A method, apparatus and device for determining a through-the-hole drilling tool

Abstract

This specification relates to the field of oil and gas engineering technology, and particularly to a method, apparatus, and equipment for determining a wellbore drilling tool, comprising: acquiring first drilling parameter data corresponding to the wellbore drilling tool and second drilling parameter data corresponding to the wellbore casing; calculating a first sticking risk factor for the wellbore drilling tool based on the first drilling parameter data, the first sticking risk factor representing the probability of the wellbore drilling tool sticking; calculating a second sticking risk factor for the wellbore casing based on the second drilling parameter data, the second sticking risk factor representing the probability of the wellbore casing sticking; calculating a first running-in capability index for the wellbore drilling tool based on the stiffness of the wellbore drilling tool and the first sticking risk factor; calculating a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determining whether the wellbore drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of oil and gas engineering technology, specifically to a method, apparatus, and equipment for determining well drilling tools. Background Technology

[0002] In oil and gas drilling engineering, well cleaning is a crucial step in ensuring unobstructed wellbore flow and guaranteeing the safety of subsequent extraction operations. As oil and gas resource development extends to deeper, more complex formations, and unconventional reservoirs, wellbore irregularities are becoming increasingly prominent, such as wellbore collapse, narrowing, keyway formation, and gravel accumulation. These issues significantly increase the difficulty of well cleaning, thereby affecting the efficiency of subsequent operations. Well cleaning tools, as the core tools for solving these problems, must be designed with multiple factors in mind, including wellbore quality, wellbore trajectory, operational efficiency, and cost control.

[0003] Existing methods mainly rely on experience or simple methods such as the stiffness ratio of the drilling tool and the well casing, as well as the superimposed stiffness ratio method, for judgment. However, these methods do not consider the influence of certain drilling parameters between the drilling tool and the wellbore on the drilling tool running process, nor do they consider the influence of complex downhole wellbore conditions on the drilling tool running process, thus failing to scientifically and accurately evaluate the drilling tool's effectiveness.

[0004] Therefore, it is crucial to address the problems of one-sided evaluation, low accuracy, and poor adaptability to complex wellbore conditions in existing methods, and to propose a comprehensive, accurate, and adaptable wellbore tool determination method that is highly adaptable to complex wellbore conditions. Summary of the Invention

[0005] The purpose of the embodiments in this specification is to provide a method, apparatus, and equipment for determining wellbore drilling tools, so as to overcome the problems of one-sided evaluation, low accuracy, and poor adaptability to complex wellbore conditions in existing wellbore drilling tool determination methods.

[0006] On one hand, embodiments of this specification provide a method for determining a well-drilling tool, comprising: acquiring first drilling parameter data corresponding to the well-drilling tool and second drilling parameter data corresponding to the wellbore casing; calculating a first sticking risk factor for the well-drilling tool based on the first drilling parameter data, wherein the first sticking risk factor is used to indicate the probability of the well-drilling tool sticking; calculating a second sticking risk factor for the wellbore casing based on the second drilling parameter data, wherein the second sticking risk factor is used to indicate the probability of the wellbore casing sticking; calculating a first running-in capability index for the well-drilling tool based on the stiffness of the well-drilling tool and the first sticking risk factor; calculating a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determining whether the well-drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index.

[0007] On another front, embodiments of this specification provide a wellbore drilling tool determination device, comprising: an acquisition module for acquiring first drilling parameter data corresponding to the wellbore drilling tool and second drilling parameter data corresponding to the wellbore casing; a first calculation module for calculating a first sticking risk factor of the wellbore drilling tool based on the first drilling parameter data, the first sticking risk factor representing the probability of the wellbore drilling tool sticking; a second calculation module for calculating a second sticking risk factor of the wellbore casing based on the second drilling parameter data, the second sticking risk factor representing the probability of the wellbore casing sticking; a third calculation module for calculating a first running-in capability index of the wellbore drilling tool based on the stiffness of the wellbore drilling tool and the first sticking risk factor; a fourth calculation module for calculating a second running-in capability index of the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and a determination module for determining whether the wellbore drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index.

[0008] In another aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor performs the above-described well drilling tool determination method.

[0009] As can be seen from the technical solutions provided in the embodiments of this specification above, the embodiments of this specification can obtain first drilling parameter data corresponding to the well-drilling tool and second drilling parameter data corresponding to the wellbore casing; calculate a first sticking risk factor for the well-drilling tool based on the first drilling parameter data, the first sticking risk factor being used to indicate the possibility of the well-drilling tool getting stuck; calculate a second sticking risk factor for the wellbore casing based on the second drilling parameter data, the second sticking risk factor being used to indicate the possibility of the wellbore casing getting stuck; calculate a first running-in capability index for the well-drilling tool based on the stiffness of the well-drilling tool and the first sticking risk factor; calculate a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determine whether the well-drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index. Compared to existing methods, the embodiments in this specification can calculate the likelihood of sticking in both the drilling tool and the casing based on the corresponding drilling parameter data. This allows for a more comprehensive and accurate assessment of the running-in capability of both the drilling tool and casing, considering both deformation and sticking risk during well entry. Furthermore, by comparing the running-in capabilities of the drilling tool and casing, a rapid, scientific, and precise determination of their compatibility can be made. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments or prior art of this specification, the accompanying drawings used in the description of the embodiments or prior art will be briefly introduced below.

[0011] Figure 1 This is a flowchart of a well-drilling tool determination method provided in the embodiments of this specification;

[0012] Figure 2 This is a schematic diagram of the overall process of a well drilling tool determination method provided in the embodiments of this specification;

[0013] Figure 3 This is a flowchart illustrating a method for constructing a card blocking risk calculation model provided in the embodiments of this specification;

[0014] Figure 4 This is a schematic diagram illustrating the mapping relationship between wellbore clearance ratio and mechanical resistance provided in the embodiments of this specification;

[0015] Figure 5 This is a schematic diagram illustrating the mapping relationship between wellbore curvature and mechanical resistance provided in the embodiments of this specification;

[0016] Figure 6 This is a schematic diagram illustrating the mapping relationship between wellbore roughness and mechanical resistance provided in the embodiments of this specification;

[0017] Figure 7 This is a schematic diagram of the mutual information matrix between drilling parameters provided in the embodiments of this specification;

[0018] Figure 8 This is a schematic diagram of the casing running characteristics between the drilling parameters provided in the embodiments of this specification;

[0019] Figure 9 This is a schematic diagram of the structural composition of a well drilling tool determining device provided in the embodiments of this specification;

[0020] Figure 10 This is a schematic diagram of the structural composition of the computer device provided in the embodiments of this specification. Detailed Implementation

[0021] The technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0022] In some embodiments, drilling parameters may include wellbore trajectory parameters, tubing string parameters, and wellbore parameters. Logging data, well logging data, drilling history, and drilling logs cover all aspects from geological conditions to drilling operations, and historical drilling parameter data can be obtained from, but is not limited to, these data.

[0023] Wellbore trajectory parameters describe the geometry and spatial location of the wellbore, serving as crucial data for drilling design and operations. These parameters include well depth, inclination angle, azimuth angle, and wellbore curvature. Well depth can be the vertical or measured depth of the wellbore from the wellhead to the target formation. It is used to determine target formations, calculate tubing length, and assess drilling difficulty. The inclination angle is the angle between the wellbore axis and the vertical direction. It affects the stress distribution on the tubing, friction calculations, and wellbore stability analysis. The azimuth angle is the projection of the wellbore axis onto the horizontal plane. It describes the horizontal orientation of the wellbore, influencing wellbore trajectory control and geological target location. Wellbore curvature is the rate of change of the wellbore trajectory, expressed as angular change per unit length. It reflects the degree of bending of the wellbore, affecting the buckling behavior of the tubing and friction distribution.

[0024] Tubing string parameters describe the geometric and mechanical properties of the casing or drill string, forming the basis for analyzing string stress and optimizing design. These parameters can include casing dimensions, centralizer dimensions, and bending stiffness. Casing dimensions characterize the outer diameter, inner diameter, and wall thickness of the casing. Casing dimensions affect the casing's stiffness, weight, and clearance from the wellbore. Centralizer dimensions characterize the outer diameter, length, and spacing of the centralizer. Centralizer dimensions are used to control the alignment of the casing with the wellbore, reducing friction and buckling risk. Bending stiffness characterizes the tubing string's resistance to bending deformation and is related to the material's elastic modulus and moment of inertia. Bending stiffness affects the deformation behavior and stress distribution of the tubing string in a bent wellbore.

[0025] Wellbore parameters describe the geometry and surface characteristics of the wellbore and are crucial for analyzing the interaction between the wellbore and the casing string. Wellbore parameters can include wellbore diameter, wellbore roughness, and wellbore clearance ratio. Wellbore diameter represents the diameter of the wellbore, which may vary depending on the well section. The wellbore diameter affects the clearance between the casing and the wellbore, thus influencing frictional resistance and contact pressure. Wellbore roughness represents the degree of unevenness of the wellbore surface, which can be expressed as the height of microscopic irregularities. Wellbore roughness affects the coefficient of friction and contact pressure between the casing and the wellbore. The wellbore clearance ratio represents the ratio of the casing outer diameter to the wellbore diameter. The wellbore clearance ratio reflects the degree of fit between the casing and the wellbore, affecting casing alignment and frictional resistance.

[0026] Figure 1 This is a flowchart of a well-drilling tool determination method provided in the embodiments of this specification. Figure 2This is a schematic diagram of the overall process of a wellbore drilling tool determination method provided in the embodiments of this specification. In specific implementation, it includes the following steps:

[0027] S101: Obtain the first drilling parameter data corresponding to the wellbore drilling tool and the second drilling parameter data corresponding to the wellbore casing.

[0028] In some embodiments, a ducting tool is a tool used to treat the wellbore. During drilling operations, the wellbore can be treated first with the ducting tool, and then the wellbore casing can be run into the treated wellbore. The ducting tool and the wellbore casing need to be compatible so that the wellbore casing can be smoothly run into the wellbore treated with the ducting tool without getting stuck. First drilling parameter data corresponding to the ducting tool and second drilling parameter data corresponding to the wellbore casing can be acquired.

[0029] By systematically acquiring drilling parameter data related to wellbore tools and wellbore casing, a data foundation is laid for subsequent calculations of the possibility of wellbore tools and wellbore casing getting stuck.

[0030] The primary drilling parameter data corresponding to the wellbore cleaning tool may include drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio, calculated based on the wellbore cleaning tool's structure. Wellbore curvature can represent the degree of curvature of the wellbore trajectory and can be expressed as the angle of inclination change (° / 30m) or the radius of curvature (m) at fixed intervals (e.g., every 30 meters). If the wellbore curvature exceeds the allowable curvature of the drill string assembly (e.g., the limit bending radius of a rigid drill pipe), the flexibility of the drill string can be matched during well cleaning (e.g., using a weighted drill pipe or a flexible sub). Wellbore roughness quantifies the irregularity of the wellbore surface, reflecting wellbore cleanliness or erosion conditions. It can be expressed as average roughness (or irregularity index), specifically calculated from the deviation between the local wellbore diameter and the theoretical diameter using caliper logging data (such as CAL). High-roughness wells easily lead to drilling tool vibration, difficulty in mud carrying rock, and increased mechanical resistance during drilling. Drilling tools can be equipped with stabilizers or reaming tools to smooth the wellbore and reduce roughness. The wellbore clearance ratio represents the ratio of the drill string's outer diameter to the wellbore diameter, reflecting the drill string's operating space within the wellbore. A critical clearance ratio (e.g., 15%–20%) that is too small can easily cause stuck pipe, while one that is too large may lead to difficulties in drill string control. Drilling tool design can use small-diameter drill strings in the reduced-diameter section and add stabilizers in the enlarged-diameter section to ensure a reasonable clearance ratio.

[0031] The secondary drilling parameters for the wellbore casing may include wellbore curvature, wellbore roughness, and wellbore clearance ratio, calculated based on the wellbore casing structure. Wellbore curvature refers to the degree of curvature of the wellbore trajectory the casing must traverse, and can be expressed as the maximum dogleg angle (° / 30m) or the minimum radius of curvature (m). Conventional wellbore casing typically allows curvatures ≤10° / 30m, while flexible casing (such as expansion casing) can accommodate higher curvatures. Wellbore roughness characterizes the impact of wellbore irregularities on casing running friction, and can be quantified using the equivalent friction coefficient or the standard deviation of wellbore circumference. High roughness (such as keyways and helical boreholes) significantly increases running friction, and may even lead to obstruction or casing deformation. The wellbore clearance ratio represents the ratio of the casing outer diameter to the wellbore diameter.

[0032] The first and second drilling parameter data are related. For example, the drilling tool corresponding to the first drilling parameter and the casing corresponding to the second drilling parameter belong to the same wellbore. Therefore, the first and second drilling parameter data are parameter data calculated for the same wellbore, respectively corresponding to the drilling tool and the casing.

[0033] S102: Calculate the first sticking risk factor of the well-drilling tool based on the first drilling parameter data. The first sticking risk factor is used to indicate the possibility of the well-drilling tool getting stuck.

[0034] In some embodiments, a first sticking risk factor for the well-drilling tool can be calculated based on first drilling parameter data. The first sticking risk factor is used to indicate the probability of the well-drilling tool getting stuck.

[0035] By using the first sticking risk factor to quantify the probability of wellbore drilling tools getting stuck, a data foundation is laid for further quantifying the running capability of wellbore drilling tools based on the first sticking risk factor.

[0036] After obtaining the initial drilling parameter data for the wellbore drilling tool, a pre-defined sticking risk calculation model can be used to calculate the first sticking risk factor. The first sticking risk factor is a parameter that quantitatively assesses the resistance and sticking risk that the wellbore drilling tool may encounter in the wellbore; it can be used to represent the probability of the wellbore drilling tool getting stuck. Drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio are closely related to the resistance and sticking risk that the wellbore drilling tool may encounter in irregular wellbores. For example, the greater the curvature of the wellbore (dogleg), the greater the resistance when the wellbore drilling tool passes through. The rougher the wellbore, the greater the friction between the drill string and the wellbore. The smaller the ratio of the wellbore diameter to the drill string's outer diameter, the greater the resistance when the drill string passes through. The pre-defined sticking risk calculation model can, for example, be an LSTM neural network trained based on historical drilling parameter data. By using downhole sensors (such as test-and-run pressure, real-time torque / friction monitoring) and surface data (such as mud rheological parameters, mechanical drilling rate), the input primary drilling parameter data (such as wellbore curvature, roughness) can be dynamically updated, and the weights of different primary drilling parameter data can be automatically adjusted according to the characteristics of the well section. For example, in salt-gypsum formations, wellbore creep may cause a sharp decrease in the wellbore clearance ratio. In this case, the weight of the wellbore clearance ratio can be automatically increased, thereby obtaining a more accurate primary stuck risk factor.

[0037] S103: Calculate the second sticking risk factor of the well casing based on the second drilling parameter data. The second sticking risk factor is used to indicate the possibility of sticking in the well casing.

[0038] In some embodiments, a second sticking risk factor for the wellbore casing can be calculated based on second drilling parameter data. The second sticking risk factor is used to indicate the probability of the wellbore casing sticking.

[0039] By using a second sticking risk factor to quantify the probability of well casing sticking, a data foundation is laid for further quantifying the running capability of well casing based on the second sticking risk factor.

[0040] After obtaining the second drilling parameter data for the wellbore casing, a pre-defined sticking risk calculation model can be used to calculate the second sticking risk factor for the wellbore casing. The second sticking risk factor is a parameter that quantitatively assesses the resistance and sticking risk that the casing may encounter in irregular wellbores; it can be used to represent the probability of the wellbore casing sticking. Drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio are closely related to the resistance and sticking risk that the casing may encounter in irregular wellbores. For example, the greater the curvature of the wellbore (dogleg), the greater the resistance when the casing passes through. The rougher the wellbore, the greater the friction between the casing and the wellbore. The smaller the ratio of the wellbore diameter to the casing outer diameter, the greater the resistance when the casing passes through. The pre-defined sticking risk calculation model can, for example, be an LSTM neural network trained based on historical drilling parameter data. Similarly, by using downhole sensors (such as pressure measurement while drilling and real-time torque / friction monitoring) and surface data (such as mud rheological parameters and mechanical drilling rate), the input second drilling parameter data (such as wellbore curvature and roughness) can be dynamically updated, and the weight of different second drilling parameter data can be automatically adjusted according to the characteristics of the well section, thereby obtaining a more accurate second stuck risk factor.

[0041] S104: Calculate the first running-in capability index of the well-drilling tool based on the stiffness of the well-drilling tool and the first jamming risk factor.

[0042] In some embodiments, the first running-in capability index of the well-drilling tool can be calculated using the following formula, based on the stiffness of the well-drilling tool and the first sticking risk factor:

[0043] A 通井钻具 =c 通井钻具 ×EI 通井钻具

[0044] In the formula, EI 通井钻具 For the rigidity of the wellbore drilling tool, c 通井钻具 This is the first risk factor for stuck drilling tools.

[0045] By using the first sticking risk factor as a correction coefficient for the stiffness of the wellbore drilling tool, the coupling of stiffness and sticking risk is achieved. This allows for a more comprehensive and accurate measurement of the wellbore drilling tool's throughput capacity by considering both deformation and stress conditions during wellbore entry. Furthermore, it facilitates a quantitative comparison of the running-in capacity of the wellbore drilling tool and the wellbore casing.

[0046] The stiffness of a wellbore drilling tool represents its ability to resist deformation under stress, and can be expressed as the elastic modulus or bending stiffness. The magnitude of stiffness directly affects the tool's ability to pass through the wellbore. High-stiffness tools are more prone to generating large contact forces with the wellbore wall when passing through wells with high curvature, increasing the risk of stuck pipe. Low-stiffness tools have better flexibility and can adapt to the bending and deformation of the wellbore, but may affect operational efficiency due to insufficient strength. The bending stiffness (EI) of the drilling tool can be calculated based on the elastic modulus (E) and geometric parameters (such as the moment of inertia I) of the drilling tool material. For combined wellbore drilling tools (such as those with centralizers), the stiffness characteristics of the overall structure can be considered. For example, the sum of the stiffness of each component in the combined wellbore drilling tool can be taken as the stiffness of the combined wellbore drilling tool.

[0047] Based on drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio of the drilling tool, the first sticking risk factor of the drilling tool can be calculated using a sticking risk calculation model. The first sticking risk factor is a positive number greater than 1 and can be used as a weighting / correction coefficient for the drilling tool stiffness. Based on the drilling tool stiffness and the first sticking risk factor, the first running-in capability index of the drilling tool when passing through the wellbore can be calculated. The first running-in capability index characterizes the drilling tool's ability to resist not only external forces generated by wellbore bending and deformation during wellbore entry, but also additional mechanical forces generated by drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio. Specifically, the product of the drilling tool stiffness and the first sticking risk factor can be used as the first running-in capability index. The first capability index converts the deformation and stress conditions of the drilling tool during wellbore entry into the running-in capability index. The larger the index, the stronger the drilling tool's passage capability.

[0048] S105: Calculate the second running-in capability index of the well casing based on the stiffness of the well casing and the second sticking risk factor.

[0049] In some embodiments, the second running-in capability index of the well casing can be calculated using the following formula, based on the stiffness of the well casing and the second sticking risk factor:

[0050] A 套管 =c 套管 ×EI 套管

[0051] In the formula, EI 套管 For the stiffness of the well casing, c 套管 This is the second risk factor for stuck casing in the wellbore.

[0052] By using the second sticking risk factor as a correction coefficient for the casing stiffness, the coupling of stiffness and sticking risk is achieved. This allows for a more comprehensive and accurate measurement of the casing's throughput capacity by considering both deformation and stress conditions during casing insertion into the wellbore. Furthermore, it facilitates a quantitative comparison of the insertion capacity of drilling tools and casing. Insertion capacity refers to the ability of tools (such as drilling tools and casing) to be successfully inserted into the wellbore (without sticking).

[0053] The stiffness of well casing represents its ability to resist deformation under stress, and can be expressed using the elastic modulus or bending stiffness. The magnitude of stiffness directly affects the casing's ability to pass through irregular wellbores. High-stiffness casing is more prone to generating large contact forces with the wellbore wall when passing through wells with high curvature, increasing the risk of stuck pipe. Low-stiffness casing has better flexibility and can adapt to the bending and deformation of the wellbore. The bending stiffness (EI) of the casing can be calculated based on the elastic modulus (E) and geometric parameters (such as the moment of inertia I) of the casing material. For composite casings (such as drill strings with centralizers), the stiffness characteristics of the overall structure can also be considered, which will not be elaborated upon here.

[0054] Based on drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio of the casing, a second sticking risk factor for the casing can be calculated using a sticking risk calculation model. The second sticking risk factor is a positive number greater than 1 and can serve as a weighting / correction coefficient for the stiffness of irregular wellbore casing. Based on the casing stiffness and the second sticking risk factor, a second running-in capability index can be calculated for the casing as it passes through the wellbore. The second running-in capability index characterizes the casing's ability to resist not only external forces generated by wellbore bending and deformation but also additional mechanical forces generated by drilling parameters such as wellbore curvature, wellbore roughness, and wellbore clearance ratio when running into complex wellbores. Specifically, the product of the casing stiffness and the second sticking risk factor can be used as the second running-in capability index. This index transforms the deformation and stress conditions of the casing during wellbore running into the running-in capability index. A larger index indicates a stronger casing throughput capacity.

[0055] S106: Determine whether the drilling tools and the well casing are compatible based on the first and second drilling capability indices.

[0056] In some embodiments, if the first running-in capability index is greater than or equal to the second running-in capability index, it can be determined that the dredging drill string is compatible with the wellbore casing. The first running-in capability index is a quantitative assessment of the dredging drill string's ability to pass through the wellbore. It comprehensively considers the complex geometric characteristics of the wellbore, such as wellbore curvature, wellbore roughness, and wellbore clearance ratio, as well as the physical parameters of the dredging drill string (including outer diameter, length, flexibility, etc.). The larger the first running-in capability index, the stronger the drill string's ability to pass through the wellbore. The second running-in capability index is a quantitative assessment of the casing's ability to pass through the wellbore. The second running-in capability index also comprehensively considers the complex geometric characteristics of the wellbore, such as wellbore curvature, wellbore roughness, and wellbore clearance ratio, as well as the physical parameters of the casing. If the first running-in capability index is greater than or equal to the second running-in capability index, it means that the dredging drill string can be run through the casing in an irregular wellbore, that is, the dredging drill string meets the wellbore's passage requirements, and it can be directly determined that the dredging drill string is compatible with the wellbore casing, that is, the dredging drill string can be used as the dredging drill string for the wellbore. Among them, under the condition that the first running-in capability index and the second running-in capability index are equal, it can be considered that the drilling tool and the well casing have equivalent running-in capability.

[0057] In some embodiments, the structure of the wellbore drilling tool can be pre-configured, and then the first drilling parameters can be obtained based on the pre-configured structure of the wellbore drilling tool. For example, the structure of the wellbore drilling tool can be configured according to the wellbore structure. Of course, the wellbore drilling tool can also have a default pre-configured structure. Thus, if the first running-in capability index is less than the second running-in capability index, the structure of the wellbore drilling tool can be adjusted; the drilling parameter data corresponding to the adjusted wellbore drilling tool can be obtained as new first drilling parameter data; a new first running-in capability index of the wellbore drilling tool can be calculated based on the stiffness of the wellbore drilling tool and the first sticking risk factor; the above steps are iteratively executed until the first running-in capability index is greater than or equal to the second running-in capability index; and the adjusted wellbore drilling tool is determined to be compatible with the wellbore casing.

[0058] By adjusting the structure of the wellbore drilling tool, calculating the first run-in capability index, and implementing an automated decision-making closed-loop control system to determine whether a match is achieved, proactive optimization during the wellbore cleaning phase can be realized. Furthermore, low-cost fine-tuning of the wellbore drilling tool structure significantly enhances dynamic adaptability in complex and irregular wellbore conditions.

[0059] If the first downhole capability index is less than the second downhole capability index, it indicates that the drilling tool cannot be downholed, meaning the selected drilling tool has insufficient throughput and needs adjustment and optimization. Specifically, the structure of the drilling tool can be adjusted in the following ways, including but not limited to: 1) optimizing the physical parameters of the drilling tool (e.g., reducing the outer diameter and increasing flexibility); 2) adding auxiliary tools (e.g., centralizers, friction reducers) to reduce the risk of stuck pipe; 3) adjusting the drilling fluid properties to improve wellbore cleaning.

[0060] The first stuck-out risk factor and the first running-in capability index are related to the structure of the well-drilling tool. After adjusting the structure of the well-drilling tool, a new first stuck-out risk factor and a new first running-in capability index can be recalculated and compared with the second running-in capability index again. This process can be iteratively executed until the new first running-in capability index is greater than or equal to the second running-in capability index. When the iteratively optimized well-drilling tool meets the condition that the first running-in capability index is greater than or equal to the second running-in capability index, the adjusted well-drilling tool can be determined as a well-drilling tool for irregular wellbores. At this point, the tool has sufficient throughput / running capability to effectively cope with the complex conditions of the wellbore and ensure the smooth progress of well-drilling operations.

[0061] Figure 3 This is a flowchart illustrating a method for constructing a card blocking risk calculation model provided in the embodiments of this specification. In specific implementation, it includes the following steps:

[0062] S301: Based on the mechanical model of the first casing run-in of a regular wellbore and the mechanical resistance model of an irregular wellbore, construct the mechanical model of the second casing run-in of an irregular wellbore.

[0063] In some embodiments, a regular wellbore can be defined as a wellbore with a regular circular cross-section, a wellbore roughness less than or equal to a preset roughness threshold, and a wellbore diameter variance less than or equal to a preset variance threshold. An irregular wellbore can be defined as a wellbore with an irregular circular cross-section, or a wellbore roughness greater than a preset roughness threshold, or a wellbore diameter variance greater than a preset variance threshold. A regular wellbore has a regular circular or near-circular cross-section, a smooth wellbore wall, and a generally consistent diameter, meeting design expectations. During drilling operations, stable drill bit size, optimized drilling parameters (rotation speed, drilling pressure, mud properties), and a homogeneous and stable formation contribute to the formation of a regular wellbore. The wellbore diameter variance can be expressed as the variance of the diameter of one or more wellbore segments. Specifically, for a wellbore segment containing multiple equidistant sampling points, the wellbore diameter at each sampling point location can be obtained. The wellbore diameter variance can be calculated for all sampling points. Similarly, for multiple wellbore segments, the wellbore diameter at each sampling point location within each segment can be obtained. The diameter of the wellbore can be calculated for all sampling points in each section, yielding the diameter variance. Regular wellbores facilitate subsequent operations such as casing and cementing. Regular wellbores also offer better cleaning, reducing the risk of stuck pipe. Irregular wellbores deviate from a circular cross-section, exhibiting irregular deformations (such as elliptical, candied hawthorn-like, or spiral shapes), or have severe erosion, keyways, or other defects in the wellbore wall. For example, uneven formation stress can cause the wellbore to be squeezed, resulting in an elliptical irregular wellbore; the spiral trajectory created by drill string vibration or drill bit deviation during drilling operations can lead to a spiral irregular wellbore; downhole mud erosion or formation water absorption and expansion can cause irregular wellbores with localized diameter anomalies; and drill string friction can create irregular wellbores with grooves in the wellbore wall.

[0064] In some embodiments, the mechanical resistance model of the irregular wellbore can be used as a correction term for the first casing running mechanical model to construct the following second casing running mechanical model:

[0065]

[0066] In the formula, F represents the axial force of the drill string; s represents the well depth; EI represents the bending stiffness of the drill string; k represents the wellbore curvature; q represents the linear weight of the drill string; q represents the well inclination angle; m0 represents the axial friction coefficient; N0 represents the contact distribution force; F m The correction term, constructed based on the mechanical resistance model of the irregular wellbore, represents the mechanical resistance encountered when the casing of the irregular wellbore is run in.

[0067] By using formula Constructing a second casing running mechanical model can more comprehensively and accurately simulate the dynamic casing running process in irregular wells by taking into account factors such as complex trajectories, well wall roughness, and gap changes. This allows for the precise calculation of the mechanical resistance during the casing running process in irregular wells.

[0068] The mechanical model for the first casing run-in of a regular wellbore can be described as follows: In the formula, F represents the axial force of the drill string; s represents the well depth; EI represents the bending stiffness of the drill string; k represents the wellbore curvature; q represents the linear weight of the drill string; q represents the well inclination angle; m0 represents the axial friction coefficient; and N0 represents the contact distribution force.

[0069] The mechanical model for the first casing run-in of a regular wellbore is mainly based on the following assumptions: 1) Regular wellbore trajectory: The wellbore is assumed to be a straight line or a simple curve, ignoring complex trajectories (such as high curvature or spiral trajectories) in the actual wellbore; 2) Smooth wellbore wall: The wellbore wall is assumed to be smooth, ignoring roughness and irregularity; 3) Uniform gap: The gap between the casing and the wellbore is assumed to be uniform, ignoring the influence of gap variation on the running-in process; 4) Simple downhole environment: The influence of complex downhole conditions (such as wellbore collapse, cuttings accumulation, sand bridges, etc.) on casing running-in is ignored.

[0070] The above assumptions lead to the following problems in the application of regular wellbore models: 1) Underestimation of resistance: It is impossible to accurately calculate the mechanical resistance (e.g., frictional resistance and contact force) in irregular wellbores; 2) Neglect of stuck pipe risk: It is impossible to predict the risk of casing stuck pipe in complex wellbores; 3) Insufficient model accuracy: It is difficult to guide parameter optimization and risk control in actual operations. Irregular wellbores significantly affect the casing running process, specifically: curved or helical wellbores increase the bending stress and frictional resistance of the casing; uneven well walls increase the contact force and friction between the casing and the well wall; and changes in the wellbore diameter lead to uneven clearance between the casing and the well wall, increasing running resistance. These irregularities not only increase the resistance during casing running but may also cause casing sticking, deformation, or even damage, seriously affecting operational efficiency and safety.

[0071] Therefore, in order to more accurately describe the mechanical behavior of casing installation in irregular wellbores, a mechanical resistance correction term can be added to the mechanical model of casing installation in the first case of a regular wellbore to construct a mechanical model of casing installation in the second case of an irregular wellbore. F m The correction term constructed based on the mechanical resistance model represents the sum of mechanical resistance caused / affected by various drilling parameters when the casing of an irregular wellbore is run in.

[0072] S302: Solve for the weighting coefficients of drilling parameters and the sticking force of regular wellbore in the mechanical resistance model of irregular wellbore.

[0073] In some embodiments, an orthogonal table can be generated based on the number of levels of the weighting coefficient and the number of levels of the sticking force; one row in the orthogonal table represents a value of the weighting coefficient and the sticking force; based on historical drilling parameter data, the second casing running mechanical model can be used to generate a hook load prediction result corresponding to each value of the weighting coefficient and the sticking force; based on the difference between the hook load prediction result and the actual hook load result, the value of the weighting coefficient and the value of the sticking force can be selected in the orthogonal table.

[0074] The values ​​of the weighting coefficients and the sticking force were determined by orthogonal experiments. On the one hand, based on partial experiments covering all factor combinations, the amount of calculation was significantly reduced, which helped to improve the accuracy of the mechanical resistance model. On the other hand, by inverting historical drilling parameter data, the weighting coefficients and sticking force were made to better fit the actual working conditions.

[0075] In orthogonal experimental design, the number of levels refers to the number of possible values ​​for each parameter. Weighting coefficients are parameters used to adjust the mechanical model of the second casing run-in in irregular wellbores, taking into account the effects of wellbore trajectory, wellbore roughness, and clearance variations. The first level number represents the number of possible values ​​for the weighting coefficients. For example, if the weighting coefficients range from 0.8 to 1.2 and are divided into 5 levels, then the first level number is 5. Sticking force is the resistance encountered when the casing is run into a regular wellbore, usually caused by wellbore friction, cuttings accumulation, etc., and can be considered an unknown constant. The second level number represents the number of possible values ​​for the sticking force. For example, if the sticking force ranges from 10kN to 50kN and is divided into 5 levels, then the second level number is 5. An orthogonal array is a table used for multi-factor experimental design, which can cover all parameter combinations with the fewest number of experiments. Based on the first level number of the weighting coefficients and the second level number of the sticking force, a corresponding orthogonal array can be generated. Each row of an orthogonal array represents an experimental condition, including one value for the weighting coefficient and one value for the blocking force. Each column of the orthogonal array corresponds to a parameter (such as a weighting coefficient or blocking force), and the values ​​in the column represent the level of that parameter. Depending on the number of parameters and levels, an appropriate orthogonal array type (such as L9, L16, etc.) can be selected.

[0076] For example, the weighting coefficient 'a' for wellbore curvature, the weighting coefficient 'b' for wellbore roughness, the weighting coefficient 'g' for wellbore clearance ratio, and the weighting coefficient 'F' for sticking force. g0An L16 orthogonal array can be designed. Assume the wellbore curvature weighting coefficients include four levels: 0.8, 0.9, 1.0, and 1.1; the wellbore roughness correction coefficients include four levels: 0.7, 0.8, 0.9, and 1.0; the wellbore clearance ratio weighting coefficients include four levels: 0.9, 1.0, 1.1, and 1.2; and the sticking force includes four levels: 10 kN, 20 kN, 30 kN, and 40 kN. An L16 orthogonal array is suitable for four parameters, each with four levels, and has 16 rows (number of experiments) and 4 columns (parameters). The values ​​of the wellbore curvature weighting coefficients, wellbore roughness weighting coefficients, wellbore clearance ratio weighting coefficients, and sticking force are filled into the corresponding columns of the orthogonal array, as shown in Table 1.

[0077] Table 1

[0078]

[0079] Based on the designed orthogonal array and historical drilling parameter data from historical wells, a second casing running-in mechanical model for irregular wells can be used to generate hook load prediction results. Historical drilling parameter data from historical wells can include historical operating values ​​of drilling parameters such as drilling pressure, rotational speed, drilling fluid flow rate, and well trajectory. For each row in the orthogonal array (i.e., each test condition), the values ​​of weighting coefficients and sticking force can be substituted into the mechanical resistance correction term of the second casing running-in mechanical model for irregular wells. By inputting historical drilling parameter data into the second casing running-in mechanical model for irregular wells, the predicted hook load value under the current test conditions is output. The predicted hook load results under each test condition can be recorded, and the optimal values ​​of weighting coefficients and sticking force can be determined based on the difference between the predicted and measured hook load results. Specifically, for each test condition, the difference between the predicted and measured hook load results (such as absolute error or mean square error) can be calculated. By comparing the differences under different test conditions, the test condition with the smallest difference is identified. The weighting coefficients and sticking force values ​​corresponding to this test condition are the optimal values. The mechanical model for the second casing run in irregular wellbores can be rerun using the optimal values ​​to verify the accuracy of the hook load prediction results. If the prediction results agree well with the measured results, the values ​​of the weighting coefficients and the sticking force are determined; otherwise, the parameters are further adjusted. By generating orthogonal arrays, the influence of the weighting coefficients of drilling parameters such as wellbore curvature repair, wellbore roughness, and wellbore clearance ratio, as well as the weighting coefficient of the sticking force, on the casing run-in process can be efficiently evaluated. Orthogonal experiments not only reduce the number of experiments but also improve the accuracy and reliability of the model.

[0080] S303: Construct a blocking risk calculation model based on the weighting coefficients and the blocking force.

[0081] In some embodiments, the weighting coefficient and the sticking force can be substituted into the mechanical resistance model of the irregular wellbore to obtain the following sticking risk calculation model:

[0082]

[0083] In the formula, k is the wellbore curvature; a Irr d represents the weighting coefficient for wellbore curvature; d represents wellbore roughness; b represents the weighting coefficient for wellbore curvature. Irr The value of the weighting coefficient for wellbore roughness; x is the wellbore clearance ratio; g Irr The value of the weighting coefficient for the wellbore clearance ratio.

[0084] Considering that the mapping relationship between wellbore curvature and mechanical resistance can be expressed as F(k) = F g0 The mapping relationship between (1+ak), wellbore roughness, and mechanical resistance can be expressed as F(d)=F g0 The mapping relationship between (1+bd) and the wellbore clearance ratio and mechanical resistance can be expressed as F(x)=F g0 e -gx The mechanical resistance model for irregular wellbores can be further expressed as:

[0085] F m =F g0 (2+ak+bd+e -gx );

[0086] Considering the sticking force F of a regular wellbore g0 It can be a constant, or a resistance risk factor can be introduced. The relationship between the resistance risk factor and mechanical resistance can be defined as:

[0087] F m =kc;

[0088] In the formula, k is a constant. The weighting coefficient a of the obtained wellbore curvature can be used... Irr Weighting coefficient b for wellbore roughness Irr The weighting coefficient g of the wellbore clearance ratio Irr The sticking force F of a regular wellbore g0 Substitute F m =kc, thus obtaining the card blocking risk calculation model. At this time, k = 3F g0 .

[0089] In some embodiments, drilling parameter values ​​of the wellbore drilling tool can be substituted into the stuck pipe risk calculation model. This leads to the first sticking risk factor. Similarly, the drilling parameters of the wellbore casing can be substituted into the sticking risk calculation model. The second risk factor for the card was obtained.

[0090] In some embodiments, based on the finite element model of the casing of an irregular wellbore, the mapping relationship between drilling parameters and mechanical resistance can be obtained; based on the mapping relationship between drilling parameters and mechanical resistance, the mechanical resistance model of the irregular wellbore can be constructed using the plowing traction resistance theory as follows:

[0091] F m =F(k) + F(d) + F(x);

[0092] In the formula, F(k)=F g0 (1+ak) represents the mapping relationship between wellbore curvature and mechanical resistance; F g0 d is the sticking force of a regular wellbore; k is the wellbore curvature; a is the weighting coefficient of the wellbore curvature; F(d) = F g0 (1+bd) represents the mapping relationship between wellbore roughness and mechanical resistance; d is the wellbore roughness; b is the weighting coefficient of wellbore roughness; F(x)=F g0 e -gx This represents the mapping relationship between the wellbore clearance ratio and mechanical resistance; x is the wellbore clearance ratio; g is the weighting coefficient of the wellbore clearance ratio.

[0093] Based on the plowing traction resistance theory, the total mechanical resistance experienced by the casing during the running-in process in irregular wells can be regarded as the sum of all static mechanical resistance and all dynamic mechanical resistance caused by various drilling parameters. This allows for the integration of the mapping relationship between different drilling parameters and mechanical resistance, providing a more comprehensive and accurate description of the mechanical resistance during casing running-in in irregular wells.

[0094] A partial casing installation finite element model of a historical wellbore can be constructed based on historical drilling parameter data. The geometry of a wellbore may be irregular due to geological conditions, drilling technology, and other factors (e.g., elliptical wellbore, helical wellbore, or localized reduction in diameter). Therefore, it is necessary to accurately reconstruct the three-dimensional morphology of the wellbore based on logging data or wellbore imaging results. Specifically, the partial casing installation finite element model of a historical wellbore can be modeled according to its actual dimensions and structure to ensure that the model accurately reflects the mechanical properties of the casing.

[0095] After establishing a finite element model of the local casing of a historical wellbore, the material properties of the casing, wellbore, and drilling fluid can be defined. The casing's material properties include elastic modulus, Poisson's ratio, and density; these parameters affect the casing's stiffness and deformation behavior. The wellbore's material properties can be set according to the formation lithology; for example, sandstone, mudstone, or limestone have significantly different mechanical properties and need to be defined separately. Furthermore, the rheological properties of the drilling fluid (such as density and viscosity) can also be included in the model, because the drilling fluid not only exerts buoyancy on the casing but also affects its movement through viscous resistance.

[0096] The contact behavior between the casing and the wellbore is the primary cause of mechanical resistance, thus requiring precise setting of contact conditions. A frictional contact model can be used to define the friction coefficient between the casing and the wellbore. The value of the friction coefficient depends on the roughness of the wellbore, the lubrication properties of the drilling fluid, and the surface characteristics of the casing. Furthermore, contact type (such as hard contact or soft contact) can be considered to simulate the actual interaction between the casing and the wellbore.

[0097] Appropriate boundary conditions and loads can be applied to the local casing running finite element model of a historical wellbore to ensure the accuracy of the simulation results. Specifically, the wellbore boundary can be set as a fixed constraint to simulate the supporting effect of the formation. An axial force (such as a lowering or lifting force) is applied to the top of the casing to simulate the running operation in actual operation. In addition, drilling fluid pressure and gravity loads can be applied, taking into account their buoyancy and lateral pressure on the casing and simulating the casing's own weight.

[0098] Fine meshing can be performed on the wellbore and casing, especially in contact and stress concentration areas, to improve calculation accuracy. After meshing, finite element software (such as ANSYS, Abaqus, etc.) can be used for numerical solution to obtain the stress distribution, deformation, and contact force distribution of the casing, thereby obtaining the mapping relationship between each drilling parameter and mechanical resistance. Figure 4 The mapping relationship between wellbore clearance ratio and mechanical resistance is shown, where changes in wellbore clearance are characterized by variations in casing size. Figure 5 The mapping relationship between wellbore curvature and mechanical resistance is shown. Figure 6 The mapping relationship between wellbore roughness and mechanical resistance is shown, where the wellbore roughness is characterized by the wellbore diameter variation rate.

[0099] Based on the mapping relationship between each drilling parameter and mechanical resistance, the mechanical resistance caused / affected by each drilling parameter can be expressed as the product of the sticking force and the correction term in a regular wellbore.

[0100] For example, the mapping relationship between wellbore curvature and mechanical resistance can be expressed as:

[0101] F(k)=F g0 (1+ak);

[0102] In the formula, F g0 denoted as , where k is the wellbore curvature and a is the weighting coefficient for the wellbore curvature.

[0103] For example, the mapping relationship between wellbore roughness and mechanical resistance can be expressed as:

[0104] F(d)=F g0 (1+bd);

[0105] In the formula, F g0 d represents the sticking force of a regular wellbore, d represents the wellbore roughness, and b represents the weighting coefficient of the wellbore roughness.

[0106] For example, the mapping relationship between wellbore roughness and mechanical resistance can be expressed as:

[0107] F(x)=F g0 e -gx ;

[0108] In the formula, F g0 denoted as the sticking force of a regular wellbore, x is the wellbore clearance ratio, and g is the weighting coefficient of the wellbore clearance ratio.

[0109] The theory of traction resistance in plowing describes the resistance generated by the soil against the plow body during tillage. Its core principle is to decompose traction resistance into two parts: static resistance and dynamic resistance. Static resistance can include soil shear resistance, soil uplift resistance, and soil friction resistance. Soil shear resistance originates from the shearing action of the plow blades cutting into the soil; soil uplift resistance is related to the weight of the soil turned over by the plow body; and soil friction resistance is generated by the frictional force between the soil and the plow body surface. Dynamic resistance can include soil breaking resistance and inertial resistance. Soil breaking resistance is the resistance when the plow blades break up soil clumps; and inertial resistance is the inertial force that accelerates the soil as it is moved by the plow body.

[0110] Based on the plowing traction resistance theory, the total mechanical resistance experienced by casing during installation in irregular wellbores can also be considered as the sum of all static and dynamic mechanical resistances caused by various drilling parameters. For example, the mechanical resistance experienced by casing during installation in irregular wellbores is mainly related to three drilling parameters: wellbore curvature, wellbore roughness, and wellbore clearance ratio. Therefore, the total mechanical resistance experienced by casing during installation in irregular wellbores can be considered as the sum of the mechanical resistances caused by these three drilling parameters. The mapping relationship between these three drilling parameters and mechanical resistance can be integrated to construct a mechanical resistance model for irregular wellbores.

[0111] In some embodiments, based on historical drilling parameter data, mutual information values ​​among multiple drilling parameters can be calculated; based on the mutual information values ​​among the multiple drilling parameters, master control drilling parameters can be selected.

[0112] By quantifying the correlation between multiple drilling parameters using mutual information values, several key drilling parameters that have a significant impact on the drilling process can be selected, greatly reducing the interference of irrelevant factors on subsequent calculations of sticking risk factors and run-in capability index.

[0113] Mutual information can be used to measure the correlation between two random variables. In drilling parameter analysis, the mutual information value can reflect the dependency between different drilling parameters. Specifically, for two drilling parameters X and Y, their mutual information value I(X;Y) can be defined as:

[0114]

[0115] Here, p(x,y) represents the joint probability distribution of drilling parameters X and Y, and p(x) and p(y) represent the marginal probability distributions of drilling parameters X and Y, respectively. Based on historical drilling parameter data, the marginal probability distribution of each parameter and the joint probability distribution of parameter pairs can be estimated. Based on the mutual information formula, the mutual information value between each pair of drilling parameters can be calculated, and the mutual information matrix can be obtained. Figure 7 A schematic diagram of the mutual information matrix between drilling parameters is shown.

[0116] Based on the calculated mutual information values, the key drilling parameters with the greatest impact on the drilling process can be selected. High mutual information values ​​indicate a strong correlation between two parameters, significantly affecting the drilling process. Low mutual information values ​​indicate strong independence between two parameters, with a smaller impact on the drilling process. Drilling parameters can be ranked according to their mutual information values, filtering out those with strong correlations to other parameters. For example, a mutual information threshold can be set, selecting drilling parameters with mutual information values ​​greater than or equal to this threshold as key drilling parameters. These parameters typically have a significant impact on drilling efficiency, safety, or cost.

[0117] In some embodiments, a scatter plot of casing run-in characteristics for multiple drilling parameters can be generated based on historical drilling parameter data. As a basic form of statistical chart, the core function of a scatter plot is to intuitively and clearly reveal the potential relationship between two variables. Specifically, a scatter plot positions two drilling parameters on the X and Y axes respectively, so that each data point represents the correspondence between the two drilling parameters at a specific observation value. The distribution of points in the casing run-in characteristic scatter plot provides rich information about the relationship between the two drilling parameters. If the point distribution shows a clear linear trend, this usually means that there is a linear relationship between the two drilling parameters, i.e., a change in one drilling parameter can proportionally predict a change in the other. When the point distribution in the casing run-in characteristic scatter plot no longer follows a linear trend but exhibits a curve, U-shape, inverse U-shape, or other more complex shapes, it can be inferred that there is a non-linear relationship between the two drilling parameters. This non-linear relationship means that a change in one drilling parameter cannot be simply predicted by a linear function of the other drilling parameter, but requires a more complex mathematical model to describe it. Furthermore, the identification of such nonlinear relationships is of great significance for gaining a deeper understanding of the drilling process, optimizing drilling strategies, and improving drilling efficiency. Figure 8 A scatter plot of casing insertion characteristics among drilling parameters is shown. If multiple drilling parameters are non-linearly correlated, their mutual information values ​​can be calculated. Based on these mutual information values, the controlling drilling parameters can be selected, and a mechanical resistance model for irregular wellbores can be constructed.

[0118] In some embodiments, based on a sliding time window, mutual information values ​​among multiple drilling parameters can be calculated; a preset mutual information threshold can be adjusted according to the rate of change of the mutual information values ​​among the multiple drilling parameters; and a master control drilling parameter can be selected according to the adjusted mutual information threshold.

[0119] Traditional mutual information analysis is typically based on static historical datasets, assuming that the statistical properties between drilling parameters remain constant during the operation. However, actual drilling processes exhibit significant time-varying and nonlinear characteristics. For example, when the drill bit traverses different rock formations (such as sandstone and shale), the correlation between parameters such as drilling pressure and torque may abruptly change; as drilling depth increases, drill bit dulling leads to a gradual weakening of the coupling relationship between mechanical drilling rate and rotational speed; operations such as tripping in and out of the hole and circulating drilling fluid introduce transient disturbances, causing the parameter correlations to temporarily fail.

[0120] To address the aforementioned issues, a dynamic mutual information algorithm can be introduced, which updates the mutual information matrix between parameters in real time through a sliding time window. Specifically, the real-time acquired drilling parameters can be divided into continuous time windows based on fixed durations (e.g., 5 minutes) or event triggers (e.g., encountering a new formation). Within each window, the joint probability distribution of parameter pairs is calculated based on kernel density estimation or a maximum entropy model, allowing for dynamic updates of the mutual information values ​​and generating a time-varying mutual information matrix.

[0121] Based on the time-varying mutual information matrix, an exponentially weighted moving average method can be used to dynamically calibrate the mutual information threshold. Specifically, when the mutual information of a parameter pair is greater than or equal to the mutual information threshold, it is determined to be a primary control parameter pair for the current window; otherwise, it is downgraded to a secondary parameter. Based on the updated mutual information matrix and the threshold, a list of primary control parameters is output in real time. If the rate of change of the mutual information of a parameter exceeds a preset tolerance (e.g., 10%), an anomaly warning is triggered, and a control strategy is recommended (e.g., "Drilling pressure-torque mutual information suddenly increases; it is recommended to reduce the rotational speed to suppress stick-slip vibration").

[0122] Traditional fixed thresholds (such as mutual information > 0.7) may miss critical parameters when drilling through hard formations, while dynamic thresholds can automatically tighten or loosen the criteria according to changes in lithology. In addition, by reducing the computational load through sliding windows, real-time operation on edge devices (such as downhole sensors) is ensured, significantly improving the efficiency and safety of operations under complex formation conditions.

[0123] In some embodiments, a mechanical resistance model for irregular wellbores can be constructed based on master drilling parameters. Master drilling parameters may include wellbore curvature, wellbore roughness, and wellbore clearance ratio. Finite element simulations of irregular wellbores can be performed using master drilling parameters to obtain the mapping relationship between drilling parameters and mechanical resistance. Based on this mapping relationship, a mechanical resistance model for irregular wellbores can be constructed using the plowing traction resistance theory: F m =F(k)+F(d)+F(x), where F(k)=F g0 (1+ak) represents the mapping relationship between wellbore curvature and mechanical resistance; F g0 d is the sticking force of a regular wellbore; k is the wellbore curvature; a is the weighting coefficient of the wellbore curvature; F(d) = F g0 (1+bd) represents the mapping relationship between wellbore roughness and mechanical resistance; d is the wellbore roughness; b is the weighting coefficient of wellbore roughness; F(x)=F g0 e -gx This represents the mapping relationship between the wellbore clearance ratio and mechanical resistance; x is the wellbore clearance ratio; g is the weighting coefficient of the wellbore clearance ratio.

[0124] In some embodiments, if the first down-feed capability index is less than the second down-feed capability index, a genetic algorithm can be used to calculate the Pareto front solution corresponding to various well-drilling tool structures. Based on the Pareto front solution, the structure of the well-drilling tool can be adjusted.

[0125] By using genetic algorithms to calculate the Pareto front solutions for various wellbore drilling tool structures, on the one hand, it can replace manual trial and error, shortening the design cycle of wellbore drilling tools; on the other hand, it can avoid getting trapped in local optima and improve the running-in capability of wellbore drilling tools.

[0126] In traditional methods, single-objective optimization (i.e., optimizing only the first drilling capability index) may lead to a deterioration in drilling speed or cost. By introducing a genetic algorithm, multiple objectives can be considered simultaneously in the iterative optimization of drilling tools, thus avoiding deterioration in drilling speed or cost. For example: 1) Technical objective: maximizing the first drilling capability index; 2) Efficiency objective: increasing drilling speed; 3) Economic objective: reducing operating costs (such as drill string wear and time costs). Multiple sets of drill string parameter combinations (such as stiffness, length, and number of subs) can be randomly generated, and the first drilling parameter data corresponding to different drill string parameter combinations can be obtained based on the mapping relationship between different drill string parameters and drill string parameter combinations. The first drilling capability index, drilling speed, and cost parameters for each set of parameters are calculated and normalized into a multi-objective fitness function. In each iteration, the Pareto front solution (non-dominated solution) can be retained, and a new generation of parameter combinations can be continuously generated through crossover and mutation.

[0127] The wellbore drilling tool determination method provided in this specification can acquire first drilling parameter data corresponding to the wellbore drilling tool and second drilling parameter data corresponding to the wellbore casing; calculate a first sticking risk factor for the wellbore drilling tool based on the first drilling parameter data, the first sticking risk factor being used to indicate the probability of the wellbore drilling tool sticking; calculate a second sticking risk factor for the wellbore casing based on the second drilling parameter data, the second sticking risk factor being used to indicate the probability of the wellbore casing sticking; calculate a first running-in capability index for the wellbore drilling tool based on the stiffness of the wellbore drilling tool and the first sticking risk factor; calculate a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determine whether the wellbore drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index. Compared to existing methods, the embodiments in this specification can calculate the likelihood of sticking in both the drilling tool and the casing based on the corresponding drilling parameter data. This allows for a more comprehensive and accurate assessment of the running-in capability of both the drilling tool and casing, considering both deformation and sticking risk during well entry. Furthermore, by comparing the running-in capabilities of the drilling tool and casing, a rapid, scientific, and precise determination of their compatibility can be made.

[0128] Based on the above-described method for determining wellbore drilling tools, this specification also provides embodiments of a wellbore drilling tool determination device. For example... Figure 9 As shown, the wellbore drilling tool determining device 900 may specifically include the following modules:

[0129] The acquisition module 901 can be used to acquire the first drilling parameter data corresponding to the wellbore drilling tool and the second drilling parameter data corresponding to the wellbore casing.

[0130] The first calculation module 902 can be used to calculate the first stuck risk factor of the well-drilling tool based on the first drilling parameter data. The first stuck risk factor is used to indicate the possibility of the well-drilling tool getting stuck.

[0131] The second calculation module 903 can be used to calculate the second sticking risk factor of the well casing based on the second drilling parameter data. The second sticking risk factor is used to indicate the possibility of sticking in the well casing.

[0132] The third calculation module 904 can be used to calculate the first running-in capability index of the well-drilling tool based on the stiffness of the well-drilling tool and the first jamming risk factor.

[0133] The fourth calculation module 905 can be used to calculate the second running capability index of the well casing based on the stiffness of the well casing and the second sticking risk factor.

[0134] The determination module 906 can be used to determine whether the wellbore drilling tool and the wellbore casing are compatible based on the first downing capability index and the second downing capability index.

[0135] In some embodiments, the acquisition module 901 can be specifically used to construct a second casing running mechanical model for an irregular wellbore based on the first casing running mechanical model of a regular wellbore and the mechanical resistance model of an irregular wellbore; the regular wellbore refers to a wellbore with a regular circular cross-section, a well wall roughness less than or equal to a preset roughness threshold, and a well wall diameter variance less than or equal to a preset variance threshold; the irregular wellbore refers to a wellbore with an irregular circular cross-section, or a well wall roughness greater than a preset roughness threshold, or a well wall diameter variance greater than a preset variance threshold; the weighting coefficients of the drilling parameters in the mechanical resistance model of the irregular wellbore and the sticking force of the regular wellbore are solved; and a sticking risk calculation model is constructed based on the weighting coefficients and the sticking force.

[0136] In some embodiments, the acquisition module 901 may further be used to use the mechanical resistance model of the irregular wellbore as a correction term for the first casing running mechanical model, so as to construct the following second casing running mechanical model:

[0137]

[0138] In the formula, F represents the axial force of the drill string; s represents the well depth; EI represents the bending stiffness of the drill string; k represents the wellbore curvature; q represents the linear weight of the drill string; q represents the well inclination angle; m0 represents the axial friction coefficient; N0 represents the contact distribution force; F m The correction term, constructed based on the mechanical resistance model of the irregular wellbore, represents the mechanical resistance encountered when the casing of the irregular wellbore is run in.

[0139] In some embodiments, the acquisition module 901 can also be used to generate an orthogonal table based on the number of levels of the weighting coefficient and the number of levels of the sticking force; one row in the orthogonal table represents a value of the weighting coefficient and the sticking force; based on historical drilling parameter data, the second casing running mechanical model is used to generate a hook load prediction result corresponding to each value of the weighting coefficient and the sticking force; based on the difference between the hook load prediction result and the actual hook load result, the value of the weighting coefficient and the value of the sticking force are selected from the orthogonal table.

[0140] In some embodiments, the acquisition module 901 can also be used to substitute the weighting coefficient and the sticking force into the mechanical resistance model of the irregular wellbore to obtain the following sticking risk calculation model:

[0141]

[0142] In the formula, k is the wellbore curvature; a Irr d represents the weighting coefficient for wellbore curvature; d represents wellbore roughness; b represents the weighting coefficient for wellbore curvature. Irr The value of the weighting coefficient for wellbore roughness; x is the wellbore clearance ratio; g Irr The value of the weighting coefficient for the wellbore clearance ratio.

[0143] In some embodiments, the acquisition module 901 can also be used to obtain the mapping relationship between drilling parameters and mechanical resistance based on the finite element model of the casing of the irregular wellbore; and to construct the following mechanical resistance model of the irregular wellbore using the plowing traction resistance theory based on the mapping relationship between drilling parameters and mechanical resistance:

[0144] F m =F(k) + F(d) + F(x);

[0145] In the formula, F(k)=F g0 (1+ak) represents the mapping relationship between wellbore curvature and mechanical resistance; F g0 To represent the sticking force of a regular wellbore; k is the wellbore curvature; a is the weighting coefficient of the wellbore curvature; F(d) = F g0(1+bd) represents the mapping relationship between wellbore roughness and mechanical resistance; d is the wellbore roughness; b is the weighting coefficient of wellbore roughness; F(x)=F g0 e -gx This represents the mapping relationship between the wellbore clearance ratio and mechanical resistance; x is the wellbore clearance ratio; g is the weighting coefficient of the wellbore clearance ratio.

[0146] In some embodiments, the determining module 906 may be specifically used to determine that the wellbore drilling tool is matched with the wellbore casing if the first downhole capability index is greater than or equal to the second downhole capability index.

[0147] In some embodiments, the determining module 906 may further be used to: adjust the structure of the well-drilling tool if the first downhole capability index is less than the second downhole capability index; acquire drilling parameter data corresponding to the adjusted well-drilling tool as new first drilling parameter data; calculate a new first downhole capability index of the well-drilling tool based on the stiffness of the well-drilling tool and the first sticking risk factor; iteratively execute the above steps until the first downhole capability index is greater than or equal to the second downhole capability index; and determine that the adjusted well-drilling tool matches the wellbore casing.

[0148] The wellbore drilling tool determining device provided in the embodiments of this specification can acquire first drilling parameter data corresponding to the wellbore drilling tool and second drilling parameter data corresponding to the wellbore casing; calculate a first sticking risk factor for the wellbore drilling tool based on the first drilling parameter data, the first sticking risk factor being used to indicate the possibility of the wellbore drilling tool getting stuck; calculate a second sticking risk factor for the wellbore casing based on the second drilling parameter data, the second sticking risk factor being used to indicate the possibility of the wellbore casing getting stuck; calculate a first running-in capability index for the wellbore drilling tool based on the stiffness of the wellbore drilling tool and the first sticking risk factor; calculate a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determine whether the wellbore drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index. Compared to existing methods, the embodiments in this specification can calculate the likelihood of sticking in both the drilling tool and the casing based on the corresponding drilling parameter data. This allows for a more comprehensive and accurate assessment of the running-in capability of both the drilling tool and casing, considering both deformation and sticking risk during well entry. Furthermore, by comparing the running-in capabilities of the drilling tool and casing, a rapid, scientific, and precise determination of their compatibility can be made.

[0149] It should be noted that the units, devices, or modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. For ease of description, the above devices are described by dividing them into various modules according to their functions. Of course, in implementing this specification, the functions of each module can be implemented in one or more software and / or hardware, or the module that implements the same function can be implemented by a combination of multiple sub-modules or sub-units, etc. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection between the devices or units shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0150] This specification also provides a computer device for determining a wellbore drilling tool, including a processor and a memory for storing processor-executable instructions. Specifically, the processor can execute the following steps according to the instructions: acquiring first drilling parameter data corresponding to the wellbore drilling tool and second drilling parameter data corresponding to the wellbore casing; calculating a first sticking risk factor for the wellbore drilling tool based on the first drilling parameter data, the first sticking risk factor representing the probability of the wellbore drilling tool sticking; calculating a second sticking risk factor for the wellbore casing based on the second drilling parameter data, the second sticking risk factor representing the probability of the wellbore casing sticking; calculating a first running-in capability index for the wellbore drilling tool based on the stiffness of the wellbore drilling tool and the first sticking risk factor; calculating a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determining whether the wellbore drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index.

[0151] To execute the above instructions more accurately, please refer to... Figure 10 As shown in the embodiments of this specification, another specific computer device 1000 is also provided, wherein the computer device 1000 includes a network communication port 1001, a processor 1002 and a memory 1003, and the above structures are connected by internal cables so that the various structures can perform specific data interaction.

[0152] The processor 1002 can specifically be used to acquire first drilling parameter data corresponding to the ventilated drilling tool and second drilling parameter data corresponding to the wellbore casing; calculate a first sticking risk factor for the ventilated drilling tool based on the first drilling parameter data, the first sticking risk factor representing the probability of the ventilated drilling tool sticking; calculate a second sticking risk factor for the wellbore casing based on the second drilling parameter data, the second sticking risk factor representing the probability of the wellbore casing sticking; calculate a first running-in capability index for the ventilated drilling tool based on the stiffness of the ventilated drilling tool and the first sticking risk factor; calculate a second running-in capability index for the wellbore casing based on the stiffness of the wellbore casing and the second sticking risk factor; and determine whether the ventilated drilling tool and the wellbore casing are compatible based on the first running-in capability index and the second running-in capability index.

[0153] The memory 1003 can be used to store the corresponding instruction program.

[0154] In this embodiment, the network communication port 1001 can be a virtual port bound to different communication protocols, thereby enabling the sending or receiving of different data. For example, the network communication port can be a port responsible for web data communication, a port responsible for FTP data communication, or a port responsible for email data communication. Furthermore, the network communication port can also be a physical communication interface or communication chip. For example, it can be a wireless mobile network communication chip, such as GSM or CDMA; it can also be a Wi-Fi chip; or it can be a Bluetooth chip.

[0155] In this embodiment, the processor 1002 can be implemented in any suitable manner. For example, the processor can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers, etc. This specification is not limiting.

[0156] In this embodiment, the memory 1003 includes volatile memory and non-volatile memory. The memory 1003 can include multiple layers. In digital systems, anything that can store binary data can be a memory; in integrated circuits, a circuit with storage function but no physical form is also called a memory, such as RAM, FIFO, etc.; in a system, a storage device with a physical form is also called a memory, such as a memory stick, TF card, etc.

[0157] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer 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 computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0159] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0160] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0161] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for determining wellbore drilling tools, characterized in that, The method includes: Based on the mechanical model of the first casing run-in of a regular wellbore and the mechanical resistance model of an irregular wellbore, a mechanical model of the second casing run-in of an irregular wellbore is constructed. A regular wellbore is defined as one with a regular circular cross-section, a wall roughness less than or equal to a preset roughness threshold, and a diameter variance less than or equal to a preset variance threshold. An irregular wellbore is defined as one with an irregular circular cross-section, or a wall roughness greater than a preset roughness threshold, or a diameter variance greater than a preset variance threshold. The weighting coefficients of the drilling parameters and the sticking force of the regular wellbore are calculated in the mechanical resistance model of the irregular wellbore. Substituting the weighting coefficients and the sticking force into the mechanical resistance model of the irregular wellbore, the following sticking risk calculation model is obtained: In the formula, For wellbore curvature; The value of the weighting coefficient for wellbore curvature; For well wall roughness; The value of the weighting coefficient for wellbore roughness; The wellbore clearance ratio; The value of the weighting coefficient for the wellbore clearance ratio; Acquire the first drilling parameter data corresponding to the wellbore drilling tools and the second drilling parameter data corresponding to the wellbore casing; Based on the first drilling parameter data, the first stuck-out risk factor is calculated using the stuck-out risk calculation model. The first stuck-out risk factor is used to represent the possibility of the well-drilling tool getting stuck. Based on the second drilling parameter data, the second sticking risk factor is calculated using the sticking risk calculation model. The second sticking risk factor is used to represent the possibility of sticking in the wellbore casing. Calculate the first running-in capability index of the well-drilling tool based on the stiffness of the well-drilling tool and the first sticking risk factor; The second running-in capability index of the well casing is calculated based on the stiffness of the well casing and the second sticking risk factor. Based on the first and second downfeed capability indices, determine whether the drilling tools and well casing are compatible.

2. The method according to claim 1, characterized in that, The construction of a second casing running mechanical model for an irregular wellbore, based on the first casing running mechanical model for a regular wellbore and the mechanical resistance model for an irregular wellbore, includes: The mechanical resistance model of the irregular wellbore is used as a correction term for the first casing running mechanical model to construct the following second casing running mechanical model: ； In the formula, This represents the axial force on the drill string; Indicates the depth of the well; Indicates the bending stiffness of the drill string; Indicates the wellbore curvature; Indicates the weight of the drill string line; Indicates the well inclination angle; Indicates the axial friction coefficient; Indicates the contact force distribution; The correction term, constructed based on the mechanical resistance model of the irregular wellbore, represents the mechanical resistance encountered when the casing of the irregular wellbore is run in.

3. The method according to claim 1, characterized in that, The process of determining the weighting coefficients of drilling parameters and the sticking force of regular wellbores in the solution of the irregular wellbore mechanical resistance model includes: An orthogonal table is generated based on the number of levels of the weighting coefficient and the number of levels of the blocking force; a row in the orthogonal table represents one value of the weighting coefficient and the blocking force. Based on historical drilling parameter data, the second casing running mechanical model is used to generate the hook load prediction results corresponding to each value of the weighting coefficient and the sticking force. Based on the difference between the predicted hook load and the measured hook load, the values ​​of the weighting coefficient and the value of the blocking force are selected in the orthogonal table.

4. The method according to claim 1, characterized in that, The method further includes: Based on the finite element model of the casing of irregular wellbore, the mapping relationship between drilling parameters and mechanical resistance is obtained; Based on the mapping relationship between drilling parameters and mechanical resistance, the mechanical resistance model for irregular wellbores is constructed using the plowing traction resistance theory: ； In the formula, This represents the mapping relationship between wellbore curvature and mechanical resistance. To represent the sticking force of a regular wellbore; For wellbore curvature; This is the weighting coefficient for the wellbore curvature; This represents the mapping relationship between wellbore roughness and mechanical resistance. For well wall roughness; This is the weighting coefficient for wellbore roughness; This indicates the mapping relationship between the wellbore clearance ratio and mechanical resistance. The wellbore clearance ratio; This is the weighting coefficient for the wellbore clearance ratio.

5. The method according to claim 1, characterized in that, The step of determining whether the drilling tools and wellbore casing are compatible based on the first and second down-the-hole capability indices includes: If the first down-feeding capability index is greater than or equal to the second down-feeding capability index, it is determined that the well-drilling tool and the well casing are matched.

6. The method according to claim 1, characterized in that, The step of determining whether the drilling tools and wellbore casing are compatible based on the first and second down-the-hole capability indices includes: If the first downhole capability index is less than the second downhole capability index, adjust the structure of the well-drilling tool; Obtain the drilling parameter data corresponding to the adjusted wellbore drill string as the new first drilling parameter data; Calculate the new first entry capability index of the well-drilling tool based on the stiffness of the well-drilling tool and the first sticking risk factor; The above steps are executed iteratively until the first downlink capability index is greater than or equal to the second downlink capability index. The adjusted wellbore drilling tool is confirmed to be compatible with the wellbore casing.

7. A wellbore drilling tool determining device, characterized in that, The device is used for: Based on the mechanical model of the first casing run-in of a regular wellbore and the mechanical resistance model of an irregular wellbore, a mechanical model of the second casing run-in of an irregular wellbore is constructed. A regular wellbore is defined as one with a regular circular cross-section, a wall roughness less than or equal to a preset roughness threshold, and a diameter variance less than or equal to a preset variance threshold. An irregular wellbore is defined as one with an irregular circular cross-section, or a wall roughness greater than a preset roughness threshold, or a diameter variance greater than a preset variance threshold. The weighting coefficients of the drilling parameters and the sticking force of the regular wellbore are calculated in the mechanical resistance model of the irregular wellbore. Substituting the weighting coefficients and the sticking force into the mechanical resistance model of the irregular wellbore, the following sticking risk calculation model is obtained: In the formula, For wellbore curvature; The value of the weighting coefficient for wellbore curvature; For well wall roughness; The value of the weighting coefficient for wellbore roughness; The wellbore clearance ratio; The value of the weighting coefficient for the wellbore clearance ratio; The device includes: The acquisition module is used to acquire the first drilling parameter data corresponding to the wellbore drilling tool and the second drilling parameter data corresponding to the wellbore casing; The first calculation module is used to calculate the first stuck-out risk factor based on the first drilling parameter data and the stuck-out risk calculation model. The first stuck-out risk factor is used to represent the probability of the well-drilling tool getting stuck. The second calculation module is used to calculate the second sticking risk factor based on the second drilling parameter data and the sticking risk calculation model. The second sticking risk factor is used to represent the possibility of the well casing sticking. The third calculation module is used to calculate the first running-in capability index of the well-drilling tool based on the stiffness of the well-drilling tool and the first jamming risk factor. The fourth calculation module is used to calculate the second running-in capability index of the well casing based on the stiffness of the well casing and the second sticking risk factor. The determination module is used to determine whether the drilling tools and the well casing are compatible based on the first and second down-feeding capacity indices.

8. A computer 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 computer program, it implements the method as described in any one of claims 1-6.

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