Bit parameter determination method and apparatus

Abstract

The application provides a drill bit parameter determination method and device, and relates to the technical field of deep well drilling. The method comprises the following steps: generating a dynamic stress distribution map of a composite bit drill bit according to triaxial stress data corresponding to each composite piece on the composite bit drill bit; the dynamic stress distribution map is used to represent the dynamic stress distribution and change characteristics of the surface of the composite bit drill bit; determining an optimal target value of a structure parameter of the composite bit drill bit according to the dynamic stress distribution map and a drill bit finite element model of the composite bit drill bit constructed in advance; and using the optimal target value of the structure parameter as an optimization target to optimize the structure parameter of the composite bit drill bit, so as to obtain an optimal structure parameter of the composite bit drill bit. The device executes the above method. The drill bit parameter determination method and device provided in the embodiment of the application can improve the drilling performance under the high-temperature and high-pressure working condition of deep well drilling by optimizing the drill bit parameter, and prolong the service life of the drill bit.

Description

Technical Field

[0001] This invention relates to the field of deep well drilling technology, specifically to a method and apparatus for determining drill bit parameters. Background Technology

[0002] With the continued growth of global energy demand, the development of deep oil and gas resources and geothermal energy has become an increasingly prominent focus. During deep well drilling for these resources, drill bits must withstand extreme high temperatures (above 200 degrees Celsius) and high pressures (above 200 MPa) for extended periods, placing stringent demands on their rock-breaking efficiency, wear resistance, and structural reliability. Composite drill bits, due to their high hardness and wear resistance, have become a core tool for deep well drilling under high-temperature and high-pressure conditions.

[0003] Currently, existing optimization research on composite drill bits mainly focuses on improving material properties or analyzing the static stress distribution of the drill bit to guide local structural improvements. However, improving material properties has its limitations, and analyzing the static stress distribution cannot fully reflect the stress situation of composite drill bits under high temperature and high pressure conditions in deep well drilling. The lack of a systematic structural optimization design logic results in poor drilling performance and short service life for the designed composite drill bits under high temperature and high pressure conditions. Summary of the Invention

[0004] To address the problems in the prior art, embodiments of the present invention provide a method and apparatus for determining drill bit parameters, which can at least partially solve the problems existing in the prior art.

[0005] On one hand, the present invention proposes a method for determining drill bit parameters, including:

[0006] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0007] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0008] The step of generating a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit includes:

[0009] Stress characteristics are identified for the triaxial stress data corresponding to each composite piece, and the dynamic stress distribution map is generated based on the three-dimensional stress model of the composite piece drill bit surface constructed according to the identified stress characteristics.

[0010] The step of determining the structural parameter optimization target value of the composite drill bit based on the dynamic stress distribution spectrum and the pre-constructed finite element model of the composite drill bit includes:

[0011] Numerical simulation calculations were performed on the dynamic stress distribution spectrum based on the pre-constructed finite element model of the composite drill bit to obtain the first stress response result;

[0012] In response to the parameter setting action triggered based on the first stress response result, the target value for optimizing the structural parameters of the composite drill bit is determined.

[0013] The structural parameters are of various types, and each type of structural parameter corresponds to multiple structural parameter values. Correspondingly, optimizing the structural parameters of the composite drill bit using the optimization target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit includes:

[0014] Multiple structural parameter values ​​of various types of structural parameters are combined to obtain multiple structural design schemes;

[0015] Each structural design scheme is optimized based on the target value of the structural parameters to obtain the optimal structural parameters corresponding to the optimal structural design scheme.

[0016] The step of optimizing each structural design scheme based on the target value of the structural parameters includes:

[0017] The target value is optimized based on the structural parameters, and each structural design scheme is optimized using the crossover and mutation operation in the genetic algorithm.

[0018] The step of optimizing the target value based on the structural parameters and optimizing each structural design scheme using the crossover and mutation operation in the genetic algorithm includes:

[0019] Based on different composite sheet arrangements, drill bit body shapes, and support ring designs, multiple structural design schemes were constructed to obtain an initial structural population, with each structural design scheme corresponding to a structural population individual.

[0020] Based on the target value of the structural parameters, the first fitness score corresponding to each design structural scheme is calculated using a preset fitness function. The first fitness score includes the stress uniform distribution score, the stress peak reduction score, the rock breaking efficiency maximization score, and the wear rate minimization score.

[0021] Based on the first fitness score, target structural individuals with a score higher than the first preset threshold are selected from the initial structural population. The target structural individuals are then iteratively optimized through crossover and mutation until a structural design scheme that satisfies the structural parameter optimization target value is obtained. The structural parameters corresponding to the structural design scheme that satisfies the structural parameter optimization target value are determined as the optimized structural parameters.

[0022] The method for determining drill bit parameters further includes:

[0023] The three-dimensional geometric model of the composite drill bit is optimized based on the optimal structural parameters of the composite drill bit to obtain an optimized three-dimensional geometric model, and an optimized dynamic stress distribution map is obtained based on the optimized three-dimensional geometric model.

[0024] Numerical simulation calculations were performed on the optimized dynamic stress distribution spectrum based on the pre-constructed finite element model of the composite drill bit to obtain the second stress response result;

[0025] In response to a parameter setting action triggered based on the second stress response result, the target value for optimizing the material parameters of the composite drill bit is determined;

[0026] The material parameters of the composite drill bit are optimized using the aforementioned material parameter optimization target value as the optimization objective to obtain the optimal material parameters of the composite drill bit.

[0027] The material parameters are of various types, and each type of material parameter corresponds to multiple material parameter values. Accordingly, optimizing the material parameters of the composite drill bit using the material parameter optimization target value as the optimization objective to obtain the optimal material parameters of the composite drill bit includes:

[0028] By combining multiple material parameter values ​​of various types of material parameters, multiple material design schemes can be obtained;

[0029] Optimize each material design scheme according to the target value of the material parameters to obtain the optimal material parameters corresponding to the optimal material design scheme.

[0030] The step of optimizing each material design scheme based on the target value of the material parameters includes:

[0031] The target value is optimized based on the material parameters, and each material design scheme is optimized using the crossover and mutation operation in the genetic algorithm.

[0032] The step of optimizing the target value based on the material parameters and optimizing each material design scheme using the crossover and mutation operation in the genetic algorithm includes:

[0033] Multiple material design schemes were constructed based on different alloy element addition ratios, diamond particle arrangement and bonding methods to obtain an initial material population, with each material design scheme corresponding to an individual material population.

[0034] The target value is optimized based on the material parameters, and the second fitness score corresponding to each material design scheme is calculated using a preset fitness function. The second fitness score includes a stability score and a wear resistance score.

[0035] Based on the second fitness score, target material population individuals with a score higher than the second preset threshold are selected from the initial material population. The target material population individuals are then iteratively optimized through crossover and mutation until a material design scheme that meets the material parameter optimization target value is obtained. The material parameters corresponding to the material design scheme that meets the material parameter optimization target value are then determined as the optimized material parameters.

[0036] On one hand, the present invention proposes a drill bit parameter determination device comprising:

[0037] The generation unit is used to generate a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0038] The determining unit is used to determine the structural parameter optimization target value of the composite drill bit based on the dynamic stress distribution spectrum and the pre-constructed finite element model of the composite drill bit, and to optimize the structural parameters of the composite drill bit using the structural parameter optimization target value as the optimization target to obtain the optimal structural parameters of the composite drill bit.

[0039] In another aspect, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the following method:

[0040] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0041] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0042] This invention provides a computer-readable storage medium, comprising:

[0043] The computer-readable storage medium stores a computer program that, when executed by a processor, implements the following method:

[0044] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0045] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0046] This invention also provides a computer program product, which includes a computer program that, when executed by a processor, implements the following method:

[0047] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0048] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0049] The drill bit parameter determination method and apparatus provided in this invention generate a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece. The dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit. Based on the dynamic stress distribution map and a pre-constructed finite element model of the composite drill bit, the structural parameter optimization target value of the composite drill bit is determined. The structural parameter optimization target value is used as the optimization target to optimize the structural parameters of the composite drill bit, thereby obtaining the optimal structural parameters of the composite drill bit. The optimized drill bit parameters can improve drilling performance under high temperature and high pressure conditions in deep well drilling and extend the service life of the drill bit. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In the drawings:

[0051] Figure 1 This is a flowchart illustrating a method for determining drill bit parameters according to an embodiment of the present invention.

[0052] Figure 2 This is a schematic diagram of the structure of a drill bit parameter determination device provided in an embodiment of the present invention.

[0053] Figure 3 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments and descriptions of the present invention are used to explain the present invention, but are not intended to limit the present invention. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other.

[0055] Figure 1 This is a flowchart illustrating a method for determining drill bit parameters according to an embodiment of the present invention, as shown below. Figure 1 As shown, the drill bit parameter determination method provided in this embodiment of the invention includes:

[0056] Step S1: Generate a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece in the composite drill bit; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0057] Step S2: Determine the target value for the structural parameters of the composite drill bit based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit. Optimize the structural parameters of the composite drill bit using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0058] In step S1 above, the device generates a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece. The dynamic stress distribution map characterizes the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit. The device can be a computer device that executes this method. The acquisition, storage, use, and processing of data in this application comply with relevant regulations. Deep well drilling can refer to drilling operations in a wellbore with a depth of 4500 meters to 6000 meters.

[0059] It can simulate the high temperature and high pressure conditions encountered during deep well drilling in a laboratory environment, such as a temperature of 200 degrees Celsius and a pressure of 210 MPa.

[0060] Composite diamond (PDC) drill bits are specifically formed by embedding multiple polycrystalline diamond (PCD) composite sheets into the drill bit body. Due to their excellent cutting performance and long service life, they are widely used in drilling operations in hard rock formations and other complex geological conditions.

[0061] Triaxial stress testing is performed on each polycrystalline diamond composite piece in the composite drill bit. Specifically, sensor technology can be used to ensure accurate capture of the triaxial stress changes of each composite piece under different pressure and temperature conditions. Triaxial stress includes radial stress, tangential stress, and axial stress.

[0062] The step of generating a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit includes:

[0063] Stress characteristics are identified for the triaxial stress data corresponding to each composite piece, and the dynamic stress distribution map is generated based on the three-dimensional stress model of the composite piece drill bit surface constructed according to the identified stress characteristics.

[0064] The collected triaxial stress data were processed using data analysis software to identify key stress features and construct a three-dimensional stress model covering the entire surface of the composite drill bit. This model not only reflects the static stress distribution but also displays the dynamic stress characteristics that change over time. Using this three-dimensional stress model, combined with computer graphics technology, a dynamic stress distribution map was generated.

[0065] A three-dimensional stress model is the result of analysis of specific physical quantities, focusing on calculating the three-dimensional stress tensor distribution of a drill bit under load.

[0066] After obtaining the triaxial stress data corresponding to each composite piece, the triaxial stress data of each composite piece can be filtered, denoised and interpolated, and a dynamic stress distribution map corresponding to the composite piece drill bit can be generated based on the processed triaxial stress data.

[0067] In a laboratory environment, a high-precision, high-temperature and high-pressure resistant miniature triaxial stress sensor is installed to collect triaxial stress data of each composite sheet in real time. The triaxial stress includes radial stress, tangential stress and axial stress.

[0068] Using wireless or wired transmission technology, data collected in real time from sensors is sent to a data collection system on a ground station or drilling platform.

[0069] To eliminate high-frequency noise interference in the signal, the raw triaxial stress data can be low-pass filtered. Specifically, digital filters such as FIR (Finite Impulse Response) or IIR (Infinite Impulse Response) filters can be used, with the cutoff frequency adjusted according to actual needs.

[0070] To further remove random noise from the data, denoising methods such as wavelet transform can be used, which can not only effectively reduce noise but also retain important feature information of the data. Since there may be intervals in the sensor arrangement, resulting in discontinuous data, it is necessary to interpolate the discrete data points to obtain a continuous dataset. Specifically, linear interpolation, spline interpolation, etc. can be used to ensure that the stress change trend is accurately reflected while avoiding overfitting.

[0071] Based on the processed triaxial stress data, a three-dimensional stress model of the composite drill bit is constructed using computer-aided design (CAD) software. This three-dimensional stress model should include the location of all composite sections and their corresponding triaxial stress data. Then, using specialized stress analysis software (such as ANSYS, ABAQUS, etc.), the three-dimensional stress model and triaxial stress data are imported to perform a detailed stress analysis.

[0072] By setting different time points under high-temperature and high-pressure conditions, the stress evolution during deep well drilling was simulated. Finally, a graphics generation tool was used to transform the stress analysis results into an intuitive and easy-to-understand dynamic stress distribution map. This dynamic stress distribution map not only displays the magnitude and direction of stress at any location on the target drill bit, but also shows the dynamic distribution and variation characteristics of stress over time and under different operating conditions through animation. This is of great significance for improving the design efficiency and performance optimization of drill bits.

[0073] Furthermore, the specific execution process for obtaining the triaxial stress data of each composite material on the composite material drill bit under high temperature and high pressure conditions is as follows:

[0074] The high-temperature and high-pressure working conditions corresponding to the target formation environment are simulated in the high-temperature and high-pressure experimental device, and each composite piece on the target drill bit is independently drilled and tested using a rotary cutting test platform with a preset rotation speed and preset cutting depth; the triaxial stress data of each composite piece is collected in real time through an embedded triaxial stress sensor array.

[0075] The actual temperature and pressure corresponding to the target formation environment are 200 degrees Celsius and 210 MPa, respectively; the preset rotation speed ranges from 30 to 60 revolutions per minute; and the preset cutting depth ranges from 1 mm to 2.5 mm per revolution.

[0076] The rotary cutting test platform can support composite drill bits to work at preset speeds (30-60 rpm) and preset cutting depths (1 mm-2.5 mm / rpm). The platform integrates speed adjustment and position control functions, which can accurately meet the testing requirements under different working conditions.

[0077] Independent drilling tests are conducted on each composite section, meaning that cutting force is applied to only one composite section at a time. High-sensitivity, high-temperature and high-pressure resistant triaxial stress sensors are embedded near each composite section of the target drill bit, forming a triaxial stress sensor array. This array accurately captures the actual stress changes acting on the composite section. Triaxial stress data for each composite section is acquired in real time via a signal acquisition system connected to each sensor. Using reliable wireless or wired communication technology, the data acquired from the triaxial stress sensor array is transmitted to a data acquisition system at a ground station or drilling platform for subsequent analysis.

[0078] In step S2 above, the device determines the target value for structural parameter optimization of the composite drill bit based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit. Using this target value as the optimization objective, the device optimizes the structural parameters of the composite drill bit to obtain the optimal structural parameters of the composite drill bit. The step of determining the target value for structural parameter optimization of the composite drill bit based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit includes:

[0079] Numerical simulation calculations were performed on the dynamic stress distribution spectrum based on the pre-constructed finite element model of the composite drill bit to obtain the first stress response result;

[0080] In response to the parameter setting action triggered based on the first stress response result, the target value for optimizing the structural parameters of the composite drill bit is determined.

[0081] The finite element model of a drill bit is a tool framework for numerical simulation. It discretizes the geometry of the drill bit into mesh elements, assigns material properties, and defines boundary conditions to form a computable mathematical representation. This model can serve a variety of analysis objectives (such as dynamics, heat conduction, modal analysis, etc.), and its core is the modeling method rather than a specific output result.

[0082] A pre-constructed finite element model of the composite drill bit is used to accurately describe key factors such as the geometry, material properties, and boundary conditions of the composite drill bit; that is, this finite element model includes the original structural parameters of the composite drill bit. A dynamic stress distribution map is input into this finite element model, and corresponding high-temperature and high-pressure operating parameters are set. By solving the finite element equations, the stress response of the composite drill bit under such high-temperature and high-pressure conditions in deep well drilling is simulated, thereby obtaining the first stress response results. These first stress response results include, but are not limited to, stress concentration areas, peak stress, stress distribution patterns, impact stress magnitude, rock-breaking efficiency, and wear rate.

[0083] The optimization objectives of structural parameters may include uniform stress distribution, reduction of peak stress, maximization of rock breaking efficiency, and minimization of wear rate. The quantitative values ​​of the above optimization objectives of structural parameters are called the optimization objective values ​​of structural parameters.

[0084] The structural parameters that need to be optimized may include the arrangement of composite plates, the shape of the drill bit body, and the design of the support ring.

[0085] The parameters can be set manually based on the first stress response results, thereby obtaining the target values ​​for structural parameter optimization.

[0086] The structural parameters are of various types, and each type of structural parameter corresponds to multiple structural parameter values; correspondingly, the optimization of the structural parameters of the composite drill bit using the optimization target value of the structural parameters as the optimization target to obtain the optimal structural parameters of the composite drill bit includes:

[0087] Multiple structural parameter values ​​of various types of structural parameters are combined to obtain multiple structural design schemes;

[0088] Each structural design scheme is optimized based on the target value of the structural parameters to obtain the optimal structural parameters corresponding to the optimal structural design scheme.

[0089] To find the optimal structural design scheme, multiple structural design schemes can be pre-constructed based on different composite sheet arrangements, drill bit body shapes, and support ring designs. Then, a genetic algorithm is used to iteratively optimize the original structural parameters based on multiple structural design schemes.

[0090] Genetic algorithms are search heuristics that simulate the process of natural selection. They explore the design space through operations such as selection, crossover, and mutation, gradually approaching the optimal solution. The main structural parameters considered during optimization include the arrangement of composite plates, the shape of the drill bit body, and the design of the support rings. Each iteration updates these parameters and re-evaluates their corresponding performance metrics until the optimal combination that satisfies all structural optimization objectives—the optimal structural parameters—is found.

[0091] Furthermore, the optimal structural parameters can be verified to ensure they achieve the expected results under actual high-temperature and high-pressure conditions. After thorough verification, the optimal structural parameters are determined as the final design parameters for the composite drill bit, and a prototype composite drill bit is manufactured accordingly for field testing.

[0092] By collecting triaxial dynamic stress data of each polycrystalline diamond composite sheet under high temperature and high pressure conditions and constructing a dynamic stress distribution map covering the entire drill bit area, the limitations of traditional static analysis are overcome. The dynamic stress distribution map is input into the finite element model to accurately simulate the multiaxial stress response of the drill bit under high temperature and high pressure conditions in deep well drilling. It effectively identifies the correlation between stress concentration areas and rock breaking efficiency. Based on the stress response results, a comprehensive optimization objective is set to achieve uniform stress distribution, peak value reduction, maximization of rock breaking efficiency, and minimization of wear rate. Through a genetic algorithm, the arrangement of composite sheets, the shape of the drill bit body, and the design of the support ring are systematically adjusted to achieve full-dimensional optimization of structural parameters. This significantly improves the drilling performance and service life of the drill bit in deep well drilling, and enhances the safety and economy of deep well drilling operations.

[0093] The optimization of each structural design scheme based on the target value of the structural parameters includes:

[0094] The target value is optimized based on the structural parameters, and each structural design scheme is optimized using the crossover and mutation operation in a genetic algorithm. Further specific details include:

[0095] Based on different composite sheet arrangements, drill bit body shapes, and support ring designs, multiple structural design schemes were constructed to obtain an initial structural population, with each structural design scheme corresponding to a structural population individual.

[0096] Based on the target value of the structural parameters, the first fitness score corresponding to each design structural scheme is calculated using a preset fitness function. The first fitness score includes the stress uniform distribution score, the stress peak reduction score, the rock breaking efficiency maximization score, and the wear rate minimization score.

[0097] Based on the first fitness score, target structural individuals with a score higher than the first preset threshold are selected from the initial structural population. The target structural individuals are then iteratively optimized through crossover and mutation until a structural design scheme that satisfies the structural parameter optimization target value is obtained. The structural parameters corresponding to the structural design scheme that satisfies the structural parameter optimization target value are determined as the optimized structural parameters.

[0098] The arrangement of composite sheets includes different numbers, positions and angles of composite sheets (e.g., tilt angles of 15°, 20°, etc.).

[0099] The drill bit body shape includes circular, elliptical, or other streamlined designs to reduce resistance.

[0100] Support ring design includes the number and location of support reinforcement rings added or removed at specific locations (such as adding support rings to the leading edge).

[0101] For example, suppose 10 different structural design schemes are created as an initial population, each structural design representing a possible combination. Scheme A: Composite sheet with a 15° tilt angle, circular body, no support ring; Scheme B: Composite sheet with a 20° tilt angle, elliptical body, with a support ring added to the leading edge, and so on.

[0102] The fitness score between each structural optimization scheme and the structural optimization objective is calculated using a preset fitness function. This first fitness score includes the stress uniformity distribution score, the stress peak reduction score, the rock breaking efficiency maximization score, and the wear rate minimization score.

[0103] Among them, the stress uniformity distribution fraction is calculated as the standard deviation of the stress on the entire drill bit surface or the ratio of the maximum to the minimum stress.

[0104] Peak stress reduction score: The maximum stress value is used directly as the evaluation index;

[0105] Rock breaking efficiency maximization score: can be measured by the depth of drilling per unit time;

[0106] Wear rate minimization fraction: predicting the wear rate of a material under specific conditions based on experimental data.

[0107] Specifically, corresponding weighting coefficients can be set for the stress uniformity distribution score, stress peak reduction score, rock breaking efficiency maximization score, and wear rate minimization score. These weighting coefficients are used to represent the importance of structural optimization, and finally, the first fitness score of each structural design scheme is obtained by weighting.

[0108] Based on the first fitness score, select high-performing individuals from the initial structural population to serve as parent individuals, i.e., individuals in the target structural population. For example, select the top 5 design schemes with the highest fitness scores. Specifically, a first preset score threshold can be set to select target structural population individuals with higher scores. Crossover operations are then performed on the selected parent individuals to generate new offspring individuals.

[0109] For example, combining the composite sheet arrangement of scheme A with the drill bit body shape of scheme B creates a new scheme C. Randomly altering some genes in certain individuals introduces new variables. For example, randomly adjusting the number or position of support rings in the new scheme C. Continuing selection, crossover, and mutation operations until a predetermined stopping condition is met (such as a maximum number of iterations or a fitness change less than a threshold). For example, setting the maximum number of iterations to 100.

[0110] For example, three initial structural design schemes are created, each including different composite plate arrangements, drill bit body shapes, and support ring designs. For instance:

[0111] Option 1: Composite sheet with a side tilt angle of 15°, circular body, and no support ring.

[0112] Option 2: Composite sheet with a side tilt angle of 20°, elliptical body, with a support ring added to the front edge.

[0113] Option 3: Composite sheet with a side tilt angle of 25°, circular body, with a support ring added to the rear edge.

[0114] For each scheme, the stress response under high temperature and high pressure conditions is calculated using finite element analysis software, and the fitness score is calculated based on a preset fitness function. The following scores are assumed to be obtained:

[0115] Option 1: Fitness = 75; Option 2: Fitness = 85; Option 3: Fitness = 80.

[0116] The two schemes with the highest fitness scores are selected as parent individuals. The composite piece arrangement of Scheme 2 is combined with the drill body shape of Scheme 3 to form a new Scheme 4 (e.g., composite piece side tilt angle of 20°, circular body, with support rings added to the trailing edge). The position or number of support rings is randomly adjusted in the new Scheme 4 to form Scheme 5 (e.g., composite piece side tilt angle of 20°, circular body, with support rings added to both the front and rear edges). Selection, crossover, and mutation operations are continued. After multiple iterations, a structural design scheme with the highest first fitness score that satisfies all structural optimization objectives is finally found.

[0117] Through the detailed implementation methods and examples described above, the structural parameters of the drill bit can be systematically optimized, ensuring its high-efficiency performance under high-temperature and high-pressure environments. This not only improves the working efficiency of the drill bit but also extends its service life and reduces maintenance costs.

[0118] The method for determining drill bit parameters also includes:

[0119] The three-dimensional geometric model of the composite drill bit is optimized based on the optimal structural parameters of the composite drill bit to obtain an optimized three-dimensional geometric model, and an optimized dynamic stress distribution map is obtained based on the optimized three-dimensional geometric model.

[0120] Numerical simulation calculations were performed on the optimized dynamic stress distribution spectrum based on the pre-constructed finite element model of the composite drill bit to obtain the second stress response result;

[0121] In response to a parameter setting action triggered based on the second stress response result, the target value for optimizing the material parameters of the composite drill bit is determined;

[0122] The material parameters of the composite drill bit are optimized using the aforementioned material parameter optimization target value as the optimization objective to obtain the optimal material parameters of the composite drill bit.

[0123] The three-dimensional geometric model of the composite drill bit is reconstructed or modified based on the optimized structural parameters to obtain an optimized three-dimensional geometric model. The optimized dynamic stress distribution spectrum can be output through the optimized three-dimensional geometric model, which can accurately reflect the latest structural design changes.

[0124] The optimized dynamic stress distribution spectrum is simulated and calculated based on the pre-constructed finite element model of the composite drill bit. Finite element analysis is then performed to obtain the second stress response results of the composite drill bit under high temperature and high pressure conditions in deep well drilling. The second stress response results also include, but are not limited to, stress concentration areas, peak stress, stress distribution patterns, impact stress magnitude, rock breaking efficiency, and wear rate.

[0125] The parameters can be set manually based on the second stress response results, thereby obtaining the target value for material parameter optimization.

[0126] The material parameter optimization objectives include at least one of maximizing stability and maximizing wear resistance. The material parameters to be iteratively optimized include the alloying element addition ratio, diamond particle arrangement, and bonding method. The material parameter optimization objective value is the quantified value of the above-mentioned material parameter optimization objectives.

[0127] The purpose of analyzing the second stress response results is to identify shortcomings in the current material configuration. For example, certain areas may have insufficient wear resistance or overall stability, and specific material optimization objectives can be set accordingly, including maximizing stability and maximizing wear resistance.

[0128] Maximizing stability refers to improving the mechanical properties of the material under high temperature and high pressure environments, reducing the risk of deformation and failure. Maximizing wear resistance refers to enhancing the wear resistance of key components (such as PDC composite sheets) and extending service life. This material parameter optimization objective can be one or more; this embodiment does not limit this.

[0129] The material parameters are of various types, and each type of material parameter corresponds to multiple material parameter values; correspondingly, the optimization of the material parameters of the composite drill bit using the material parameter optimization target value as the optimization target to obtain the optimal material parameters of the composite drill bit includes:

[0130] By combining multiple material parameter values ​​of various types of material parameters, multiple material design schemes can be obtained;

[0131] Optimize each material design scheme according to the target value of the material parameters to obtain the optimal material parameters corresponding to the optimal material design scheme.

[0132] To find the optimal material design scheme, multiple material design schemes can be pre-constructed based on different alloy element addition ratios, diamond particle arrangement, and bonding methods. Then, a genetic algorithm is used to iteratively optimize the original material parameters based on these multiple material design schemes. The main material parameters considered during optimization include the alloy element addition ratios, diamond particle arrangement, and bonding methods. Each iteration updates these parameters and re-evaluates their corresponding performance indicators until the best combination that satisfies all material optimization objectives is found, i.e., the optimized material parameters.

[0133] The optimization of each material design scheme based on the target value of the material parameters includes:

[0134] The target value is optimized based on the material parameters, and each material design scheme is optimized using the crossover and mutation operation in a genetic algorithm. Specifically, this includes:

[0135] Multiple material design schemes were constructed based on different alloy element addition ratios, diamond particle arrangement and bonding methods to obtain an initial material population, with each material design scheme corresponding to an individual material population.

[0136] The target value is optimized based on the material parameters, and the second fitness score corresponding to each material design scheme is calculated using a preset fitness function. The second fitness score includes a stability score and a wear resistance score.

[0137] Based on the second fitness score, target material population individuals with a score higher than the second preset threshold are selected from the initial material population. The target material population individuals are then iteratively optimized through crossover and mutation until a material design scheme that meets the material parameter optimization target value is obtained. The material parameters corresponding to the material design scheme that meets the material parameter optimization target value are then determined as the optimized material parameters.

[0138] The proportions of alloying elements added include consideration of different combinations of alloying elements, such as the ratio of nickel (Ni) to chromium (Cr). A range of ratios can be set, such as Ni:Cr = 2:1, 3:1, and 4:1, etc.

[0139] Diamond particle arrangement includes different arrangement densities and patterns, such as high-density arrangement, low-density arrangement, or specific pattern arrangement (such as honeycomb arrangement).

[0140] The bonding method includes selecting different adhesives and their proportions, such as metal-based adhesives, ceramic-based adhesives, or other novel composite adhesives.

[0141] For example, suppose 20 different material designs are created as an initial population, each material design representing a possible combination.

[0142] Option a: The alloy element ratio is Ni:Cr=3:1, the diamond particles are arranged in a high density, and a metal-based binder is used.

[0143] Option b: The alloy element ratio is Ni:Cr=2:1, the diamond particles are arranged at a medium density, and a ceramic-based binder is used, and so on.

[0144] The fitness score between each material optimization scheme and the material optimization target value is calculated using a preset fitness function. This second fitness score includes a stability score and a wear resistance score.

[0145] Among them, the stability score is used to measure the mechanical properties of materials under high temperature and high pressure, and to reduce the risk of deformation and failure. It can be evaluated by the stress distribution uniformity and the maximum stress value in finite element analysis.

[0146] Abrasion resistance score is used to evaluate the abrasion resistance of critical components (such as PDC composite sheets) and extend their service life. It can predict the wear rate of materials under specific conditions using experimental data or simulations.

[0147] Specifically, corresponding weighting coefficients can be set for the stability score and the wear resistance score respectively. These weighting coefficients are used to indicate the importance attached to material optimization. Finally, the second fitness score of each material design scheme is obtained by weighting.

[0148] Based on a second fitness score, high-performing individuals are selected from the initial material population to serve as parent individuals, i.e., individuals in the target material population. For example, the top 5 design schemes with the highest fitness scores can be selected. Similarly, a second preset score threshold can be set to select target material population individuals with higher scores. The selected parent individuals are then crossoverdone to generate new offspring individuals.

[0149] For example, combining the alloy element ratio of scheme a with the diamond particle arrangement of scheme b creates a new scheme c (e.g., an alloy element ratio of Ni:Cr = 2.5:1, and a high-density diamond particle arrangement). Randomly altering some genes of certain individuals introduces new variables. For example, randomly adjusting the choice or ratio of the binder in new scheme c creates scheme d (e.g., an alloy element ratio of Ni:Cr = 2.5:1, a high-density diamond particle arrangement, and the use of a third binder). Selection, crossover, and mutation operations continue until a predetermined stopping condition is met (e.g., the maximum number of iterations or a fitness change less than a threshold). For example, a maximum of 50 iterations might be set.

[0150] For example, 20 initial material design schemes are created, each containing different alloy element ratios, diamond particle arrangements, and bonding methods. For instance:

[0151] Option 1: The alloy element ratio is Ni:Cr=3:1, the diamond particles are arranged in a high density, and a metal-based binder is used.

[0152] Option 2: The alloy element ratio is Ni:Cr=2:1, the diamond particles are arranged at a medium density, and a ceramic-based binder is used.

[0153] Option 3: The alloy element ratio is Ni:Cr=4:1, the diamond particles are arranged in a low density, and a new type of composite binder is used.

[0154] For each scheme, the stress response under high temperature and high pressure conditions is calculated using finite element analysis software, and the fitness score is calculated based on a preset fitness function. The following scores are assumed to be obtained:

[0155] Option 1: Fitness = 78 (Stability score: 40, Abrasion resistance score: 38); Option 2: Fitness = 82 (Stability score: 42, Abrasion resistance score: 40); Option 3: Fitness = 75 (Stability score: 39, Abrasion resistance score: 36).

[0156] The two schemes with the highest fitness scores are selected as parent individuals. The alloy element ratio of Scheme 1 is combined with the diamond particle arrangement of Scheme 2 to form a new Scheme 4 (e.g., alloy element ratio of Ni:Cr = 2.5:1, diamond particle arrangement of high density). The choice or ratio of binder is randomly adjusted in the new Scheme 4 to form Scheme 5 (e.g., alloy element ratio of Ni:Cr = 2.5:1, diamond particle arrangement of high density, using a third binder). Selection, crossover, and mutation operations are continued. After multiple iterations, a material design scheme with the second highest fitness score that satisfies all optimization objectives is finally found.

[0157] Examples of the crossover and mutation operations mentioned above are provided below:

[0158] For cross operations:

[0159] Assume there are two parent individuals:

[0160] Parent generation 1: The alloy element ratio is Ni:Cr=3:1, the diamond particles are arranged in a high density, and a metal-based binder is used.

[0161] Parent generation 2: The alloy element ratio is Ni:Cr=2:1, the diamond particles are arranged at a medium density, and a ceramic-based binder is used.

[0162] Two offspring individuals can be generated through a single-point crossover operation:

[0163] Fellow 1: The alloy element ratio is Ni:Cr=3:1, the diamond particles are arranged at a medium density, and a metal-based binder is used.

[0164] Fellow 2: The alloy element ratio is Ni:Cr=2:1, the diamond particles are arranged in a high density, and a ceramic-based binder is used.

[0165] For mutation operations:

[0166] Mutation operations can be performed on offspring 1, such as randomly changing the choice of adhesive.

[0167] The mutated individual has an alloy element ratio of Ni:Cr=3:1, diamond particles are arranged at a medium density, and a new type of composite binder is used.

[0168] Through the detailed implementation methods and examples described above, the material parameters of drill bits can be systematically optimized to ensure their high-efficiency performance under high-temperature and high-pressure environments. This not only improves the working efficiency of drill bits but also extends their service life and reduces maintenance costs.

[0169] Optimized structural and material parameters can be used together to optimize drill bit parameters. These parameters can also be verified to ensure they achieve the expected results under actual high-temperature and high-pressure conditions. After thorough verification, the optimized structural and material parameters are determined as the final design parameters for the target drill bit, and a prototype composite drill bit is manufactured based on these parameters for field testing.

[0170] The drill bit parameter determination method provided in this embodiment of the invention ensures that not only is the structural design optimized, but the material selection can also better adapt to the optimized structural features, further enhancing the stability and wear resistance of the drill bit, enabling it to maintain efficient operation under harsher working conditions.

[0171] This approach makes the design process more scientific and systematic, with detailed data supporting everything from initial stress analysis to final material selection, significantly improving the accuracy and reliability of drill bit design. Structural optimization solves problems inherent in traditional drill bits, such as stress concentration, low rock-breaking efficiency, and uneven wear, directly enhancing the safety and economy of deep well drilling operations. Material optimization focuses on improving the overall stability and wear resistance of the drill bit, extending its service life and reducing downtime and increased costs due to frequent replacements or maintenance. In short, this comprehensive approach, considering both structure and materials, not only improves deep well drilling efficiency but also reduces long-term operating costs, maximizing economic benefits. This has resulted in a more comprehensive and in-depth product development strategy, improving drill bit design and practical application from multiple perspectives, demonstrating significant practical value and broad applicability.

[0172] The drill bit parameter determination method provided in this invention generates a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece. The dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit. Based on the dynamic stress distribution map and a pre-constructed finite element model of the composite drill bit, the optimization target value of the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are optimized using the optimization target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit. The optimized drill bit parameters can improve drilling performance under high temperature and high pressure conditions in deep well drilling and extend the service life of the drill bit.

[0173] Further, the step of generating a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit includes:

[0174] Stress characteristics are identified for the triaxial stress data corresponding to each composite piece, and the dynamic stress distribution map is generated based on the three-dimensional stress model of the composite piece drill bit surface constructed according to the identified stress characteristics. This can be referred to the above embodiment for explanation, and will not be repeated here.

[0175] Further, determining the target values ​​for optimizing the structural parameters of the composite drill bit based on the dynamic stress distribution spectrum and the pre-constructed finite element model of the composite drill bit includes:

[0176] The dynamic stress distribution spectrum is numerically simulated based on the pre-constructed finite element model of the composite drill bit to obtain the first stress response result; the above embodiments can be referred to for explanation, and will not be repeated here.

[0177] In response to the parameter setting action triggered based on the first stress response result, the target value for optimizing the structural parameters of the composite drill bit is determined. This can be referred to the above embodiments for further explanation, and will not be repeated here.

[0178] Furthermore, the structural parameters are of multiple types, and each type of structural parameter corresponds to multiple structural parameter values; correspondingly, the optimization of the structural parameters of the composite drill bit using the structural parameter optimization target value as the optimization target to obtain the optimal structural parameters of the composite drill bit includes:

[0179] Multiple structural parameter values ​​of various types of structural parameters are combined to obtain multiple structural design schemes; the above embodiments can be referred to for explanation, and will not be repeated here.

[0180] Each structural design scheme is optimized based on the target value of the structural parameters to obtain the optimal structural parameters corresponding to the optimal structural design scheme. This can be referred to the above embodiments for further explanation, and will not be repeated here.

[0181] Furthermore, optimizing each structural design scheme based on the target value of the structural parameters includes:

[0182] The target value is optimized based on the structural parameters, and each structural design scheme is optimized using the crossover and mutation operation in the genetic algorithm. This can be referred to the above embodiments for further explanation, and will not be repeated here.

[0183] Further, the step of optimizing the target value based on the structural parameters and optimizing each structural design scheme using the crossover and mutation operation in the genetic algorithm includes:

[0184] Based on different composite sheet arrangements, drill bit body shapes, and support ring designs, multiple structural design schemes are constructed to obtain an initial structural population. Each structural design scheme corresponds to one individual in the structural population. The above embodiments can be referred to for explanation, and will not be repeated here.

[0185] Based on the target value of the structural parameters, the first fitness score corresponding to each design structural scheme is calculated using a preset fitness function. The first fitness score includes the stress uniformity distribution score, the stress peak reduction score, the rock breaking efficiency maximization score, and the wear rate minimization score. The above embodiments can be referred to for explanation, and will not be repeated here.

[0186] Based on the first fitness score, target structural individuals with scores higher than a first preset threshold are selected from the initial structural population. These individuals are then iteratively optimized through crossover and mutation until a structural design scheme that satisfies the target value for structural parameter optimization is obtained. The structural parameters corresponding to the structural design scheme that satisfies the target value for structural parameter optimization are then determined as the optimized structural parameters. This can be referred to the above embodiments for further explanation and will not be repeated here.

[0187] Furthermore, the method for determining drill bit parameters also includes:

[0188] The three-dimensional geometric model of the composite drill bit is optimized based on the optimal structural parameters of the composite drill bit to obtain an optimized three-dimensional geometric model, and an optimized dynamic stress distribution spectrum is obtained based on the optimized three-dimensional geometric model; the above embodiments can be referred to for explanation, and will not be repeated here.

[0189] The optimized dynamic stress distribution spectrum is numerically simulated based on the pre-constructed finite element model of the composite drill bit to obtain the second stress response result; the above embodiments can be referred to for explanation, and will not be repeated here.

[0190] In response to the parameter setting action triggered based on the second stress response result, the target value for optimizing the material parameters of the composite drill bit is determined; this can be described with reference to the above embodiments and will not be repeated here.

[0191] The material parameters of the composite drill bit are optimized using the aforementioned material parameter optimization target value as the optimization objective to obtain the optimal material parameters of the composite drill bit. This can be referred to the above embodiments for explanation, and will not be repeated here.

[0192] Furthermore, the material parameters are of multiple types, and each type of material parameter corresponds to multiple material parameter values; correspondingly, the optimization of the material parameters of the composite drill bit using the material parameter optimization target value as the optimization target to obtain the optimal material parameters of the composite drill bit includes:

[0193] Multiple material parameter values ​​of various types of material parameters are combined to obtain multiple material design schemes; the above embodiments can be referred to for explanation, and will not be repeated here.

[0194] Each material design scheme is optimized based on the target value of the material parameters to obtain the optimal material parameters corresponding to the optimal material design scheme. This can be referred to the above embodiments for explanation, and will not be repeated here.

[0195] Furthermore, optimizing each material design scheme based on the target value of the material parameters includes:

[0196] The target value is optimized based on the material parameters, and each material design scheme is optimized using the crossover and mutation operation in a genetic algorithm. This can be referred to the above embodiments for further explanation, and will not be repeated here.

[0197] Further, the step of optimizing the target value based on the material parameters and optimizing each material design scheme using the crossover and mutation operation in the genetic algorithm includes:

[0198] Multiple material design schemes were constructed based on different alloy element addition ratios, diamond particle arrangement, and bonding methods to obtain an initial material population. Each material design scheme corresponds to an individual material population. The above embodiments can be referred to for explanation, and will not be repeated here.

[0199] The target value is optimized based on the material parameters, and the second fitness score corresponding to each material design scheme is calculated using a preset fitness function. The second fitness score includes a stability score and a wear resistance score. This can be referred to the above embodiments for explanation, and will not be repeated here.

[0200] Based on the second fitness score, target material individuals with scores higher than the second preset threshold are selected from the initial material population. These individuals are then iteratively optimized through crossover and mutation until a material design scheme that satisfies the material parameter optimization target value is obtained. The material parameters corresponding to the material design scheme that satisfies the material parameter optimization target value are then determined as the optimized material parameters. This can be referred to the above embodiments for further explanation and will not be repeated here.

[0201] Figure 2 This is a schematic diagram of the drill bit parameter determination device provided in an embodiment of the present invention, as shown below. Figure 2 As shown, the drill bit parameter determination device provided in this embodiment of the invention includes a generation unit 201 and a determination unit 202, wherein:

[0202] The generation unit 201 is used to generate a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit; the determination unit 202 is used to determine the structural parameter optimization target value of the composite drill bit based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, and optimize the structural parameters of the composite drill bit using the structural parameter optimization target value as the optimization target to obtain the optimal structural parameters of the composite drill bit.

[0203] Specifically, the generation unit 201 in the device is used to generate a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit; the determination unit 202 is used to determine the structural parameter optimization target value of the composite drill bit based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, and optimize the structural parameters of the composite drill bit using the structural parameter optimization target value as the optimization target to obtain the optimal structural parameters of the composite drill bit.

[0204] The drill bit parameter determination device provided in this embodiment of the invention generates a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece. The dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit. Based on the dynamic stress distribution map and a pre-constructed finite element model of the composite drill bit, the device determines the structural parameter optimization target value of the composite drill bit. Using the structural parameter optimization target value as the optimization objective, the device optimizes the structural parameters of the composite drill bit to obtain the optimal structural parameters of the composite drill bit. The optimized drill bit parameters can improve drilling performance under high temperature and high pressure conditions in deep well drilling and extend the service life of the drill bit.

[0205] The embodiments of the present invention provide a drill bit parameter determination device that can be used to execute the processing flow of the above-described method embodiments. Its functions will not be repeated here, but can be referred to the detailed description of the above-described method embodiments.

[0206] Figure 3 This is a schematic diagram of the physical structure of a computer device provided in an embodiment of the present invention, such as... Figure 3 As shown, the computer device includes: a memory 301, a processor 302, and a computer program stored in the memory 301 and executable on the processor 302. When the processor 302 executes the computer program, it implements the following method:

[0207] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0208] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0209] This embodiment discloses a computer program product, which includes a computer program that, when executed by a processor, implements the following method:

[0210] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0211] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0212] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the following method:

[0213] A dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece; the dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit.

[0214] Based on the dynamic stress distribution map and the pre-constructed finite element model of the composite drill bit, the target value for optimizing the structural parameters of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit.

[0215] Compared with existing technologies, the drill bit parameter determination method provided in this invention generates a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece. This dynamic stress distribution map characterizes the dynamic stress distribution and variation characteristics covering the surface of the composite drill bit. Based on the dynamic stress distribution map and a pre-constructed finite element model of the composite drill bit, the optimization target value of the structural parameters of the composite drill bit is determined. Using this optimization target value as the optimization objective, the structural parameters of the composite drill bit are optimized to obtain the optimal structural parameters. The optimized drill bit parameters improve drilling performance under high temperature and high pressure conditions in deep well drilling and extend the service life of the drill bit.

[0216] 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.

[0217] 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.

[0218] 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.

[0219] 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.

[0220] In the description of this specification, the references to terms such as "an embodiment," "a specific embodiment," "some embodiments," "for example," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0221] 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 drill bit parameters, characterized in that, include: The dynamic stress distribution map of the composite drill bit is generated based on the triaxial stress data corresponding to each composite piece in the composite drill bit. The dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics on the surface of the composite drill bit. Based on the dynamic stress distribution spectrum and the pre-constructed finite element model of the composite drill bit, the target value for structural parameter optimization of the composite drill bit is determined. The structural parameters of the composite drill bit are then optimized using the target value as the optimization objective to obtain the optimal structural parameters of the composite drill bit. The structural parameters are of various types, and each type of structural parameter corresponds to multiple structural parameter values; correspondingly, the optimization of the structural parameters of the composite drill bit using the optimization target value of the structural parameters as the optimization target to obtain the optimal structural parameters of the composite drill bit includes: Multiple structural parameter values ​​of various types of structural parameters are combined to obtain multiple structural design schemes; Each structural design scheme is optimized based on the structural parameter optimization target value to obtain the optimal structural parameters corresponding to the optimal structural design scheme. The optimization of each structural design scheme based on the target value of the structural parameters includes: The target value is optimized based on the structural parameters, and each structural design scheme is optimized using the crossover and mutation operation in the genetic algorithm. The step of optimizing the target value based on the structural parameters and optimizing each structural design scheme using the crossover and mutation operation in the genetic algorithm includes: Based on different composite sheet arrangements, drill bit body shapes, and support ring designs, multiple structural design schemes were constructed to obtain an initial structural population, with each structural design scheme corresponding to a structural population individual. Based on the target value of the structural parameters, the first fitness score corresponding to each design structural scheme is calculated using a preset fitness function. The first fitness score includes the stress uniform distribution score, the stress peak reduction score, the rock breaking efficiency maximization score, and the wear rate minimization score. Based on the first fitness score, target structural individuals with a score higher than the first preset threshold are selected from the initial structural population. The target structural individuals are then iteratively optimized through crossover and mutation until a structural design scheme that satisfies the structural parameter optimization target value is obtained. The structural parameters corresponding to the structural design scheme that satisfies the structural parameter optimization target value are determined as the optimized structural parameters.

2. The method for determining drill bit parameters according to claim 1, characterized in that, The step of generating a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece of the composite drill bit includes: Stress characteristics are identified for the triaxial stress data corresponding to each composite piece, and the dynamic stress distribution map is generated based on the three-dimensional stress model of the composite piece drill bit surface constructed according to the identified stress characteristics.

3. The method for determining drill bit parameters according to claim 1, characterized in that, The step of determining the structural parameter optimization target value of the composite drill bit based on the dynamic stress distribution spectrum and the pre-constructed finite element model of the composite drill bit includes: Numerical simulation calculations were performed on the dynamic stress distribution spectrum based on the pre-constructed finite element model of the composite drill bit to obtain the first stress response result; In response to the parameter setting action triggered based on the first stress response result, the target value for optimizing the structural parameters of the composite drill bit is determined.

4. The method for determining drill bit parameters according to claim 2, characterized in that, The method for determining drill bit parameters also includes: The three-dimensional geometric model of the composite drill bit is optimized based on the optimal structural parameters of the composite drill bit to obtain an optimized three-dimensional geometric model, and an optimized dynamic stress distribution map is obtained based on the optimized three-dimensional geometric model. Numerical simulation calculations were performed on the optimized dynamic stress distribution spectrum based on the pre-constructed finite element model of the composite drill bit to obtain the second stress response result; In response to a parameter setting action triggered based on the second stress response result, the target value for optimizing the material parameters of the composite drill bit is determined; The material parameters of the composite drill bit are optimized using the material parameter optimization target value as the optimization target to obtain the optimal material parameters of the composite drill bit.

5. The method for determining drill bit parameters according to claim 4, characterized in that, The material parameters are of various types, and each type of material parameter corresponds to multiple material parameter values; correspondingly, the optimization of the material parameters of the composite drill bit using the material parameter optimization target value as the optimization target to obtain the optimal material parameters of the composite drill bit includes: By combining multiple material parameter values ​​of various types of material parameters, multiple material design schemes can be obtained; Optimize each material design scheme according to the target value of the material parameters to obtain the optimal material parameters corresponding to the optimal material design scheme.

6. The method for determining drill bit parameters according to claim 5, characterized in that, The optimization of each material design scheme based on the target value of the material parameters includes: The target value is optimized based on the material parameters, and each material design scheme is optimized using the crossover and mutation operation in the genetic algorithm.

7. The method for determining drill bit parameters according to claim 6, characterized in that, The step of optimizing the target value based on the material parameters and optimizing each material design scheme using the crossover and mutation operation in the genetic algorithm includes: Multiple material design schemes were constructed based on different alloy element addition ratios, diamond particle arrangement and bonding methods to obtain an initial material population, with each material design scheme corresponding to an individual material population. The target value is optimized based on the material parameters, and the second fitness score corresponding to each material design scheme is calculated using a preset fitness function. The second fitness score includes a stability score and a wear resistance score. Based on the second fitness score, target material population individuals with a score higher than the second preset threshold are selected from the initial material population. The target material population individuals are then iteratively optimized through crossover and mutation until a material design scheme that meets the material parameter optimization target value is obtained. The material parameters corresponding to the material design scheme that meets the material parameter optimization target value are then determined as the optimized material parameters.

8. A drill bit parameter determining device, characterized in that, include: The generation unit is used to generate a dynamic stress distribution map of the composite drill bit based on the triaxial stress data corresponding to each composite piece in the composite drill bit. The dynamic stress distribution map is used to characterize the dynamic stress distribution and variation characteristics on the surface of the composite drill bit. The determining unit is used to determine the structural parameter optimization target value of the composite drill bit based on the dynamic stress distribution spectrum and the pre-constructed finite element model of the composite drill bit, and to optimize the structural parameters of the composite drill bit using the structural parameter optimization target value as the optimization target to obtain the optimal structural parameters of the composite drill bit. The structural parameters are of various types, and each type of structural parameter corresponds to multiple structural parameter values; correspondingly, the determining unit is specifically used for: Multiple structural parameter values ​​of various types of structural parameters are combined to obtain multiple structural design schemes; Each structural design scheme is optimized based on the structural parameter optimization target value to obtain the optimal structural parameters corresponding to the optimal structural design scheme. The optimization of each structural design scheme based on the target value of the structural parameters includes: The target value is optimized based on the structural parameters, and each structural design scheme is optimized using the crossover and mutation operation in the genetic algorithm. The step of optimizing the target value based on the structural parameters and optimizing each structural design scheme using the crossover and mutation operation in the genetic algorithm includes: Based on different composite sheet arrangements, drill bit body shapes, and support ring designs, multiple structural design schemes were constructed to obtain an initial structural population, with each structural design scheme corresponding to a structural population individual. Based on the target value of the structural parameters, the first fitness score corresponding to each design structural scheme is calculated using a preset fitness function. The first fitness score includes the stress uniform distribution score, the stress peak reduction score, the rock breaking efficiency maximization score, and the wear rate minimization score. Based on the first fitness score, target structural individuals with a score higher than the first preset threshold are selected from the initial structural population. The target structural individuals are then iteratively optimized through crossover and mutation until a structural design scheme that satisfies the structural parameter optimization target value is obtained. The structural parameters corresponding to the structural design scheme that satisfies the structural parameter optimization target value are determined as the optimized structural parameters.

9. 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 of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 7.

11. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method of any one of claims 1 to 7.

Images