Method and device for predicting fatigue fracture of drill string in deep well shallow layer large dogleg section

Abstract

The application provides a deep well shallow layer large dogleg well section drill string fatigue fracture prediction method and device, the method comprises the following steps: determining the stress parameters of the drill string according to the drilling well section engineering parameters; establishing the drill string fatigue crack propagation rate calculation model according to the stress parameters; and predicting the drill string fatigue strength according to the drill string fatigue crack propagation rate calculation model. The application realizes the deep well full well section drill string cumulative fatigue strength prediction and fatigue fracture risk early warning, guides the on-site operator to optimize the process measures and construction parameters, timely trips and changes the drill string, and guarantees the safety of the drill string in the deep well and ultra-deep well drilling process. In order to avoid the frequent drill string fracture accidents caused by the drill string fatigue in the deep well shallow layer large dogleg well section, the application provides a low-cost method with strong timeliness and easy popularization and application, improves the scientific and intelligent level of deep well and ultra-deep well drilling, and provides support for future digital and automatic drilling.

Description

Technical Field

[0001] This invention relates to the field of oil and gas development technology, particularly to the field of designing drilling risk monitoring and early warning systems for oil and gas exploration and development, specifically to a method and device for predicting drill string fatigue fracture in shallow deep well sections with large doglegs. Background Technology

[0002] In recent years, deep oil and gas has become an important energy alternative. In particular, the efficient development of ultra-deep oil and gas resources, especially those deeper than 8,000 meters, is the focus and hot topic of current and future oil and gas exploration and development.

[0003] With the increase in the number of deep and ultra-deep wells, the problems of drill string breakage and drill string leakage in large-diameter wells and deep formations are increasing. Among them, frequent drill string breakage in shallow dogleg sections of deep wells is the main problem faced by deep well drill strings. In some cases, the handling of drill string breakage accidents has led to secondary downhole problems such as stuck pipe, drill string breakage, and failure to retrieve the drill string, resulting in well filling and sidetracking. These problems affect the drilling cycle and restrict the improvement of the quality and efficiency of deep well drilling.

[0004] In existing technologies, methods for predicting and evaluating wellbore drill string fatigue failure during drilling mainly fall into two categories: non-destructive testing (NDT) of the drill string and drill string fatigue life prediction. NDT primarily relies on ultrasonic waves, electromagnetic waves, and metal magnetic memory to detect and identify drill string cracks. The paper "An Early Monitoring Method for Drill String Fatigue Damage Based on Metal Magnetic Memory" proposes using metal magnetic memory to detect drill string fatigue damage by studying the relationship between fatigue stress characteristics at the drill string's meshing thread and the gradient value of the tangential component of the magnetic memory signal, and conducts related laboratory experiments. While this type of method can effectively detect existing fatigue cracks in the drill string, it cannot assess the risk of fatigue fracture in the section of the drill string to be drilled. Furthermore, this method requires testing the entire drill string throughout the well, which is time-consuming, labor-intensive, and costly.

[0005] The second type of method is based on the stress characteristics of the drill string in the wellbore. It uses the SN curve relationship between drill string stress load and material fatigue life or the stress load and drill string defect (crack) propagation model to predict the fatigue life of the drill string. The invention patent "A Method for Predicting the Remaining Life of Drill Pipe" (CN 106840873 A) considers the discrete nature of the drill pipe fatigue life itself. It selects 1 to 2 drill pipes with the worst service conditions from the same batch of drill pipes, and calculates the probability density function of the logarithmic average fatigue life of n samples by completing a large number of drill string samples under the same load. By integrating the probability density function, the fatigue life under the required reliability under the load condition is obtained. This method effectively avoids the discrete nature of the drill pipe fatigue life itself. However, it has the problems of large sample selection and testing workload in the laboratory, long time consumption and high cost.

[0006] Secondly, the invention patent "An Evaluation Method for Drill String Fatigue Failure Risk" (CN 103967428 A) considers the impact of high-frequency alternating stress generated by drill string vibration (axial, lateral whirl, stick-slip) on drill string fatigue life, which is not taken into account in traditional static models. Based on the finite element model of drill string dynamics, it obtains the buckling stress, corrected dynamic bending stress, and dynamic axial stress distribution of each node section of the drill string throughout the well, and then obtains the fatigue frequency coefficient of each node of the drill string throughout the well. Based on this, it completes the fatigue fracture failure risk assessment of the drill string throughout the well, and optimizes the drill string structural parameters and drilling parameters. This method fully considers the dynamic stress characteristics of the drill string in the wellbore and completes the fatigue failure risk assessment of the drill string under dynamic stress based on this method. However, considering that drill string fatigue under complex alternating stress has a time accumulation effect, the calculation volume of this method for long-term, large-scale, whole-well drill string cumulative fatigue failure risk assessment is huge, time-consuming, and has poor practicality in drilling sites. Meanwhile, the breakage of drill strings in shallow deep wells with large doglegs is mainly concentrated in the upper large dogleg section during drilling (reaming) of the lower formation of deep wells. Compared with the bending stress caused by the dogleg of the wellbore, the bending stress caused by drill string vibration is smaller and is not the main cause of rapid fatigue fracture of the drill string.

[0007] In summary, existing technologies lack timely, easy-to-promote, and low-cost methods or means to address the problem of frequent drill string breakage in shallow dogleg sections of deep wells. Summary of the Invention

[0008] To address the problems in existing technologies, the present invention proposes a method and device for predicting drill string fatigue fracture in shallow deep well dogleg sections. This method enables the prediction of cumulative fatigue strength of the drill string throughout the entire deep well section and provides early warning of fatigue fracture risks. It guides on-site operators to optimize process measures and construction parameters, and to promptly trip and replace drill strings, ensuring drill string safety during deep and ultra-deep well drilling. To avoid frequent drill string failures caused by drill string fatigue in shallow deep well dogleg sections, this invention provides a timely, easy-to-promote, and low-cost method, improving the scientific and intelligent level of deep and ultra-deep well drilling and providing support for future digital and automated drilling.

[0009] In a first aspect, the present invention provides a method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells, comprising:

[0010] Determine the stress parameters of the drill string based on the engineering parameters of the drilling section;

[0011] A calculation model for the fatigue crack propagation rate of the drill string is established based on the stress parameters.

[0012] The fatigue strength of the drill string is predicted based on the drill string fatigue crack propagation rate calculation model.

[0013] In one embodiment, the engineering parameters include drilling engineering parameters and wellbore engineering parameters;

[0014] The drilling parameters include: drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, and drilling fluid density;

[0015] The wellbore engineering parameters include: wellbore structure, well inclination, and drill string assembly.

[0016] In one embodiment, the stress parameters include: bending stress, axial stress, shear stress, circumferential stress, and tangential stress values.

[0017] In one embodiment, establishing a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters includes:

[0018] Based on the drill string crack propagation assessment method, a calculation model for the fatigue crack propagation rate of the drill string is established according to the maximum stress difference, minimum stress difference, F-crack geometry factor, cross-sectional stress ratio, fracture toughness index of drill string material, initial crack size, critical crack size, and material constants.

[0019] In one embodiment, predicting the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model includes:

[0020] According to the drill string fatigue crack propagation rate calculation model, the cross section is calculated to reach the fatigue fracture corresponding cycle number at each calculation node.

[0021] The relative fatigue coefficient of the drill string at each calculation node is determined based on the actual number of rotations of the drill string.

[0022] The cumulative fatigue coefficient of the drilling section is calculated based on the relative fatigue coefficient of the drill string at each calculation node.

[0023] The cumulative fatigue coefficient of the drilled section is determined based on the cumulative fatigue coefficient of drilling multiple cross-sections to predict the fatigue strength of the drill string.

[0024] In one embodiment, the method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells further includes:

[0025] When the cumulative fatigue coefficient of the drilled section exceeds a preset threshold, reduce the rotation speed, increase the mechanical drilling rate, and replace the drill string assembly until the cumulative fatigue coefficient of the drilled section is less than the preset threshold.

[0026] Secondly, the present invention provides a device for predicting drill string fatigue fracture in shallow deep well dogleg sections, the device comprising:

[0027] The stress parameter determination module is used to determine the stress parameters of the drill string based on the engineering parameters of the drilling section.

[0028] The calculation model establishment module is used to establish a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters.

[0029] The fatigue strength prediction module is used to predict the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model.

[0030] In one embodiment, the engineering parameters include drilling engineering parameters and wellbore engineering parameters;

[0031] The drilling parameters include: drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, and drilling fluid density;

[0032] The wellbore engineering parameters include: wellbore structure, well inclination, and drill string assembly.

[0033] In one embodiment, the stress parameters include: bending stress, axial stress, shear stress, circumferential stress, and tangential stress values.

[0034] In one embodiment, the computational model building module includes:

[0035] The calculation model establishment unit is used to establish a calculation model for the fatigue crack propagation rate of the drill string based on the drill string crack propagation assessment method, according to the maximum stress difference, minimum stress difference, F-crack geometry factor, cross-sectional stress ratio, fracture toughness index of drill string material, initial crack size, critical crack size, and material constants.

[0036] In one embodiment, the fatigue strength prediction module includes:

[0037] The cycle calculation unit is used to calculate the cycle number corresponding to the fatigue fracture of the cross section at each calculation node according to the drill string fatigue crack propagation rate calculation model.

[0038] The relative fatigue coefficient determination unit is used to determine the relative fatigue coefficient of the drill string at each calculation node based on the actual number of rotations of the drill string.

[0039] The cumulative fatigue coefficient calculation unit is used to calculate the cumulative fatigue coefficient of the drilling section based on the relative fatigue coefficient of the drill string at each calculation node.

[0040] The fatigue strength prediction unit is used to determine the cumulative fatigue coefficient of the drilled section based on the cumulative fatigue coefficient of drilling multiple cross-section well sections, so as to predict the fatigue strength of the drill string.

[0041] In one embodiment, the drill string fatigue fracture prediction device for shallow dogleg sections in deep wells further includes:

[0042] The drilling mode change module is used to reduce the rotation speed, increase the mechanical drilling speed, and change the drill string assembly when the cumulative fatigue coefficient of the drilled section exceeds a preset threshold, until the cumulative fatigue coefficient of the drilled section is less than the preset threshold.

[0043] Thirdly, the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of a method for predicting fatigue fracture of the drill string in shallow deep well dogleg sections.

[0044] Fourthly, the present invention provides an electronic device, including a memory, a processor, and a deterministic program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of a method for predicting fatigue fracture of the drill string in shallow deep well dogleg sections.

[0045] Fifthly, the present invention provides a deterministic machine-readable storage medium storing a deterministic machine program thereon, which, when executed by a processor, implements the steps of a method for predicting fatigue fracture of the drill string in shallow deep well dogleg sections.

[0046] As can be seen from the above description, the method and device for predicting drill string fatigue fracture in shallow deep well dogleg sections provided in this embodiment of the invention first determines the stress parameters of the drill string based on the engineering parameters of the drilling section; then, a calculation model for the fatigue crack propagation rate of the drill string is established based on the stress parameters; finally, the fatigue strength of the drill string is predicted based on the calculation model for the fatigue crack propagation rate of the drill string.

[0047] This invention can be used for predicting the cumulative fatigue strength of drill strings and providing early warning of fatigue fracture risks in deep wells. It guides on-site operators to optimize process measures and construction parameters, and to promptly pull out and replace drill strings, ensuring drill string safety during deep and ultra-deep well drilling. It can avoid frequent drill string breakage accidents caused by drill string fatigue in shallow dogleg sections of deep wells. It has the technical effects of being timely, easy to promote and apply, and low-cost digital methods, improving the scientific and intelligent level of deep and ultra-deep well drilling, and can provide support for future digital and automated drilling. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a flowchart illustrating the method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells according to an embodiment of the present invention. Figure 1 ;

[0050] Figure 2 This is a flowchart illustrating step 200 in an embodiment of the present invention;

[0051] Figure 3 This is a flowchart illustrating step 300 in an embodiment of the present invention;

[0052] Figure 4 This is a flowchart illustrating the method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells according to an embodiment of the present invention. Figure 2 ;

[0053] Figure 5 The flowchart illustrates the steps for calculating the cumulative fatigue coefficient of the drill string during well drilling in a specific application example of this invention.

[0054] Figure 6 This is a flowchart illustrating the risk assessment and early warning of fatigue fracture of the drill string in the section to be drilled in a specific application example of the present invention.

[0055] Figure 7 This is a design drawing of the five-section wellbore structure of Well CT1 in a specific application example of the present invention;

[0056] Figure 8 This is a schematic diagram showing the locations of the two drill string breakage points in well CT1 in a specific application example of the present invention;

[0057] Figure 9 This is a schematic diagram of the cumulative fatigue index of the drill string in the first to third well sections of well CT1 in a specific application example of the present invention;

[0058] Figure 10 This is a schematic diagram of the cumulative fatigue index of the drill string in the fourth to fifth well sections of well CT1, as a specific application example of the present invention.

[0059] Figure 11 This is a schematic diagram showing the distribution of the cumulative fatigue coefficient of the entire well after the completion of the fifth section of the CT1 well under different rotation speeds and mechanical drilling rates in a specific application example of the present invention.

[0060] Figure 12 This is a schematic diagram showing the distribution of mechanical drilling speed and rotation speed in the fifth section of well CT1, a specific application example of the present invention.

[0061] Figure 13 This is a schematic diagram illustrating the composition of the drill string fatigue fracture prediction device for shallow deep well dogleg sections in an embodiment of the present invention. Figure 1 ;

[0062] Figure 14 This is a schematic diagram of the composition of the computational model establishment module 20 in an embodiment of the present invention;

[0063] Figure 15 This is a schematic diagram of the composition of the fatigue strength prediction module 30 in an embodiment of the present invention;

[0064] Figure 16 This is a schematic diagram illustrating the composition of the drill string fatigue fracture prediction device for shallow deep well dogleg sections in an embodiment of the present invention. Figure 2 ;

[0065] Figure 17 This is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. Detailed Implementation

[0066] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0067] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or deterministic program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a deterministic program product implemented on one or more deterministic storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing deterministic program code.

[0068] It should be noted that the terms "comprising" and "having" and any variations thereof in the specification, claims and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product or device.

[0069] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0070] An embodiment of the present invention provides a specific implementation method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells. See [link to implementation details]. Figure 1 The method specifically includes the following:

[0071] Step 100: Determine the stress parameters of the drill string based on the engineering parameters of the drilling section;

[0072] Specifically, based on the drilling engineering parameters of the drilling section (drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, drilling fluid density, etc.) and the wellbore engineering parameters (well structure, well inclination, drill string assembly, etc.), the stress values ​​of bending stress, axial stress, shear stress, circumferential stress, and tangential stress of a certain section of the drill string are obtained.

[0073] Step 200: Establish a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters;

[0074] Based on the drill string crack propagation assessment method, a calculation model for the fatigue crack propagation rate of the drill string based on initial defects is established to obtain the number of cycles corresponding to fatigue fracture at a certain calculation node. The calculation method is as follows:

[0075]

[0076] In the above formula: N is the number of cycles corresponding to the fatigue fracture at the selected section calculation node, dimensionless; Δσ is the maximum and minimum stress difference of the calculated section, MPa; F is the crack geometry factor, dimensionless; R x Section stress ratio, dimensionless; K IC Fracture toughness index of drill string material, MPa·m 1 / 2 ;a0、a c Initial and critical crack sizes, m; c and m are material constants, dimensionless.

[0077] Step 300: Predict the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model.

[0078] Specifically, based on the drill string fatigue crack propagation rate calculation model in step 300, the cumulative fatigue coefficient of the drill string for each drilling run in the drilled section of the wellbore is calculated to predict the drill string fatigue strength.

[0079] As can be seen from the above description, the method for predicting drill string fatigue fracture in shallow deep well dogleg sections provided by the embodiments of the present invention first determines the stress parameters of the drill string based on the engineering parameters of the drilling section; then, a calculation model for the fatigue crack propagation rate of the drill string is established based on the stress parameters; finally, the fatigue strength of the drill string is predicted based on the calculation model for the fatigue crack propagation rate of the drill string.

[0080] This invention addresses the problems of existing drill string fatigue failure prediction and evaluation methods, such as long processing time, high cost, low timeliness, and insufficient specificity. It proposes a method for calculating the cumulative fatigue strength of the drill string based on an initial defect propagation model. This method includes a calculation method for the cumulative fatigue strength of the drill string based on the initial defect propagation model, as well as a pre-drilling and ongoing drill string fatigue fracture risk verification process based on the calculation method. This enables prediction of the cumulative fatigue strength of the drill string and early warning of fatigue fracture risks throughout the deep well section. It guides on-site operators to optimize process measures and construction parameters, and to promptly trip and replace the drill string, ensuring drill string safety during deep and ultra-deep well drilling. To avoid frequent drill string failures due to drill string fatigue in shallow dogleg sections of deep wells, this invention provides a low-cost, time-efficient, and easily applicable digital method.

[0081] In one embodiment, the engineering parameters include drilling engineering parameters and wellbore engineering parameters;

[0082] The drilling parameters include: drilling pressure, rotation speed, torque, stand pressure, and drilling fluid density;

[0083] The wellbore engineering parameters include: wellbore structure, well inclination, and drill string assembly.

[0084] In one embodiment, the stress parameters include: bending stress, axial stress, shear stress, circumferential stress, and tangential stress.

[0085] In one embodiment, see Figure 2 Step 200 includes:

[0086] Step 201: Based on the drill string crack propagation assessment method, establish a calculation model for the fatigue crack propagation rate of the drill string according to the maximum stress difference, minimum stress difference, F-crack geometry factor, cross-sectional stress ratio, fracture toughness index of drill string material, initial crack size, critical crack size, and material constants.

[0087] In one embodiment, see Figure 3 Step 300 includes:

[0088] Step 301: Calculate the number of cycles corresponding to fatigue fracture at each calculation node based on the drill string fatigue crack propagation rate calculation model.

[0089] The cross section reaches the fatigue fracture cycle corresponding to the engineering parameters at each calculation node.

[0090] Step 302: Determine the relative fatigue coefficient of the drill string at each calculation node based on the actual number of rotations of the drill string;

[0091] Step 303: Calculate the cumulative fatigue coefficient of the drilling section based on the relative fatigue coefficient of the drill string at each calculation node;

[0092] In steps 302 and 303, the relative fatigue coefficient of the drill string at each calculation node is obtained based on the actual number of rotations of the drill string. The relative fatigue coefficients of each calculation node in the well section are accumulated to obtain the cumulative fatigue coefficient of the well section drilling of the calculation section.

[0093] Calculate the relative fatigue coefficient of the nodes:

[0094] In the above formula: n i Δl is the relative fatigue coefficient of the cross section at the calculation node, dimensionless; RPM is the drill string rotation speed at the calculation node, r / min; ROP is the mechanical drilling rate at the calculation node, m / h; Δl i To calculate the advance length at the node, in meters (m);

[0095] Step 304: Determine the cumulative fatigue coefficient of the drilled section based on the cumulative fatigue coefficient of drilling multiple cross-sections to predict the fatigue strength of the drill string.

[0096] The drill string of the well section is divided into k calculation sections according to the requirements, and the cumulative fatigue coefficient distribution of each calculation section of the drill string of the whole well section is calculated according to formula (3).

[0097] Cumulative fatigue coefficient of μ nodes in the cross-section drilling section:

[0098] In one embodiment, see Figure 4 Methods for predicting drill string fatigue fracture in shallow dogleg sections of deep wells also include:

[0099] Step 400: When the cumulative fatigue coefficient of the drilled section exceeds a preset threshold, reduce the rotation speed, increase the mechanical drilling rate, and replace the drill string assembly until the cumulative fatigue coefficient of the drilled section is less than the preset threshold.

[0100] Specifically, based on the distribution of the cumulative fatigue coefficient of the drill string throughout the well to the target well depth, the maximum cumulative fatigue coefficient value and location of the drill string are determined, and the maximum cumulative fatigue coefficient is compared to see if it reaches the specified threshold.

[0101] If the specified threshold is exceeded, the maximum cumulative fatigue coefficient of the drill string in the whole well is calculated and updated after changing drilling parameters (reducing rotation speed, increasing mechanical drilling speed), (replacing) drill string assembly, and other process measures until it is less than the specified threshold. If the maximum cumulative fatigue coefficient of the drill string in the whole well is still greater than the threshold after changing drilling parameters (reducing rotation speed, increasing mechanical drilling speed), replacing drill string, and other process measures, the new drill string will be used for drilling the whole well during the drilling process of the drilling section.

[0102] Drilling is carried out based on optimized drilling parameters and process measures. During the actual drilling of the section to be drilled, the actual mechanical drilling speed is compared with the set mechanical drilling speed. If it is reached, drilling continues. If it is not reached, the actual cumulative fatigue coefficient distribution of the whole well drill string is calculated and updated to determine whether the maximum cumulative fatigue coefficient of the whole well drill string has reached the specified threshold. Before reaching the threshold A, the drill string with a cumulative fatigue coefficient greater than the specified threshold in the wellbore is pulled out and discarded.

[0103] This invention addresses the problems of existing drill string fatigue failure prediction and evaluation methods, such as long processing time, high cost, low timeliness, and insufficient specificity. It proposes a method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells. This method includes: determining the stress parameters of the drill string based on the engineering parameters of the drilling section; establishing a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters; and predicting the fatigue strength of the drill string based on the calculation model. This invention enables prediction of the cumulative fatigue strength of the drill string throughout the entire deep well section and provides early warning of fatigue fracture risks. It guides on-site operators to optimize process measures and construction parameters, enabling timely tripping and drill string replacement, ensuring drill string safety during deep and ultra-deep well drilling. To avoid frequent drill string failures due to drill string fatigue in shallow dogleg sections of deep wells, this invention provides a timely, easily applicable, and low-cost method, improving the scientific and intelligent level of deep and ultra-deep well drilling and providing support for future digital and automated drilling.

[0104] To further illustrate this solution, this invention also provides a specific application example of the drill string fatigue fracture prediction method for shallow dogleg sections in deep wells, using CT1 in a certain region as an example. (See [link to relevant documentation]). Figure 5 as well as Figure 6 The specific application example includes the following content.

[0105] See Figure 7 Well CT1 employs a five-section wellbore structure. During the drilling of the fourth section (Ф241.3mm), two drill string failures occurred in the upper section. The two failures occurred at depths of 4751.28m and 5155.05m, respectively, with the break points located at depths of 1715.81m and 1715m. Comparison revealed that both drill string failures occurred in the shallow dogleg section of the well. Figure 8 After two drill string breakage incidents, drill string retrieval was carried out. Drilling continued after handling the complexities of the incidents, reaching a depth of 5155.5m and completing the fourth section. Considering the presence of shallow doglegs in the upper 1600-1620m and 1720-1740m sections of the fifth section (5155.5m-5850m), the axial stress on the drill string in the fifth section is greater than in the fourth section. There is a risk of renewed fatigue fracture of the drill string in the shallow dogleg section during drilling. Based on innovative technical methods and calculation techniques, a pre-drilling full-well drill string fatigue fracture risk analysis and early warning system was conducted for the fifth section.

[0106] S1: Calculate the cumulative fatigue coefficient of the drill string during the drilling process;

[0107] Specifically, step S1 includes:

[0108] S11: Based on the drilling engineering parameters of the drilling section (drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, drilling fluid density, etc.) and the wellbore engineering parameters (well structure, well inclination, drill string assembly, etc.), obtain the stress values ​​of bending stress, axial stress, shear stress, circumferential stress, tangential stress, etc. of a certain section of the drill string.

[0109] S12: Based on the stress results, the equivalent composite stress of the cross section is obtained, and the average stress and stress amplitude of the calculated cross section are obtained.

[0110] S13: Establish a calculation model for the fatigue crack propagation rate of the drill string.

[0111] Based on the drill string crack propagation assessment method, a calculation model for the fatigue crack propagation rate of the drill string based on initial defects is established, as detailed in formula (1).

[0112] S14: Calculate the cumulative fatigue coefficient of the drilling section.

[0113] Obtain the engineering parameters corresponding to each calculation node of the cross section in the well section. Repeat steps S11, S12, and S13 to obtain the number of cycles corresponding to fatigue fracture of the cross section under the corresponding engineering parameters at each calculation node. Obtain the relative fatigue coefficient of the drill string at each calculation node based on the actual number of rotations of the drill string. Add up the relative fatigue coefficients of each calculation node of the cross section in the well section to obtain the cumulative fatigue coefficient of the drilling of the calculated cross section in the well section.

[0114] S2: Risk assessment and early warning of fatigue fracture of the drill string in the well section to be drilled under different technological measures and drilling parameters.

[0115] Specifically, step S2 includes:

[0116] S21: According to the method for calculating the cumulative fatigue coefficient of the drill string in step S1, calculate the cumulative fatigue coefficient of the drill string for each drilling trip in the drilled section of the wellbore, and sum the cumulative fatigue coefficients of the drill string in each drilling trip to obtain the distribution of the cumulative fatigue coefficient of the drill string in the entire wellbore at the current well depth.

[0117] S22: Following the method for calculating the cumulative fatigue coefficient of the drill string in step S1, calculate the distribution of the cumulative fatigue coefficient of the drill string in the whole well when the section to be drilled reaches the target well depth under the current process measures (drill string combination, drilling fluid density, etc.) and drilling parameters (drilling pressure, rotation speed, mechanical drilling speed). Combine this with the distribution of the cumulative fatigue coefficient of the drill string in the upper drilled section, and sum them up to obtain the distribution of the cumulative fatigue coefficient of the drill string in the whole well when the section to be drilled reaches the target well depth under the current process measures and drilling parameters.

[0118] S23: Based on the distribution of the cumulative fatigue coefficient of the drill string in the section to be drilled to the target well depth, determine the value and location of the maximum cumulative fatigue coefficient of the drill string in the whole well, and compare whether the maximum cumulative fatigue coefficient reaches the specified threshold A;

[0119] S24: If the specified threshold A is exceeded, calculate and update the maximum cumulative fatigue coefficient of the drill string after changing drilling parameters (reducing rotation speed, increasing mechanical drilling speed), (replacing) drill string assembly, etc., until it is less than the specified threshold A. If the maximum cumulative fatigue coefficient of the drill string is still greater than the threshold A after changing drilling parameters (reducing rotation speed, increasing mechanical drilling speed), replacing drill string, etc., the new drill string will be used for drilling the entire well during the drilling process of the drilling section.

[0120] S25: Drill according to the optimized drilling parameters and process measures. During the actual drilling of the section to be drilled, compare whether the actual mechanical drilling speed has reached the set mechanical drilling speed. If it has, continue drilling. If it has not, calculate and update the distribution of the actual cumulative fatigue coefficient of the whole well drill string, and determine whether the maximum cumulative fatigue coefficient of the whole well drill string has reached the specified threshold A. Before reaching the threshold A, pull out the drill string in the wellbore with a cumulative fatigue coefficient greater than B, and repeat steps S21 to S24.

[0121] First, based on the wellbore engineering parameters and drilling engineering parameters, the cumulative fatigue coefficient distribution of the drill string for the first to third sections of the CT well (well depth 0-4480m) was calculated. According to the well history records, after the completion of the third section, the drill string was switched. For well depths below 2850m, the drill string was switched to the position facing upwards from the drill bit, and for well depths above 2850m, the drill string was switched to the position facing downwards from the wellhead. The cumulative fatigue index distribution of the drill string for each drilling run in sections one to three, and the cumulative fatigue index distribution of the drill string in sections one to three before and after the drill string switching are shown in [reference needed]. Figure 9 Calculation and analysis revealed that the maximum cumulative fatigue index of the drill string in the first to third well sections did not reach the specified threshold A.

[0122] Next, based on the calculated cumulative fatigue index distribution of the drill string in sections one through three after drill string switching, the cumulative fatigue index of the drill string was iteratively updated after the completion of section four. Following the innovative technical approach, the drilling speed and mechanical drilling rate for section five were adjusted to 40 r / min and 4 m / h, respectively. The cumulative fatigue index distribution of the drill string after drilling to the designed completion depth of 5850 m in section five with the set drilling parameters was calculated. The calculation revealed that the maximum cumulative fatigue index of the drill string exceeded the threshold A. Following the innovative technical approach, after the completion of section four, the drill string above 1750 m was switched to the drill bit facing upwards, and the drill string below 1750 m was switched to the wellhead facing downwards. The cumulative fatigue index distribution of the drill string after drilling to the designed completion depth in section five with 40 r / min and 4 m / h was calculated and superimposed again. It was found that the maximum cumulative fatigue index of the drill string was still greater than the threshold A. Figure 10 .

[0123] 1) Based on the calculation and verification results, after the completion of the fourth drilling phase, the entire well was pulled out and new drill strings were replaced. The cumulative fatigue index distribution of the drill string was calculated for different combinations of mechanical drilling speed and rotation speed (80 r / min, 1.5 m / h; 60 r / min, 3 m / h; 40 r / min, 4 m / h; 50 r / min, 2.5 m / h; 70 r / min, 5 m / h) to the designed completion depth of the fifth drilling phase. See [Figure showing...] Figure 11 According to the analysis, the simulation analysis determined that when drilling at a rotation speed of 80 r / min and 1.5 m / h in the fifth well section, the maximum cumulative fatigue index of the wellbore drill string exceeded the critical threshold A. When drilling with other mechanical drilling speed and rotation speed combinations, the cumulative fatigue index of the drill string for the entire well was less than the threshold A.

[0124] 2) Based on the calculation and analysis results, the upper limit of the drilling speed for the fifth well section is set at 60 r / min, and the lower limit of the mechanical drilling speed is set at 3 m / h. The actual drilling speed and mechanical drilling speed during the well section drilling process are shown in [reference needed]. Figure 12 In the fifth drilling section, the actual mechanical drilling rate was generally higher than the set lower limit, while the actual drilling speed was lower than the set upper limit. Based on the actual drilling parameters of the fifth section, the cumulative fatigue index distribution of the drill string to the designed drilling depth was calculated as follows: Figure 11 Calculation and analysis revealed that the maximum cumulative fatigue index of the drill string for the entire well was 0.35 after the fifth section was completed, which is less than the set critical threshold A. The fifth section of the CT1 well was completed safely without any drill string accidents.

[0125] As can be seen from the above description, the method for predicting drill string fatigue fracture in shallow deep well dogleg sections provided by the embodiments of the present invention first determines the stress parameters of the drill string based on the engineering parameters of the drilling section; then, a calculation model for the fatigue crack propagation rate of the drill string is established based on the stress parameters; finally, the fatigue strength of the drill string is predicted based on the calculation model for the fatigue crack propagation rate of the drill string.

[0126] This invention addresses the problems of existing drill string fatigue failure prediction and evaluation methods, such as long operating times, high costs, low timeliness, and insufficient specificity. It proposes a method for preventing drill string fatigue fracture in shallow dogleg sections of deep wells. This method includes a drill string cumulative fatigue strength calculation method based on an initial defect propagation model, and a pre-drilling and ongoing drill string fatigue fracture risk verification process based on this calculation method. This enables prediction of cumulative drill string fatigue strength and early warning of fatigue fracture risk throughout the entire deep well section. It guides on-site personnel to optimize process measures and construction parameters, enabling timely tripping and drill string replacement, ensuring drill string safety during deep and ultra-deep well drilling. This provides a timely, easily applicable, and low-cost method to avoid frequent drill string failures due to drill string fatigue in shallow dogleg sections of deep wells, improving the scientific and intelligent level of deep and ultra-deep well drilling, and supporting future digital and automated drilling.

[0127] Based on the same inventive concept, this application also provides a device for predicting the fatigue fracture of drill string in shallow deep well sections with large doglegs. This device can be used to implement the method described in the above embodiments, as shown in the following embodiments. Since the principle of the device for predicting the fatigue fracture of drill string in shallow deep well sections with large doglegs is similar to that of the method for predicting the fatigue fracture of drill string in shallow deep well sections with large doglegs, the implementation of the device can refer to the implementation of the method for predicting the fatigue fracture of drill string in shallow deep well sections with large doglegs. Repeated descriptions will not be repeated. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the system described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0128] The embodiments of the present invention provide a specific implementation of a drill string fatigue fracture prediction device for shallow dogleg sections of deep wells, capable of predicting drill string fatigue fracture in these sections. See also: Figure 13 The drill string fatigue fracture prediction device for shallow deep well dogleg sections specifically includes the following components:

[0129] The stress parameter determination module 10 is used to determine the stress parameters of the drill string based on the engineering parameters of the drilling section.

[0130] The calculation model establishment module 20 is used to establish a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters.

[0131] The fatigue strength prediction module 30 is used to predict the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model.

[0132] In one embodiment, the engineering parameters include drilling engineering parameters and wellbore engineering parameters;

[0133] The drilling parameters include: drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, and drilling fluid density, etc.

[0134] The wellbore engineering parameters include: wellbore structure, well inclination, and drill string assembly.

[0135] In one embodiment, the stress parameters include: bending stress, axial stress, shear stress, circumferential stress, and tangential stress.

[0136] In one embodiment, see Figure 14 The computational model building module 20 includes:

[0137] The calculation model establishment unit 201 establishes a calculation model for the fatigue crack propagation rate of the drill string based on the drill string crack propagation assessment method, according to the maximum stress difference, minimum stress difference, F-crack geometry factor, cross-sectional stress ratio, fracture toughness index of drill string material, initial crack size, critical crack size, and material constants.

[0138] In one embodiment, see Figure 15 The fatigue strength prediction module 30 includes:

[0139] The cycle calculation unit 301 is used to calculate the cycle number corresponding to the fatigue fracture of the cross section at each calculation node according to the drill string fatigue crack propagation rate calculation model.

[0140] The relative fatigue coefficient determination unit 302 is used to determine the relative fatigue coefficient of the drill string at each calculation node based on the actual number of rotations of the drill string.

[0141] The cumulative fatigue coefficient calculation unit 303 is used to calculate the cumulative fatigue coefficient of the drilling section based on the relative fatigue coefficient of the drill string at each calculation node.

[0142] The fatigue strength prediction unit 304 is used to determine the cumulative fatigue coefficient of the drilled section based on the cumulative fatigue coefficient of drilling multiple cross-section well sections, so as to predict the fatigue strength of the drill string.

[0143] In one embodiment, see Figure 16 The drill string fatigue fracture prediction device for shallow dogleg sections in deep wells also includes:

[0144] The drilling mode change module 40 is used to reduce the rotation speed, increase the mechanical drilling speed, and change the drill string assembly when the cumulative fatigue coefficient of the drilled section exceeds a preset threshold, until the cumulative fatigue coefficient of the drilled section is less than the preset threshold.

[0145] As can be seen from the above description, the drill string fatigue fracture prediction device for shallow deep well dogleg sections provided in this embodiment of the invention first determines the stress parameters of the drill string based on the engineering parameters of the drilling section; then, it establishes a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters; and finally, it predicts the fatigue strength of the drill string based on the calculation model for the fatigue crack propagation rate of the drill string.

[0146] This invention addresses the problems of existing drill string fatigue failure prediction and evaluation methods, such as long operating times, high costs, low timeliness, and insufficient specificity. It proposes a method for preventing drill string fatigue fracture in shallow dogleg sections of deep wells. This method includes a drill string cumulative fatigue strength calculation method based on an initial defect propagation model, and a pre-drilling and ongoing drill string fatigue fracture risk verification process based on this calculation method. This enables prediction of cumulative drill string fatigue strength and early warning of fatigue fracture risk throughout the entire deep well section. It guides on-site personnel to optimize process measures and construction parameters, enabling timely tripping and drill string replacement, ensuring drill string safety during deep and ultra-deep well drilling. This provides a timely, easily applicable, and low-cost method to avoid frequent drill string failures due to drill string fatigue in shallow dogleg sections of deep wells, improving the scientific and intelligent level of deep and ultra-deep well drilling, and supporting future digital and automated drilling.

[0147] This application also provides a specific implementation of an electronic device capable of performing all steps in the deep well shallow dogleg well section drill string fatigue fracture prediction method described in the above embodiments. See [link to implementation details]. Figure 17 The electronic devices specifically include the following:

[0148] Processor 1201, memory 1202, communications interface 1203, and bus 1204;

[0149] The processor 1201, memory 1202, and communication interface 1203 communicate with each other via bus 1204; the communication interface 1203 is used to realize information transmission between server-side devices and client-side devices and other related devices.

[0150] The processor 1201 is used to call the deterministic machine program in the memory 1202. When the processor executes the deterministic machine program, it implements all the steps in the deep well shallow dogleg well section drill string fatigue fracture prediction method in the above embodiments. For example, when the processor executes the deterministic machine program, it implements the following steps:

[0151] Step 100: Determine the stress parameters of the drill string based on the engineering parameters of the drilling section;

[0152] Step 200: Establish a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters;

[0153] Step 300: Predict the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model.

[0154] Embodiments of this application also provide a deterministic machine-readable storage medium capable of implementing all steps in the deep well shallow dogleg well section drill string fatigue fracture prediction method described in the above embodiments. The deterministic machine-readable storage medium stores a deterministic machine program, which, when executed by a processor, implements all steps in the deep well shallow dogleg well section drill string fatigue fracture prediction method described in the above embodiments. For example, when the processor executes the deterministic machine program, it implements the following steps:

[0155] Step 100: Determine the stress parameters of the drill string based on the engineering parameters of the drilling section;

[0156] Step 200: Establish a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters;

[0157] Step 300: Predict the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model.

[0158] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, hardware + program embodiments are relatively simple in description because they are fundamentally similar to method embodiments; relevant parts can be referred to the descriptions in the method embodiments.

[0159] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0160] While this application provides method operation steps as shown in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-inventive labor. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual device or client product execution, the method can be executed sequentially as shown in the embodiments or drawings, or in parallel (e.g., in a parallel processor or multi-threaded processing environment).

[0161] For ease of description, the above devices are described in terms of function, divided into various modules. Of course, in implementing the embodiments of this specification, the functions of each module can be implemented in one or more software and / or hardware components, or a module that performs the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between devices or units, and may be electrical, mechanical, or other forms.

[0162] Those skilled in the art will also know that, besides implementing the controller using purely deterministic machine-readable program code, the same functionality can be achieved entirely through logical programming of the method steps, making the controller function as logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers (PLCs), and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices within it used to implement various functions can also be considered structures within that hardware component. Alternatively, the devices used to implement various functions can be considered as both software modules implementing the method and structures within a hardware component.

[0163] 0 In a typical configuration, the device is defined as including one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0164] Memory may include non-persistent storage in machine-readable media, random access memory (RAM), and / or...

[0165] Or it can take the form of non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a machine-readable medium.

[0166] The embodiments described herein can be presented in the general context of deterministic machine-executable instructions executed by a deterministic machine.

[0167] For example, program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. The embodiments of this specification can also be practiced in distributed deterministic environments, where tasks are performed by remote processing devices connected via a communication network.

[0168] In a distributed deterministic environment, program modules can reside in local and remote deterministic storage media, including storage devices.

[0169] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are relatively simple in description because they are fundamentally similar to the method embodiments; relevant details can be found elsewhere.

[0170] See the description of the method embodiments for details. In the description of this specification, references to terms such as "an embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example that are included in at least one embodiment or example of the embodiments of this specification.

[0171] In this specification, the illustrative expressions of the terms used do not necessarily refer to the same embodiments or examples. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples, without contradiction.

[0172] The above description is merely an embodiment of the present specification and is not intended to limit the embodiments of the present specification. For those skilled in the art, various modifications and variations can be made to the embodiments of the present specification. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present specification should be included within the scope of the claims of the embodiments of the present specification.

Claims

1. A method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells, characterized in that, include: Determine the stress parameters of the drill string based on the engineering parameters of the drilling section; A calculation model for the fatigue crack propagation rate of the drill string is established based on the stress parameters. The fatigue strength of the drill string is predicted based on the drill string fatigue crack propagation rate calculation model. The step of predicting the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model includes: According to the drill string fatigue crack propagation rate calculation model, the cross section is calculated to reach the fatigue fracture corresponding cycle number at each calculation node. The relative fatigue coefficient of the drill string at each calculation node is determined based on the actual number of rotations of the drill string. The cumulative fatigue coefficient of the drilling section is calculated based on the relative fatigue coefficient of the drill string at each calculation node. The cumulative fatigue coefficient of the drilled section is determined based on the cumulative fatigue coefficient of drilling multiple cross-sections to predict the fatigue strength of the drill string.

2. The method for predicting drill string fatigue fracture in shallow deep well dogleg sections according to claim 1, characterized in that, The engineering parameters include drilling engineering parameters and wellbore engineering parameters; The drilling parameters include: drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, and drilling fluid density; The wellbore engineering parameters include: wellbore structure, well inclination, and drill string assembly.

3. The method for predicting drill string fatigue fracture in shallow deep well dogleg sections according to claim 1, characterized in that, The stress parameters include: bending stress, axial stress, shear stress, circumferential stress, and tangential stress values.

4. The method for predicting drill string fatigue fracture in shallow deep well dogleg sections according to claim 1, characterized in that, The step of establishing a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters includes: Based on the drill string crack propagation assessment method, a calculation model for the fatigue crack propagation rate of the drill string is established according to the maximum stress difference, minimum stress difference, F-crack geometry factor, cross-sectional stress ratio, fracture toughness index of drill string material, initial crack size, critical crack size, and material constants.

5. The method for predicting drill string fatigue fracture in shallow deep well dogleg sections according to claim 1, characterized in that, Also includes: When the cumulative fatigue coefficient of the drilled section exceeds a preset threshold, reduce the rotation speed, increase the mechanical drilling rate, and replace the drill string assembly until the cumulative fatigue coefficient of the drilled section is less than the preset threshold.

6. A device for predicting drill string fatigue fracture in shallow dogleg sections of deep wells, characterized in that, include: The stress parameter determination module is used to determine the stress parameters of the drill string based on the engineering parameters of the drilling section. The calculation model establishment module is used to establish a calculation model for the fatigue crack propagation rate of the drill string based on the stress parameters. The fatigue strength prediction module is used to predict the fatigue strength of the drill string based on the drill string fatigue crack propagation rate calculation model. The fatigue strength prediction module includes: The cycle calculation unit is used to calculate the cycle number corresponding to the fatigue fracture of the cross section at each calculation node according to the drill string fatigue crack propagation rate calculation model. The relative fatigue coefficient determination unit is used to determine the relative fatigue coefficient of the drill string at each calculation node based on the actual number of rotations of the drill string. The cumulative fatigue coefficient calculation unit is used to calculate the cumulative fatigue coefficient of the drilling section based on the relative fatigue coefficient of the drill string at each calculation node. The fatigue strength prediction unit is used to determine the cumulative fatigue coefficient of the drilled section based on the cumulative fatigue coefficient of drilling multiple cross-section well sections, so as to predict the fatigue strength of the drill string.

7. The drill string fatigue fracture prediction device for shallow deep well dogleg sections according to claim 6, characterized in that, The engineering parameters include drilling engineering parameters and wellbore engineering parameters; The drilling parameters include: drilling pressure, rotation speed, torque, stand pressure, hook load, drilling time, and drilling fluid density; The wellbore engineering parameters include: wellbore structure, well inclination, and drill string assembly.

8. The device for predicting drill string fatigue fracture in shallow deep well sections with large doglegs according to claim 6, characterized in that, The stress parameters include: bending stress, axial stress, shear stress, circumferential stress, and tangential stress values.

9. The drill string fatigue fracture prediction device for shallow deep well dogleg sections according to claim 6, characterized in that, The computational model building module includes: The calculation model establishment unit is used to establish a calculation model for the fatigue crack propagation rate of the drill string based on the drill string crack propagation assessment method, according to the maximum stress difference, minimum stress difference, F-crack geometry factor, cross-sectional stress ratio, fracture toughness index of drill string material, initial crack size, critical crack size, and material constants.

10. The device for predicting drill string fatigue fracture in shallow deep well sections with large doglegs according to claim 6, characterized in that, Also includes: The drilling mode change module is used to reduce the rotation speed, increase the mechanical drilling speed, and change the drill string assembly when the cumulative fatigue coefficient of the drilled section exceeds a preset threshold, until the cumulative fatigue coefficient of the drilled section is less than the preset threshold.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instruction is executed by the processor, it implements the method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells as described in any one of claims 1 to 5.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method for predicting drill string fatigue fracture in shallow deep well dogleg sections as described in any one of claims 1 to 5.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method for predicting drill string fatigue fracture in shallow dogleg sections of deep wells as described in any one of claims 1 to 5.

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