the axial load and friction coefficient of each segment, establish the hook load model, and confirm the hook load. The optimal comprehensive friction coefficient confirmation module is connected to the hook load confirmation module and is configured to measure the actual well-drain hook load data and deduce the optimal comprehensive friction coefficient based on the hook load and the actual well-drain hook load data. The lower casing friction coefficient confirmation module is connected to the optimal comprehensive friction coefficient confirmation module and is configured to confirm the lower casing friction coefficient based on the optimal comprehensive friction coefficient.

8. A computer device, characterized in that, include: At least one processor; A memory storing program instructions configured to be executed by the at least one processor, the program instructions including instructions for performing the method for calculating the friction coefficient of the lower bushing according to any one of claims 1-5.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method for calculating the friction coefficient of the lower bushing as described in any one of claims 1-5.

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