A method and system for predicting the service life of a PDC bit

Abstract

The application relates to the technical field of PDC drill bits, and discloses a PDC drill bit service life prediction analysis method and system, which comprises the following steps: firstly, acquiring mechanical parameters, vibration impact, torque and energy consumption, drill bit posture change and well bottom reaction force fluctuation and other multi-source drilling response data, and aligning according to the collection time; constructing a cutting trajectory dynamic reconstruction model based on the aligned data, obtaining trajectory deviation, load fluctuation rate and thermal-mechanical coupling characteristics of each PDC tooth, and generating a tooth position interaction feature matrix; performing time series analysis on the matrix, identifying micro-crack initiation, wear mutation and load jump events, establishing a key tooth position degradation path, forming a service life characteristic group, dividing wear stages according to the characteristic group change, and obtaining a drill bit service life prediction value according to the stage conversion mutation point. The application can obtain a service life prediction result with higher precision and better working condition adaptability.

Description

Technical Field

[0001] This invention relates to the field of PDC drill bit technology, and more specifically, to a method and system for predicting and analyzing the service life of PDC drill bits. Background Technology

[0002] PDC drill bits are a widely used type of fixed-tool drill bit in oil and gas drilling, geothermal wells, and engineering exploration. They offer high cutting efficiency, good guidance, and a wide range of formation adaptability. However, in hard and brittle formations, complex formations, and highly deviated well sections, localized excessive load on PDC teeth and accelerated thermomechanical fatigue can easily occur. Once critical tooth positions experience abnormal wear, fracture, or failure, it often leads to a decrease in overall mechanical drilling rate, amplified vibration and impact, and even stuck pipe accidents. Therefore, accurate prediction of PDC drill bit service life is of great engineering significance for optimizing drilling parameters and rationally scheduling tripping and tripping times.

[0003] In existing technologies, the assessment and prediction of PDC drill bit life mainly adopts the following approaches: One approach is to construct empirical formulas or drill bit efficiency evaluation indicators based on macroscopic mechanical parameters such as drilling pressure, rotational speed, torque, and pump pressure, and indirectly infer the wear degree and remaining life of the drill bit through the changing trends of these indicators. For example, the effective mechanical specific energy model proposed by Mazen et al. is used to evaluate the cutting efficiency and wear state of PDC drill bits by calculating the mechanical specific energy in real time and comparing it with the working conditions of a new drill bit. Another approach is to conduct finite element simulations or bench tests under laboratory conditions to analyze the stress and temperature rise of PDC teeth under typical working conditions, and then calculate the allowable working time range through a safety factor. For example, some studies have pointed out that numerical analysis has been conducted on the life and failure modes of PDC teeth under thermo-mechanical combined action to evaluate the impact of thermal load and mechanical load on the life of PDC tools; other works have established analytical or numerical models of the temperature field of PDC drill bits to evaluate the impact of different structural parameters and working conditions on thermal fatigue life.

[0004] The above methods have been applied to some extent in engineering fields, but they generally suffer from the following technical problems: First, most methods treat the PDC drill bit as a whole, judging its life status only from the changes in a single signal (such as torque, mechanical specific energy, etc.) at the wellhead or downhole. They lack a detailed description of the stress state, thermomechanical coupling response, and inter-tooth load transfer relationship of individual PDC teeth, and cannot identify the local degradation process of key tooth positions. Second, existing methods are mostly based on statistical regression or empirical fitting of single-source or small-scale signals, failing to fully utilize the inherent correlation between multi-source drilling response data such as vibration and shock, attitude changes, and bottom hole reaction force fluctuations. They are difficult to reflect the dynamic changes in the stress distribution and cutting trajectory of the drill bit under complex working conditions in a timely manner. Third, life determination often uses simple thresholds or linear trend judgments, which can only give a rough estimate of the overall life. They lack detailed analysis of the stable wear stage, accelerated decay stage, and failure critical stage, and lack clear identification paths for key events such as microcrack initiation, sudden wear changes, and load jumps. Summary of the Invention

[0005] The purpose of this invention is to provide a method and system for predicting and analyzing the service life of PDC drill bits, so as to solve the above-mentioned problems.

[0006] To achieve the above objectives, the present invention provides the following solution:

[0007] A method for predicting and analyzing the service life of PDC drill bits, comprising:

[0008] S1: Acquire multi-source drilling response data during the drilling process. The multi-source drilling response data includes mechanical parameter sequences, vibration and impact sequences, torque and energy consumption sequences, drill bit attitude change sequences, and bottom hole reaction force fluctuation sequences; perform time alignment on all multi-source drilling response data based on the acquisition time;

[0009] S2: Construct a dynamic reconstruction model of the cutting trajectory based on time-aligned multi-source drilling response data, obtain the trajectory offset, load fluctuation rate and thermomechanical stress coupling characteristics of each PDC tooth, and construct a tooth position interaction feature matrix that includes the interaction relationship between all PDC teeth.

[0010] S3: Perform time-series analysis on the tooth position interaction feature matrix to identify the microcrack evolution indicators, wear stage abrupt change points, and load jump points of each PDC tooth during continuous drilling. Construct the key tooth position degradation path according to the microcrack initiation sequence, wear propagation sequence, and load jump sequence.

[0011] S4: Based on the changing trend of the key tooth position degradation path, extract the mean value of energy input density fluctuation, the discrete amount of impact frequency time interval and the continuous offset length of cutting trajectory to form a life characterization feature group.

[0012] S5: Based on the life characterization feature group, the drill bit life is divided into the stable wear stage, the accelerated decay stage and the failure critical stage, and the sudden change point of the characterization feature at the time of life stage transition is used as the basis for life prediction to obtain the predicted value of drill bit life.

[0013] Furthermore, the time alignment in step S1 includes:

[0014] The load rise nodes are extracted from the mechanical parameter sequence, the energy peak nodes are extracted from the vibration and shock sequence, the steady-state section nodes are extracted from the torque and energy consumption sequence, the attitude turning point nodes are extracted from the drill bit attitude change sequence, and the reaction force extreme value nodes are extracted from the bottom hole reaction force fluctuation sequence, resulting in a node set of five types of nodes.

[0015] The node-dense sections on the time axis are computed, and the sections where multiple types of nodes are simultaneously clustered are selected as the baseline sections.

[0016] All multi-source drilling response data are initially aligned using local linear interpolation, and node calibration and alignment are performed based on the time position of nodes in the reference section to obtain synchronous sampling frames containing effective load segments, analyzable attitude segments, and stable reaction force segments.

[0017] Furthermore, the dynamic reconstruction model of the cutting trajectory in step S2 includes:

[0018] An attitude rotation matrix is ​​established based on the drill bit attitude change sequence, and the mechanical parameter sequence and torque and energy consumption sequence are transformed into the equivalent force vector on each tooth position.

[0019] Within each sampling period, the equivalent force vector is rotated according to the attitude rotation matrix to obtain the instantaneous force field of each tooth position;

[0020] The main cutting section, transition section and weak cutting section are divided according to the instantaneous force field change characteristics. The force difference between each section after division is calculated to determine the force imbalance.

[0021] The load volatility is constructed by the change in the amount of force imbalance within adjacent sampling periods;

[0022] Thermomechanical response parameters are calculated based on the instantaneous temperature rise increment and load fluctuation rate caused by the change in force, and used to form the dynamic reconstruction result of the cutting trajectory.

[0023] Furthermore, the tooth position interaction feature matrix in step S2 includes:

[0024] For each tooth position, establish the load propagation path pointing to the forward tooth, the backward tooth, and the radially symmetrical tooth, and calculate the propagation amplitude ratio, propagation phase offset, and propagation time difference in the propagation path;

[0025] When both the propagation amplitude ratio and the propagation phase offset exceed the corresponding growth threshold, the corresponding path is marked as a coupling path.

[0026] A three-dimensional matrix is ​​generated based on the tooth position index, propagation direction index, and coupling level. A residual layer is added to the three-dimensional matrix to record the difference between the actual propagation time and the theoretical inter-tooth propagation time. The three-dimensional matrix is ​​a tooth position interaction feature matrix.

[0027] Furthermore, the time series analysis in step S3 includes:

[0028] The tooth position interaction feature matrix is ​​expanded into four-dimensional time series data within a continuous rotation cycle, and the coupling strength change rate, phase cumulative offset and propagation delay change are calculated.

[0029] When the rate of change of coupling strength continues to increase and the cumulative phase offset shows nonlinear growth between adjacent cycles, the corresponding tooth position is recorded as the microcrack initiation tooth position.

[0030] When the change in propagation delay jumps and the trajectory offset direction reverses within the synchronous sampling window, the corresponding tooth position is recorded as the tooth position with wear mutation.

[0031] Establish tooth degeneration paths in all tooth positions according to the order of eruption, expansion, and mutation.

[0032] Furthermore, the lifetime characterization feature set in step S4 includes:

[0033] The tooth position degradation path is divided into linear degradation segment, weakly abrupt degradation segment, and strongly abrupt degradation segment according to the degradation rate;

[0034] In the linear degradation zone, the mean fluctuation of energy input density is calculated; in the weak abrupt change zone, the time interval discreteness of impact frequency is calculated; and in the strong abrupt change zone, the continuous offset length of cutting trajectory deviation is calculated.

[0035] The mean fluctuation, the discrete amount of time interval, and the continuous offset length are normalized, and a lifetime characterization feature group is formed based on the normalization results.

[0036] Furthermore, the lifespan stage division in step S5 includes:

[0037] The stage drift is calculated based on the numerical changes of the life characterization feature group in three consecutive drilling cycles.

[0038] When the stage drift is in the low range and the average fluctuation of energy input density remains stable, the current stage is classified as the stable wear stage.

[0039] When the stage drift enters the middle range and the discreteness of the impact frequency time interval changes from a single peak to multiple peaks, the current stage is classified as the accelerated decay stage.

[0040] When the stage drift amount enters the high range and the continuous offset length of the trajectory deviation is non-periodic, the current stage is classified as the critical failure stage.

[0041] Furthermore, the stage transition feature identification in step S5 includes:

[0042] The nodes of trend slope reversal, trajectory offset direction change, and propagation delay change in the lifetime characterization feature group are recorded as three types of event sequences.

[0043] When two of the three types of events occur within the same sampling window, the current window is recorded as the stage transition event window.

[0044] When the stage transition event window appears consecutively in two adjacent sampling windows and the increase in the offset angle of the trajectory offset direction is greater than the increase in the previous window, the current window is determined as the stage transition judgment window.

[0045] Furthermore, the calculation of the drill bit life prediction includes:

[0046] The stage compression amount is calculated based on the position and number of stage transition judgment windows, and lifetime back-calculation is established based on the change sequence of stage compression amount in the accelerated decay stage.

[0047] By using the cumulative offset of the degradation path and the change in stage compression as inputs, the remaining life prediction of the drill bit is obtained.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] This invention synchronizes and aligns multi-source drilling response data, including mechanical parameters, vibration and impact, torque energy consumption, drill bit attitude, and bottom hole reaction force, allowing different physical quantities to be analyzed together within the same sampling framework. This results in drilling process characteristics with a consistent time reference. The dynamic reconstruction model of the cutting trajectory, built based on the time-aligned data, can characterize the instantaneous force field, load fluctuation rate, and thermomechanical coupling response at the tooth position scale, thereby obtaining reconstructed information reflecting the actual force and trajectory deviation of each PDC tooth. By establishing a tooth position interaction feature matrix containing forward, backward, and radial symmetrical propagation paths and performing temporal unfolding within a continuous rotation cycle, typical degradation events such as microcrack initiation, abrupt wear changes, and load jumps can be identified, forming key tooth position degradation paths with clear sequential relationships. Based on the trend changes of the degradation paths, life characteristic feature groups such as the mean of energy input density fluctuation, the discreteness of impact frequency time intervals, and the continuous trajectory offset length are extracted. This allows the drill bit life to be divided into three stages: stable wear, accelerated decay, and critical failure. Clear stage transition criteria can be obtained when the trend slope reverses or the offset direction changes at the stage boundaries. This application constructs a lifetime regression logic by determining the number and location of stage transition decision windows, and then combines this with the cumulative offset of the degradation path to achieve a quantitative prediction of the remaining lifetime. This application possesses refined characterization capabilities at the tooth position, time, and event scales, enabling high-resolution analysis of the PDC drill bit's lifetime status and improving the accuracy, stability, and adaptability of lifetime prediction results.

[0050] Furthermore, the present invention also provides a PDC drill bit lifespan prediction and analysis system for implementing the above-mentioned PDC drill bit lifespan prediction and analysis method. The system includes:

[0051] The data alignment module is configured to acquire multi-source drilling response data during the drilling process, including mechanical parameter sequences, vibration and impact sequences, torque and energy consumption sequences, drill bit attitude change sequences, and bottom hole reaction force fluctuation sequences; and to perform time alignment on all multi-source drilling response data based on the acquisition time.

[0052] The interaction feature module is configured to construct a dynamic reconstruction model of the cutting trajectory based on time-aligned multi-source drilling response data, obtain the trajectory offset, load fluctuation rate and thermomechanical stress coupling characteristics of each PDC tooth, and construct a tooth position interaction feature matrix that includes the interaction relationship between all PDC teeth.

[0053] The degradation analysis module is configured to perform time-series analysis on the tooth position interaction feature matrix, identify the microcrack evolution indicators, wear stage abrupt change points and load jump points of each PDC tooth during continuous drilling, and construct the key tooth position degradation path according to the microcrack initiation sequence, wear propagation sequence and load jump sequence.

[0054] The feature extraction module is configured to extract the mean value of energy input density fluctuation, the discrete amount of impact frequency time interval, and the continuous offset length of cutting trajectory based on the changing trend of the key tooth position degradation path, forming a life characterization feature set.

[0055] The life prediction module is configured to divide the drill bit life into a stable wear stage, an accelerated decay stage, and a critical failure stage based on the life characterization feature group, and use the abrupt change point of the characterization feature at the time of life stage transition as the basis for life prediction to obtain the predicted value of drill bit life.

[0056] It should be noted that the PDC drill bit lifespan prediction and analysis system and its method provided by this invention have the same beneficial effects, which will not be elaborated here. Attached Figure Description

[0057] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments 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.

[0058] Figure 1 A flowchart of a PDC drill bit lifespan prediction and analysis method provided in an embodiment of the present invention;

[0059] Figure 2 A framework diagram of a PDC drill bit lifespan prediction and analysis system provided in an embodiment of the present invention;

[0060] Figure 3 This is a schematic diagram of the structure of a polycrystalline diamond composite sheet provided in an embodiment of the present invention;

[0061] Figure 4 This is a planar schematic diagram of a composite biomimetic geometric structure provided in an embodiment of the present invention.

[0062] In the diagram, 1 is the polycrystalline diamond layer; 2 is the cemented carbide matrix; 3 is the tenon; 4 is the sea eye; 5 is the convex-shaped geometric structure; and 6 is the prismatic geometric structure. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0065] As mentioned in the background section, traditional PDC (partially controlled die) bit life prediction technologies rely solely on single signals from the wellhead or downhole for overall condition assessment. This results in an inability to accurately characterize the stress distribution, thermomechanical coupling response, and inter-tooth load transfer relationships of individual PDC teeth. Furthermore, the inherent correlation between mechanical parameter sequences and vibration / impact sequences is not effectively explored, making it difficult to identify local degradation processes such as microcrack initiation, abrupt wear changes, and load jumps at key tooth positions. Moreover, life determination relies on simple thresholds or linear trend judgments, lacking analysis of the transition mechanism from the stable wear stage to the accelerated decay stage. This leads to discrepancies between the predicted remaining life of the drill bit and the actual degradation state, thus affecting the accuracy of drilling parameter optimization and tripping / running timing decisions. For example, during drilling into complex formations in highly deviated well sections, the drill bit attitude change sequence shows continuous deflection, while the bottom hole reaction force fluctuation sequence exhibits non-periodic oscillations. However, existing technologies can only infer the degree of drill bit wear through overall torque changes. Specifically, when a specific PDC tooth fractures locally due to thermomechanical fatigue, a high-frequency pulse signal appears in the vibration and impact sequence. However, this signal cannot be correlated with the trajectory offset or load fluctuation rate of the specific tooth position. In particular, the lack of tooth position interaction characteristics makes it impossible to identify the load redistribution phenomenon of adjacent teeth caused by the failure of this tooth position. This causes the microcrack propagation path to be masked by the overall mechanical energy index, ultimately causing the drill bit to suddenly fail during the accelerated decay stage.

[0066] If the above problems are not addressed, the overall vibration and impact may be amplified during drilling in complex formations due to the failure to monitor the degradation of key tooth positions in a timely manner, resulting in an unexpected decrease in mechanical drilling speed. Furthermore, the characteristic abrupt change points of the failure critical stage cannot be captured, which significantly increases the risk of stuck pipe accidents, disrupts the continuity of drilling operations, and the drill bit life prediction results will be unable to support the safe and efficient implementation of drilling projects.

[0067] For this, please refer to Figure 1 As shown, this embodiment of the invention provides a method for predicting and analyzing the service life of a PDC drill bit, including:

[0068] S1: Acquire multi-source drilling response data during the drilling process. The multi-source drilling response data includes mechanical parameter sequences, vibration and impact sequences, torque and energy consumption sequences, drill bit attitude change sequences, and bottom hole reaction force fluctuation sequences; perform time alignment on all multi-source drilling response data based on the acquisition time;

[0069] S2: Construct a dynamic reconstruction model of the cutting trajectory based on time-aligned multi-source drilling response data, obtain the trajectory offset, load fluctuation rate and thermomechanical stress coupling characteristics of each PDC tooth, and construct a tooth position interaction feature matrix that includes the interaction relationship between all PDC teeth.

[0070] S3: Perform time-series analysis on the tooth position interaction feature matrix to identify the microcrack evolution indicators, wear stage abrupt change points, and load jump points of each PDC tooth during continuous drilling. Construct the key tooth position degradation path according to the microcrack initiation sequence, wear propagation sequence, and load jump sequence.

[0071] S4: Based on the changing trend of the key tooth position degradation path, extract the mean value of energy input density fluctuation, the discrete amount of impact frequency time interval and the continuous offset length of cutting trajectory to form a life characterization feature group.

[0072] S5: Based on the life characterization feature group, the drill bit life is divided into the stable wear stage, the accelerated decay stage and the failure critical stage, and the sudden change point of the characterization feature at the time of life stage transition is used as the basis for life prediction to obtain the predicted value of drill bit life.

[0073] Specifically, step S1: During the drilling process, multi-source drilling response data related to the drill bit's stress, movement, and bottom hole response are collected. In this embodiment, the mechanical parameter sequence includes sequences characterizing the mechanical operating state, such as drilling pressure, rotational speed, standpipe pressure, and mechanical drilling speed.

[0074] Vibration and impact sequences include axial impact, radial impact, and torsional vibration amplitude sequences, used to reflect the vibration conditions of the drill bit.

[0075] The torque and energy consumption sequence includes real-time torque, torque fluctuation, and energy consumption per unit time.

[0076] The drill bit attitude change sequence is provided by the inclinometer and inertial navigation module, including attitude angle changes, rotational angular velocity and attitude inflection points;

[0077] The bottom hole reaction force fluctuation sequence is obtained by bottom hole dynamics inversion or downhole tool measurement, and represents the periodic or non-periodic changes in the bottom hole contact force.

[0078] All the aforementioned multi-source data were processed using the acquisition time as a reference, mapping signals with different sampling frequencies onto a unified time axis through unified timestamp processing. Subsequently, a local linear interpolation method was used for initial data alignment, and node calibration was performed based on the reference segments formed by load rise nodes, energy peak nodes, attitude transition nodes, steady-state segment nodes, and reaction force extreme value nodes. This processing yields synchronously sampled data frames containing effective force segments, resolvable attitude segments, and stable reaction force segments, providing a consistent time reference for subsequent tooth position scale analysis.

[0079] Step S2: Based on the synchronous sampling frames obtained in Step S1, a dynamic reconstruction model of the cutting trajectory is constructed. This model is based on the drill bit attitude change sequence, and the mechanical parameter sequence and torque and energy consumption sequence are converted into the equivalent force vector of each tooth position through the attitude rotation matrix. In each sampling period, the instantaneous force field of each PDC tooth is calculated according to the rotated force vector.

[0080] By analyzing the changes in the instantaneous force field over time, the force field is divided into a main cutting zone, a transition zone, and a weak cutting zone, and the force difference between each zone is calculated to obtain the force imbalance. The load fluctuation rate is constructed by the rate of change of the force imbalance between adjacent sampling cycles, and the thermomechanical stress coupling characteristics of the tooth position are calculated by combining the instantaneous temperature rise increment caused by the force change. Based on this, the trajectory offset, load fluctuation rate, and thermomechanical stress parameters of each tooth position are formed to describe the instantaneous cutting behavior of the PDC tooth.

[0081] Furthermore, load propagation paths pointing to the forward, backward, and radially symmetrical teeth are established between all tooth positions, and the propagation amplitude ratio, propagation phase offset, and propagation time difference are calculated. When both the propagation amplitude ratio and phase offset exceed a preset growth threshold, the propagation path is marked as a coupling path. A three-dimensional matrix is ​​constructed based on the tooth position index, propagation direction index, and coupling level, and the difference between the actual propagation time and the theoretical propagation time is added as a residual layer to make the three-dimensional matrix a complete tooth position interaction feature matrix.

[0082] Step S3: Expand the tooth position interaction feature matrix according to the continuous rotation cycle of the drill bit to form four-dimensional time series data. Calculate the following indices in the four-dimensional structure:

[0083] Coupling strength change rate: measures the degree of enhancement of the load propagation coupling between teeth;

[0084] Cumulative phase offset: Represents the cumulative offset of the propagation phase over multiple periods;

[0085] Variation in propagation delay: This indicates the magnitude of change in the propagation time difference across different time periods.

[0086] When the rate of change of coupling strength continues to increase and the cumulative phase offset shows nonlinear growth, the corresponding tooth position is marked as the tooth position of microcrack initiation; when the change of propagation delay suddenly jumps and the direction of trajectory offset reverses in the sampling window, the corresponding tooth position is marked as the tooth position of wear mutation; when an abnormal jump occurs during instantaneous loading, the tooth position is recorded as the tooth position of load jump.

[0087] Based on the order of occurrence of the above three types of events, the key tooth position degradation path is constructed according to the logic of initiation, expansion, and mutation, thereby obtaining a degradation evolution sequence describing the drill bit at the tooth position scale.

[0088] Step S4: Based on the degradation path obtained in Step S3, the path is divided into linear degradation segments, weakly abrupt degradation segments, and strongly abrupt degradation segments according to the degradation rate. The following lifetime characteristics are extracted from each segment:

[0089] Mean value of energy input density fluctuation (linear degradation section); discreteness of impact frequency time interval (weak abrupt change section); continuous offset length of cutting trajectory (strong abrupt change section).

[0090] After normalization, the above three quantities constitute a life characterization feature group, which is used to describe the overall degradation state of the drill bit in the time dimension and tooth position dimension.

[0091] Step S5: Calculate the life stage drift based on the change sequence of the life characterization feature group within a continuous drilling cycle. Then, complete the life stage division based on the drift and feature changes.

[0092] The stable wear stage is defined as when the stage drift is in the low range and the average value of energy input density fluctuation is stable.

[0093] The accelerated decay stage is defined as the stage when the stage drift enters the middle range and the discreteness of the impact frequency time interval changes from a single peak to multiple peaks.

[0094] The critical failure stage is defined as when the stage drift amount enters the high range and the continuous offset length of the cutting trajectory shows a non-periodic increase.

[0095] Stage transition features are identified based on trend slope reversal nodes, offset direction change nodes, and propagation delay change nodes during stage transitions. Stage compression is calculated based on the location and number of stage transition points. The cumulative offset of the degradation path and the stage compression are input into the lifespan back-calculation logic to obtain the drill bit's predicted lifespan.

[0096] In some embodiments of this application, the time alignment in step S1 includes:

[0097] The load rise nodes are extracted from the mechanical parameter sequence, the energy peak nodes are extracted from the vibration and shock sequence, the steady-state section nodes are extracted from the torque and energy consumption sequence, the attitude turning point nodes are extracted from the drill bit attitude change sequence, and the reaction force extreme value nodes are extracted from the bottom hole reaction force fluctuation sequence, resulting in a node set of five types of nodes.

[0098] The node-dense sections on the time axis are computed, and the sections where multiple types of nodes are simultaneously clustered are selected as the baseline sections.

[0099] All multi-source drilling response data are initially aligned using local linear interpolation, and node calibration and alignment are performed based on the time position of nodes in the reference section to obtain synchronous sampling frames containing effective load segments, analyzable attitude segments, and stable reaction force segments.

[0100] Specifically, the time alignment in step S1 is completed through three steps: node extraction, dense section identification, and benchmark section calibration. First, a unified node identification process is performed on the multi-source drilling response data, with node determination based entirely on quantitative calculation rules. For the mechanical parameter sequence, the differential sequence of drilling pressure or standby pressure is calculated within a fixed-length calculation window. When all data in the differential sequence within the window are greater than zero and the mean of the differential sequence is greater than the global mean of the same sequence, the time at the start of the window is recorded as the load rise node. For the vibration and impact sequence, the local extremum of each sampling point is calculated based on the vibration acceleration envelope. When the envelope amplitude of a sampling point is greater than the amplitudes of its two adjacent sampling points, that time is recorded as the energy peak node. For the torque and energy consumption sequences, the variance of the torque value and the slope of the energy consumption value within a fixed-length window are calculated respectively. When the torque window... When the variance is less than 50% of the global torque variance and the energy consumption slope is greater than zero, the starting point of the window is recorded as a steady-state segment node. For the drill bit attitude change sequence, difference sequences are calculated for the inclination and azimuth angles respectively. When the sign of the difference sequence is different from the sign of the difference sequence in the previous interval and the absolute value of the difference is greater than the median of the absolute values ​​of the difference in the sequence, the sampling point is recorded as an attitude inflection node. For the bottom hole reaction force fluctuation sequence, by detecting the local extreme points of the reaction force sequence, when the reaction force value of the sampling point is greater than or less than the reaction force values ​​of the two adjacent sampling points, it is recorded as a reaction force extreme node. Through the above procedures, five types of node sets can be formed: mechanical nodes, impact nodes, steady-state nodes, attitude nodes, and reaction force nodes.

[0101] After obtaining the node set, a fixed-length sliding scan is performed across the entire drilling timeline, and the number of node types appearing within each window is counted. A window containing at least three node types is marked as a node cluster window. Among node cluster windows with consecutive or overlapping relationships, the window set with the largest time span is selected as the node-dense segment, based on the duration of the window coverage. Within the node-dense segment, the frequency of each node type is counted chronologically, and the dense segment with the most node types is determined as the baseline segment, used as the time reference for subsequent sequence alignment.

[0102] After determining the baseline section, a two-stage alignment operation is performed on all multi-source drilling response data. The first stage is preliminary time alignment, which involves local linear interpolation of sequences with different sampling frequencies based on a unified target sampling time axis, ensuring that the time sampling points of all sequences correspond to the same set of timestamps. The second stage is node calibration alignment. Within the baseline section, the target time positions of five types of nodes are used as references. The time offset is calculated based on the actual occurrence time of nodes of the same type in each sequence, and this offset is applied to adjacent time segments of the corresponding sequence. When the offset exceeds half of the target sampling interval, time fine-tuning is performed by inserting or deleting an interpolation point in the original sequence, ensuring that key nodes correspond to the same timestamp in different sequences.

[0103] In some embodiments of this application, the dynamic reconstruction model of the cutting trajectory in step S2 includes:

[0104] An attitude rotation matrix is ​​established based on the drill bit attitude change sequence, and the mechanical parameter sequence and torque and energy consumption sequence are transformed into the equivalent force vector on each tooth position.

[0105] Within each sampling period, the equivalent force vector is rotated according to the attitude rotation matrix to obtain the instantaneous force field of each tooth position;

[0106] The main cutting section, transition section and weak cutting section are divided according to the instantaneous force field change characteristics. The force difference between each section after division is calculated to determine the force imbalance.

[0107] The load volatility is constructed by the change in the amount of force imbalance within adjacent sampling periods;

[0108] Thermomechanical response parameters are calculated based on the instantaneous temperature rise increment and load fluctuation rate caused by the change in force, and used to form the dynamic reconstruction result of the cutting trajectory.

[0109] Specifically, the dynamic reconstruction model of the cutting trajectory in step S2 is completed through five steps: attitude rotation, tooth position force field construction, force segment division, load fluctuation rate calculation, and thermomechanical response calculation. First, the inclination angle and azimuth angle at each sampling moment are obtained based on the drill bit attitude change sequence, and an attitude rotation matrix is ​​constructed using three-dimensional coordinate transformation rules. The attitude rotation matrix is ​​used to describe the spatial orientation of the drill bit coordinate system relative to the wellbore coordinate system at that sampling moment, so that the force data at different times can be expressed in a unified three-dimensional coordinate system. Subsequently, the drilling pressure, rotation speed, and torque values ​​in the mechanical parameter sequence are uniformly processed with the unit time energy input in the torque and energy consumption sequence. According to the spatial position of each tooth position on the cutter blade in the drill bit structure diagram, a mapping relationship from macroscopic parameters to local force at the tooth position is established to obtain the equivalent force vector on each tooth position, where the equivalent force vector includes axial, radial, and tangential components.

[0110] After obtaining the equivalent force vector, the equivalent force vector is rotated in coordinates according to the attitude rotation matrix in each sampling period to make the force vector consistent with the actual spatial attitude of the drill bit, thereby obtaining the instantaneous force field of each PDC tooth in that sampling period. The instantaneous force field is a set of vectors describing the forces exerted on a single tooth position in different directions under a specific attitude, and is used to characterize the real-time force state of the tooth position in contact with the rock strata during the cutting process.

[0111] After constructing the instantaneous force field, the sequence of force changes over time for each tooth position is divided into segments. First, the mean of a fixed-length window is calculated for the tangential component in the force field. When the mean of the window is located in the upper third of the global mean of the sequence, the time period corresponding to that window is designated as the main cutting segment; when the mean of the window is located in the middle third of the global mean, it is designated as the transition segment; and when the mean of the window is located in the lower third of the global mean, it is designated as the weak cutting segment. Subsequently, the difference between the maximum and minimum values ​​of the tangential, axial, and radial components within each segment is calculated, and the weighted sum of these three differences is used as the force difference. The force difference is used as an indicator to measure the uniformity of force in different segments. The difference between the force difference and the global mean force difference is used to define the force imbalance, reflecting whether the force at the tooth position tends to be concentrated or dispersed.

[0112] To characterize the fluctuation of force imbalance over time, the difference between the force imbalance values ​​in adjacent sampling periods is calculated, and the absolute value is taken as the load fluctuation rate. The load fluctuation rate represents the degree of change of the force state at the same tooth position over a short time scale, and is an important quantitative indicator for characterizing force stability and sudden jump behavior.

[0113] After obtaining the load fluctuation rate, the frictional work rate is calculated using the tangential component of the instantaneous force field based on the stress-temperature rise relationship in mechanics. Then, the instantaneous temperature rise increment within a unit sampling period is calculated based on the relationship between the frictional work rate and the material's thermal conductivity and the contact area between the tooth surface and the rock stratum. The instantaneous temperature rise increment reflects the temperature rise caused by changes in thermal effect with force. Using the instantaneous temperature rise increment and the load fluctuation rate as two input quantities, thermomechanical response parameters are constructed through a linear combination. The linear combination coefficients are determined by the material's thermophysical properties and tooth profile parameters, and obtained through calibration data from test samples. By combining the thermomechanical response parameters calculated within each sampling period with the corresponding tooth position's attitude rotation results, the three-dimensional cutting trajectory offset of that tooth position can be reconstructed, thus forming a dynamic reconstruction result of the cutting trajectory, providing fundamental data for subsequent tooth position degradation analysis.

[0114] When calculating the instantaneous temperature rise increment, the equivalent force vectors of adjacent synchronous sampling frames are first interpolated to obtain the force change. Simultaneously, the cutting work change trend of adjacent sampling frames is calculated for the cutting work sequence, and the energy consumption change trend per unit time is calculated for the torque and energy consumption sequences. The force change, cutting work change trend, and energy consumption change trend are jointly analyzed to determine the increase or decrease in frictional energy input at the tooth-rock interface within the current sampling period. Then, based on the frictional energy input change, the material's specific heat capacity, contact area, and thermal conductivity, the instantaneous temperature rise increment for the current sampling period is calculated according to the thermomechanical coupling relationship. The instantaneous temperature rise increment describes the strength of the thermal effect caused by the force change and is an important input for constructing thermomechanical response parameters.

[0115] When calculating the load fluctuation rate, the difference in force imbalance between consecutive synchronous sampling frames is first used as the amplitude of change. Then, the sign of the difference is used to record whether the force imbalance is increasing or decreasing, and this positive or negative direction is taken as the direction of change. At the same time, the number of times the force imbalance changes in both directions within a fixed-length time window is counted, and this number is taken as the frequency of change. The amplitude, direction, and frequency of change are combined according to a preset weighting to form the load fluctuation rate, which is used to characterize the comprehensive fluctuation degree of the PDC tooth's load state in a short period of time, serving as an important basis for subsequent thermomechanical response calculations and degradation analysis.

[0116] In some embodiments of this application, the tooth position interaction feature matrix in step S2 includes:

[0117] For each tooth position, establish the load propagation path pointing to the forward tooth, the backward tooth, and the radially symmetrical tooth, and calculate the propagation amplitude ratio, propagation phase offset, and propagation time difference in the propagation path;

[0118] When both the propagation amplitude ratio and the propagation phase offset exceed the corresponding growth threshold, the corresponding path is marked as a coupling path.

[0119] A three-dimensional matrix is ​​generated based on the tooth position index, propagation direction index, and coupling level. A residual layer is added to the three-dimensional matrix to record the difference between the actual propagation time and the theoretical inter-tooth propagation time. The three-dimensional matrix is ​​a tooth position interaction feature matrix.

[0120] The tooth position index is based on the external structural parameters of the drill bit. The PDC teeth arranged circumferentially on the outer edge of the drill bit are numbered in circumferential angle order to form circumferential numbers; the PDC teeth arranged along the blade direction are numbered according to the axial step position to form axial numbers; the circumferential numbers and axial numbers are combined according to a fixed arrangement rule to form a tooth position index used to identify the spatial position of each PDC tooth.

[0121] The growth threshold can be determined based on historical degradation data statistics or dynamically adjusted through online learning algorithms. Its purpose is to ensure that critical coupling is only marked when both load transfer strength and synchronization are abnormal, effectively filtering out interference from random vibration noise.

[0122] The propagation direction index is based on the force change sequence, trajectory offset change sequence, and temperature rise increment sequence of adjacent teeth. It calculates the time difference of change of adjacent teeth in these sequences. When the time difference of change of a certain sequence shows a circumferential progressive relationship among multiple adjacent teeth, the propagation direction index is marked as the circumferential direction. When the time difference of change shows a radial progressive relationship, the propagation direction index is marked as the radial direction. When the time difference of change shows a progressive relationship along the blade direction, the propagation direction index is marked as the blade direction.

[0123] The coupling level is based on the degree of synchronization of the load fluctuation rate between adjacent teeth, the degree of synchronization of the instantaneous temperature rise increment, and the similarity of the trajectory offset change waveform. The three types of synchronization are classified according to the preset classification rules. When all three types of synchronization are in the high-level range, the coupling level is marked as the first level. When any two of the three types of synchronization are in the middle-level range, the coupling level is marked as the second level. When all three types of synchronization are in the low-level range, the coupling level is marked as the third level.

[0124] Specifically, the tooth position interaction feature matrix in step S2 is formed through steps such as load propagation path construction, propagation feature quantity calculation, and three types of index generation, and is used to describe the mechanical propagation relationship between each PDC tooth. First, based on the drill bit structural parameters, the arrangement of each PDC tooth in the circumferential direction and the blade direction of the drill bit is obtained, and a load propagation path is established for each PDC tooth pointing to its circumferentially forward tooth, circumferentially backward tooth, and radially symmetrical tooth. For each propagation path, based on the instantaneous force field, trajectory offset sequence, and instantaneous temperature rise increment sequence obtained in step S2, the propagation amplitude ratio, propagation phase offset, and propagation time difference of the propagation path are calculated, where the propagation amplitude ratio is the ratio of the force amplitudes at both ends of adjacent teeth, the propagation phase offset is the phase difference of the force timing at both ends, and the propagation time difference is the time difference between the characteristic points of the force waveform at both ends.

[0125] For each propagation path, the mean of the propagation amplitude ratio sequence and the mean of the propagation phase offset sequence are calculated within a fixed-length analysis window. These are then compared to reference values ​​obtained statistically from the propagation characteristics of all tooth positions within the same window. When the mean of the propagation amplitude ratio is greater than the reference value, and the mean of the propagation phase offset is also greater than its reference value, the propagation path is marked as a coupled path, and this is used as one of the input conditions for subsequent coupling level classification.

[0126] When constructing the tooth position interaction feature matrix, a tooth position index is first generated for each PDC tooth to identify its unique spatial location within the drill bit structure. Specifically, based on the circumferential distribution of the drill bit's outer edge, all PDC teeth are numbered from smallest to largest circumferential angle to obtain circumferential serial numbers. Then, based on the axial step height order of the drill bit's cutter blade structure, the PDC teeth on the same or different cutter blades are numbered from front to rear to obtain axial serial numbers. Finally, a tooth position index is generated according to a preset combination rule (e.g., combining the circumferential serial number as the high-order bit and the axial serial number as the low-order bit). The tooth position index is an integer pair or a uniquely mapped code used to identify the three-dimensional positional relationship of the teeth.

[0127] The propagation direction index is used to determine the main direction of load propagation. Specifically, the time difference between adjacent sampling points is calculated for the sequence of changes in force imbalance between adjacent teeth, the sequence of changes in trajectory offset, and the sequence of instantaneous temperature rise increments. When a sequence shows a monotonically changing trend of time difference according to circumferential sequence among multiple consecutive tooth positions, the propagation direction index is marked as the circumferential direction; when the time difference shows a progressive trend according to radial symmetry, the propagation direction index is marked as the radial direction; when the time difference progresses according to axial sequence, the propagation direction index is marked as the blade direction. The propagation direction index can take three states: "circumferential," "radial," or "blade," used to describe the spatial directionality of the propagation path.

[0128] To measure the synchronicity of responses between tooth positions, this embodiment also generates a coupling level based on the correlation between load volatility, instantaneous temperature rise increment, and trajectory offset change sequences. Specifically, within a fixed time window, the Pearson correlation coefficient of the load volatility sequence, the Pearson correlation coefficient of the instantaneous temperature rise increment sequence, and the dynamic time warping distance (DTW) similarity of the trajectory offset change sequence between adjacent teeth are calculated, and these three synchronicity indices are compared with preset high, medium, and low intervals. When all three synchronicity indices are in the high interval, the coupling level is marked as the first level; when two of the three synchronicity indices are in the medium interval, the coupling level is marked as the second level; and when all three synchronicity indices are in the low interval, the coupling level is marked as the third level. The coupling level is used to reflect the strength of the comprehensive mechanical correlation between tooth positions.

[0129] After obtaining the tooth position index, propagation direction index, and coupling level, these three elements are arranged into a three-dimensional matrix according to a preset dimension. In this three-dimensional matrix, each matrix cell corresponds to a tooth position pair and its propagation direction and coupling level relationship. Simultaneously, a residual layer is added within the three-dimensional matrix to record the difference between the actual propagation time and the theoretical propagation time calculated based on the inter-tooth geometry.

[0130] In some embodiments of this application, the timing analysis in step S3 includes:

[0131] The tooth position interaction feature matrix is ​​expanded into four-dimensional time series data within a continuous rotation cycle, and the coupling strength change rate, phase cumulative offset and propagation delay change are calculated.

[0132] When the rate of change of coupling strength continues to increase and the cumulative phase offset shows nonlinear growth between adjacent cycles, the corresponding tooth position is recorded as the microcrack initiation tooth position.

[0133] When the change in propagation delay jumps and the trajectory offset direction reverses within the synchronous sampling window, the corresponding tooth position is recorded as the tooth position with wear mutation.

[0134] Establish tooth degeneration paths in all tooth positions according to the order of eruption, expansion, and mutation.

[0135] Specifically, the time-series analysis in step S3 is based on the tooth position interaction feature matrix, which is expanded cycle by cycle along the time axis within multiple consecutive drill bit rotation cycles to form four-dimensional time-series data containing tooth position index, propagation direction index, coupling level, and residual layer value. Each time slice in the four-dimensional time-series data corresponds to one rotation cycle. By calculating the difference, direction of difference, and cumulative difference of the coupling level value, residual layer value, and corresponding propagation direction value in adjacent time slices, the coupling strength change rate, phase cumulative offset, and propagation delay change are obtained. The coupling strength change rate is a quantitative indicator that records the magnitude and direction of the change in the coupling level value of a certain tooth position within a continuous time slice, used to reflect the synchronous enhancement or weakening trend of the load propagation between the tooth position and surrounding teeth; the phase cumulative offset is the cumulative sum of the propagation phase offset in a continuous time slice, used to describe whether the degree of phase misalignment caused by the difference in the load propagation path shows a continuous accumulation; the propagation delay change is the magnitude of the change in the load propagation time difference between adjacent teeth in a continuous time slice, used to characterize whether there is a sudden time delay jump in the load propagation.

[0136] After the four-dimensional time-series data is generated, the rate of change of coupling strength and the cumulative phase shift of each tooth position in continuous rotation cycles are jointly analyzed. When the rate of change of coupling strength of a certain tooth position continues to increase compared with the previous cycle for several consecutive cycles (i.e., the coupling level difference is positive and changes continuously in the same direction), and the cumulative phase shift shows a significant amplification relative to the cumulative amount of the previous cycle (i.e., the cumulative phase difference in continuous cycles shows an increasing trend, and the increase exceeds the average change of phase difference recorded in the steady state of the tooth position), it can be determined that the load propagation structure of the tooth position has entered a non-equilibrium accumulation state. This type of state usually corresponds to early damage behaviors such as microscale structural relaxation, microcrack initiation, or micro-stripping at the tooth-rock interface. Therefore, this tooth position is recorded as a microcrack initiation tooth position for subsequent degradation path analysis.

[0137] Subsequently, the propagation delay change and trajectory offset direction of each tooth position in the four-dimensional time series data are jointly judged. In this embodiment, the propagation delay change is used to characterize whether there is a sudden jump in the time difference of the force propagation path. When the propagation delay change of a certain tooth position suddenly increases compared to the previous period (i.e., the time difference increase exceeds the standard range of delay change of that tooth position in the steady state stage), and the corresponding trajectory offset direction reverses within the same synchronous sampling window (i.e., the direction vector of the trajectory offset changes direction by about 180° between consecutive time slices), it means that the load path of that tooth position has undergone structural rearrangement, usually caused by abrupt changes in the wear surface morphology, abrupt changes in the cutting contact area, or micro-collapse. Therefore, this tooth position is recorded as a wear abrupt change tooth position, indicating that it has experienced a sudden change in load characteristics during the degradation process.

[0138] After identifying the microcrack initiation sites and wear abrupt change sites, the changes in all sites across consecutive time slices are sorted chronologically. First, an initiation sequence is generated based on the order of appearance of the microcrack initiation sites. Then, an expansion sequence is formed based on the increasing coupling imbalance region over time. Finally, a mutation sequence is generated based on the identification time of the wear abrupt change sites.

[0139] In some embodiments of this application, the lifetime characterization feature set in step S4 includes:

[0140] The tooth position degradation path is divided into linear degradation segment, weakly abrupt degradation segment, and strongly abrupt degradation segment according to the degradation rate;

[0141] In the linear degradation zone, the mean fluctuation of energy input density is calculated; in the weak abrupt change zone, the time interval discreteness of impact frequency is calculated; and in the strong abrupt change zone, the continuous offset length of cutting trajectory deviation is calculated.

[0142] The mean fluctuation, the discrete amount of time interval, and the continuous offset length are normalized, and a lifetime characterization feature group is formed based on the normalization results.

[0143] Specifically, the lifetime characterization feature group in step S4 is constructed based on the tooth position degradation path obtained in step S3. First, the joint change sequence of the coupling strength change rate, propagation delay change, and trajectory offset of each tooth position in the tooth position degradation path on continuous time slices is analyzed according to the stability of the change amplitude and change direction. By comparing the numerical differences between continuous time slices, if multiple change values ​​of a certain tooth position are relatively stable, maintain the same direction, and the difference amplitude is within its steady-state statistical range, then the path segment corresponding to that tooth position is divided into a linear degradation segment; if the change sequence shows an increase in amplitude but the direction is not completely reversed, and the change increase is between the upper bound of the steady state and the lower bound of the sudden change, then the segment is divided into a weakly abrupt change segment; if the change sequence shows a sudden large jump, a change in direction, or a sudden expansion of the trajectory offset, then the segment is divided into a strongly abrupt change segment. Through the above division method, the degradation path is divided into three segments with different damage characteristics, which are used to further construct lifetime characterization indicators.

[0144] After segmenting the data, key characterization parameters of different types are extracted for linear degradation segments, weakly abrupt ...

[0145] Subsequently, the mean fluctuation, the time interval discreteness, and the continuous offset length are normalized. In this embodiment, the normalization process involves subtracting the statistical average of the corresponding index in the steady-state stage from each of the three values, and then dividing by the statistical standard deviation of that index in the steady-state stage, to obtain comparable dimensionless results. Through normalization, the three feature quantities from different sources are mapped to a unified scale space, which can be used for subsequent lifetime trend judgment. Finally, the normalized mean fluctuation, the normalized time interval discreteness, and the normalized continuous offset length are combined in a predetermined order to form a lifetime characterization feature set, which is used to characterize the comprehensive state characteristics of the drill bit at different degradation stages and provides input for the lifetime prediction algorithm in step S5.

[0146] In some embodiments of this application, the lifetime stage division in step S5 includes:

[0147] The stage drift is calculated based on the numerical changes of the life characterization feature group in three consecutive drilling cycles.

[0148] When the stage drift is in the low range and the average fluctuation of energy input density remains stable, the current stage is classified as the stable wear stage.

[0149] When the stage drift enters the middle range and the discreteness of the impact frequency time interval changes from a single peak to multiple peaks, the current stage is classified as the accelerated decay stage.

[0150] When the stage drift amount enters the high range and the continuous offset length of the trajectory deviation is non-periodic, the current stage is classified as the critical failure stage.

[0151] Specifically, the life stage division in step S5 is based on the life characterization feature group obtained in step S4. First, three normalized characteristic quantities of the life characterization feature group are recorded in three consecutive drilling cycles: the normalized mean fluctuation of energy input density, the normalized time interval discreteness of impact frequency, and the normalized continuous offset length of the cutting trajectory. The values ​​of these three characteristic quantities in the consecutive cycles are arranged in a 3x3 matrix according to time sequence. By calculating the sum of the variation differences of each column of characteristic quantities in the three cycles, the consistency of the change sign, and the proportion of the change amplitude, the stage difference component of that characteristic quantity is obtained. Then, the three stage difference components are combined according to a predetermined weighting method to form the stage drift quantity, which reflects the overall life characteristic change. The stage drift quantity is a dimensionless value used to describe the intensity of the shift of the life characterization feature group from one stage to the next.

[0152] After obtaining the stage drift, the lifespan stages are divided based on the interval position of the stage drift and the specific changes in the three characteristic quantities. When the stage drift is located within a predefined low interval, and the variation amplitude of the normalized fluctuation mean of the energy input density falls within the steady-state statistical allowable range for three consecutive cycles, and the difference sign remains consistent, the current stage is determined to be a stable wear stage. The stable wear stage indicates that the stress state, thermomechanical response, and trajectory deviation behavior of each tooth position of the drill bit maintain a relatively regular wear pattern, and no significant degradation acceleration occurs.

[0153] When the stage drift enters the middle interval, it is further determined whether the time interval dispersion of the impact frequency changes from a single-peak to a multi-peak pattern. The peak shape of the time interval dispersion is determined by the number of main peaks in the statistical histogram of the impact event time intervals. A single peak indicates that the impact event intervals are concentrated in a single interval, while a multi-peak pattern indicates that the impact event intervals have significant counts in more than two intervals. When a change from a single peak to a multi-peak pattern occurs, it indicates that multiple impact rhythms coexist under the drill bit load, suggesting that the drill bit wear has entered an unstable expansion stage. Therefore, this stage is identified as the accelerated decay stage.

[0154] When the stage drift enters the high range, it is further determined whether the continuous offset length of the cutting trajectory exhibits aperiodic growth. The continuous offset length records the number of consecutive time slices in which the offset falls into the abnormal offset range; aperiodic growth is determined by comparing the continuous offset length of three consecutive cycles with the theoretical offset length sequence corresponding to the drill bit rotation cycle. When the actual continuous offset length no longer exhibits a repeating pattern with the cycle, but increases monotonically, it is judged as aperiodic growth. This phenomenon indicates that the trajectory offset is no longer affected by the rotation cycle and shows a continuous degradation trend, reflecting that the drill bit wear is approaching its limit. Therefore, this stage is classified as the critical failure stage.

[0155] In some embodiments of this application, the stage transition feature identification in step S5 includes:

[0156] The nodes of trend slope reversal, trajectory offset direction change, and propagation delay change in the lifetime characterization feature group are recorded as three types of event sequences.

[0157] When two of the three types of events occur within the same sampling window, the current window is recorded as the stage transition event window.

[0158] When the stage transition event window appears consecutively in two adjacent sampling windows and the increase in the offset angle of the trajectory offset direction is greater than the increase in the previous window, the current window is determined as the stage transition judgment window.

[0159] Specifically, the stage transition feature identification in step S5 is based on the determination of multiple key change behaviors in the lifetime characterization feature group. First, the trend slope of each normalized feature quantity in the lifetime characterization feature group is calculated in three consecutive sampling windows, and the sampling window where the trend slope changes from positive to negative or from negative to positive is recorded as the trend slope reversal node. Second, the direction difference of the cutting trajectory offset vector in adjacent sampling windows is calculated. When the absolute value of the direction difference exceeds the direction change threshold, the window is recorded as the trajectory offset direction change node. Third, the difference of the propagation delay change in adjacent sampling windows is calculated. When the difference value enters the abnormal fluctuation range from the stable fluctuation range, the window is recorded as the propagation delay change node. Through the above methods, the trend slope reversal event sequence, the trajectory offset direction change event sequence, and the propagation delay change event sequence are formed respectively.

[0160] After obtaining the three types of event sequences, event counting is performed for each sampling window. When any two types of events from the three event sequences occur simultaneously in the same sampling window, that sampling window is marked as a stage transition event window. The stage transition event window represents a multi-dimensional synchronous abnormal change in the lifetime characterization feature group, indicating a critical stage division.

[0161] After determining the stage transition event window, to avoid misjudgments caused by occasional noise, the system further checks whether the stage transition event windows appear consecutively in two adjacent sampling windows and compares the increase in the offset direction angle at the trajectory offset direction change node. The increase in the trajectory offset direction angle is defined as the angle difference between the trajectory offset vector direction and two adjacent sampling windows. When the angle difference in the current window is greater than the angle difference in the previous window, it indicates that the offset direction change is intensifying, exhibiting typical characteristics of a stage abrupt change. When both of the above conditions are met—that is, the stage transition event windows appear consecutively and the increase in the trajectory offset direction angle shows an increasing trend—the current sampling window is determined as the stage transition determination window. The stage transition determination window serves as the final trigger point for life stage division. Its appearance signifies a clear state transition of the drill bit from the original life stage to the next life stage, supported by reliable physical evidence and statistical characteristics.

[0162] In some embodiments of this application, the calculation of the drill bit life prediction value includes:

[0163] The stage compression amount is calculated based on the position and number of stage transition judgment windows, and lifetime back-calculation is established based on the change sequence of stage compression amount in the accelerated decay stage.

[0164] By using the cumulative offset of the degradation path and the change in stage compression as inputs, the remaining life prediction of the drill bit is obtained.

[0165] Specifically, the calculation of drill bit life prediction values ​​is based on the stage transition judgment window, degradation path characteristic quantities, and stage compression as core quantitative criteria. First, the identified stage transition judgment windows are sorted according to their sampling sequence indices, the sampling position of each window is recorded, and the sampling interval between two adjacent stage transition judgment windows is calculated. Stage compression is defined as the difference between the sampling interval of two adjacent stage transition judgment windows and the average sampling interval of the first three consecutive sampling cycles in the stable wear stage. A positive difference indicates a shortened stage interval, i.e., signs of accelerated wear; a zero difference indicates that the stage interval remains at its original level; and a negative difference indicates a slowdown in stage advancement. In the case of multiple stage transition judgment windows, all stage compression values ​​are arranged in sampling order to form a stage compression sequence. The stage compression sequence is used to describe the rate of change in the life stage from stable wear to accelerated decay, and then to the failure threshold.

[0166] Subsequently, the stage compression rate of change is calculated based on the stage compression sequence. The stage compression rate of change is defined as the difference between the compression amounts of two adjacent stages, used to describe the acceleration of stage compression. When the stage compression rate of change is positive across multiple stage transition judgment windows, it indicates that the stage advancement speed is gradually increasing; when the rate of change is close to zero and remains continuously, it indicates that wear is in a stable expansion state; when the rate of change shows a continuous positive increase, it indicates that wear is entering the transition process towards the critical failure stage. In this embodiment, the stage compression rate of change is used as the time series basis for describing the lifetime advancement speed.

[0167] After calculating the compression and its rate of change in the calculation phase, the degradation path of critical tooth positions is quantitatively analyzed. The degradation path of critical tooth positions, obtained in step S3, includes the time series arrangement of events such as microcrack initiation, abrupt wear changes, and load jumps. To quantify the degradation path, the trajectory offsets of all critical tooth positions in consecutive sampling frames are accumulated to obtain the cumulative offset. The cumulative offset is defined as the sum of the changes in trajectory offset of each critical tooth position between two adjacent synchronous sampling windows throughout the entire drilling life. The cumulative offset reflects the overall magnitude of degradation of multiple tooth positions on the cutter blade and is a core indicator describing the degree of geometric degradation of the drill bit. A higher cumulative offset indicates a more significant tooth wear imbalance and a more unstable overall cutting state of the drill bit.

[0168] After obtaining the cumulative offset and the stage compression rate of change, both are used as input parameters for lifetime backtracking calculation. In one specific embodiment, the lifetime backtracking calculation employs the following steps: First, the cumulative offset and the stage compression rate of change are normalized according to their respective normalization ranges to ensure that their magnitudes are consistent. Then, the normalized cumulative offset and the stage compression rate of change are combined to form a lifetime representation vector. The lifespan characterization vector is compared as follows: When the cumulative offset is in the high range and the stage compression rate is positive three times consecutively, the drill bit is judged to have entered the critical failure stage. The remaining lifespan prediction time or acceptable drilling distance is obtained by back-calculating based on the difference between the lifespan characterization vector and the preset critical failure threshold. When the cumulative offset is in the middle range and the stage compression rate is positive twice consecutively, the drill bit is judged to be in the accelerated decay stage. The number of remaining sampling periods to reach the critical failure stage is calculated by extrapolating the stage compression rate in subsequent sampling periods, and then converted into the remaining drilling time or remaining drilling distance. When the cumulative offset is in the low range and the stage compression rate is close to zero, the drill bit is judged to still be in the stable wear stage. At this time, the number of sampling periods from the next stage transition judgment window is calculated by the growth rate of the cumulative offset, and then converted into the remaining lifespan prediction value.

[0169] In this embodiment, the final output of the life prediction is the remaining working time or drilling depth of the drill bit, depending on the monitoring method used in the field application. This life prediction value is generated based on a combination rule of geometric degradation (cumulative offset) and stage advance rate (stage compression change rate). It can directly reflect the development process of drill bit wear and failure through the continuous parameter change trend without relying on empirical thresholds, thereby providing a quantifiable life prediction basis for drilling operations.

[0170] It should be noted that the growth threshold, reference value, high segment, middle segment, low segment, predefined low interval, middle interval, high interval, high value interval, middle value interval, low value interval, steady-state statistical allowable range, delay change standard range, abnormal fluctuation interval, direction change threshold, and failure critical threshold used in S1 to S5 can all be determined through statistical analysis of historical sample data from the stable wear stage. A representative time window of the drill bit during the stable wear stage is selected, and the mean μ and standard deviation σ are calculated for the target characteristic quantities (including energy input density, impact frequency time interval, cutting trajectory offset length, propagation delay change, trajectory offset direction change angle, etc.). The range of values ​​less than μ+σ is defined as the low value interval, the range between μ+σ and μ+2σ is defined as the middle value interval, and the range greater than μ+2σ is defined as the high value interval. The low segment, middle segment, high segment, and predefined low interval, middle interval, and high interval correspond to the above three value ranges, respectively. The growth threshold can be set as μ+2σ of the characteristic quantity in the stable wear stage. The direction change threshold can be set as the mean plus twice the standard deviation of the trajectory offset direction change angle in the stable wear stage. The allowable range of steady-state stage statistics can be set as the range of the target characteristic quantity within μ±2σ. The standard range of delay change can be set as the μ±2σ interval of the propagation time difference in the stable wear stage. Values ​​exceeding this interval are considered to be in the abnormal fluctuation range. The reference value uniformly refers to the mean obtained through the statistics of the stable wear stage or the limit value derived based on the mean and standard deviation. The reference values ​​corresponding to each indicator can be pre-calibrated and stored in the system during implementation. The failure critical threshold can be obtained by statistically analyzing the life characterization feature group of historical failed drill bit samples in the stage before failure. The mean of the combined characteristic quantities (including stage drift and cumulative offset) plus one standard deviation is used as the numerical threshold for determining whether the drill bit has entered the failure critical stage. Under the same well section or similar formation conditions, the above thresholds and intervals can remain unchanged once determined, and can also be recalculated based on the newly added stable wear stage data when necessary.

[0171] See Figure 2 As shown, this embodiment of the invention provides a PDC drill bit lifespan prediction and analysis system, comprising:

[0172] The data alignment module is configured to acquire multi-source drilling response data during the drilling process. The multi-source drilling response data includes mechanical parameter sequences, vibration and shock sequences, torque and energy consumption sequences, drill bit attitude change sequences, and bottom hole reaction force fluctuation sequences; and to perform time alignment on all multi-source drilling response data based on the acquisition time.

[0173] The interaction feature module is configured to construct a dynamic reconstruction model of the cutting trajectory based on time-aligned multi-source drilling response data, obtain the trajectory offset, load fluctuation rate and thermomechanical stress coupling characteristics of each PDC tooth, and construct a tooth position interaction feature matrix that includes the interaction relationship between all PDC teeth.

[0174] The degradation analysis module is configured to perform time-series analysis on the tooth position interaction feature matrix, identify the microcrack evolution indicators, wear stage abrupt change points and load jump points of each PDC tooth during continuous drilling, and construct the key tooth position degradation path according to the microcrack initiation sequence, wear propagation sequence and load jump sequence.

[0175] The feature extraction module is configured to extract the mean value of energy input density fluctuation, the discrete amount of impact frequency time interval, and the continuous offset length of cutting trajectory based on the changing trend of the key tooth position degradation path, forming a life characterization feature set.

[0176] The life prediction module is configured to divide the drill bit life into a stable wear stage, an accelerated decay stage, and a critical failure stage based on the life characterization feature group, and use the abrupt change point of the characterization feature at the time of life stage transition as the basis for life prediction to obtain the predicted value of drill bit life.

[0177] This application also provides a PDC drill bit material, prepared by the following steps:

[0178] 1) Micronized powder cleaning: After acid washing and alkali washing, the diamond micronized powder is rinsed with distilled water 2-3 times;

[0179] 2) Transition layer preparation: The TiMoTa transition layer on the surface of diamond micropowder was prepared by a dual-glow plasma surface alloying (DGPSA) device;

[0180] 3) Obtaining the finished product: The cemented carbide is ultrasonically treated in anhydrous ethanol for 30 minutes to remove surface impurities. The sputtered diamond powder and the treated cemented carbide matrix are placed in a metal container and pressed into a sheet to obtain the composite material. The metal container is either a molybdenum container or a tantalum container. The composite material, along with the metal container encasing it, is assembled with a pyrophyllite assembly block. It is then placed in a six-sided press for high-temperature, high-pressure sintering, followed by a predetermined holding time to obtain the sintered body. The sintered body is removed from the six-sided press, cooled, and depressurized. The outer container is removed, and the surface is ground and polished to obtain a high-temperature, wear-resistant polycrystalline diamond composite sheet.

[0181] In addition, see Figure 3 and Figure 4As shown, the PDC drill bit material prepared through the above steps, when used in the production of PDC drill bits, further includes: firstly, extracting the surface geometric features of the clam shell, pangolin scales, and comb-scallop shell, and establishing geometric mathematical models of convex hull geometric structure 5 and prism geometric structure 6. The spacing of the convex hull geometric structure 5 is set to 22.5 mm, its radius to 7.5 mm, and its height to 2 mm. The spacing of the prism geometric structure 6 is set to 15.71 mm, its cross-sectional length to 7.854 mm, and its height to 3 mm. The convex hull geometric structure 5 and the prism geometric structure 6 are arranged alternately.

[0182] The cemented carbide substrate 2 and the polycrystalline diamond layer 1 are connected by tenons. First, a small internal "sea eye" 4 with a larger external diameter is formed in the cemented carbide substrate 2. Then, a small head and a large root tenon 3 is formed in the polycrystalline diamond layer 1. The sea eye 4 and the tenon 3 have the same external curve design. During assembly, the polycrystalline diamond layer 1 is inserted into the cemented carbide substrate 2 in one go.

[0183] In the description of this invention, it should be understood that the terms "longitudinal", "lateral", "up", "down", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this invention, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0184] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made by those skilled in the art to the technical solutions of the present invention without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for predicting and analyzing the service life of PDC drill bits, characterized in that, include: S1: Acquire multi-source drilling response data during the drilling process. The multi-source drilling response data includes mechanical parameter sequences, vibration and impact sequences, torque and energy consumption sequences, drill bit attitude change sequences, and bottom hole reaction force fluctuation sequences; perform time alignment on all multi-source drilling response data based on the acquisition time; S2: Construct a dynamic reconstruction model of the cutting trajectory based on time-aligned multi-source drilling response data, obtain the trajectory offset, load fluctuation rate and thermomechanical stress coupling characteristics of each PDC tooth, and construct a tooth position interaction feature matrix that includes the interaction relationship between all PDC teeth. S3: Perform time-series analysis on the tooth position interaction feature matrix to identify the microcrack evolution indicators, wear stage abrupt change points, and load jump points of each PDC tooth during continuous drilling. Construct the key tooth position degradation path according to the microcrack initiation sequence, wear propagation sequence, and load jump sequence. S4: Based on the changing trend of the key tooth position degradation path, extract the mean value of energy input density fluctuation, the discrete amount of impact frequency time interval and the continuous offset length of cutting trajectory to form a life characterization feature group. S5: Based on the life characterization feature group, the drill bit life is divided into the stable wear stage, the accelerated decay stage and the failure critical stage, and the sudden change point of the characterization feature at the time of life stage transition is used as the basis for life prediction to obtain the predicted value of drill bit life. The dynamic reconstruction model of the cutting trajectory in step S2 includes: An attitude rotation matrix is ​​established based on the drill bit attitude change sequence, and the mechanical parameter sequence and torque and energy consumption sequence are transformed into the equivalent force vector on each tooth position. Within each sampling period, the equivalent force vector is rotated according to the attitude rotation matrix to obtain the instantaneous force field of each tooth position; The main cutting section, transition section and weak cutting section are divided according to the instantaneous force field change characteristics. The force difference between each section after division is calculated to determine the force imbalance. The load volatility is constructed by the change in the amount of force imbalance within adjacent sampling periods; Thermomechanical response parameters are calculated based on the instantaneous temperature rise increment and load fluctuation rate caused by the change in force, which are used to form the dynamic reconstruction results of the cutting trajectory; The lifespan stage division in step S5 includes: The stage drift is calculated based on the numerical changes of the life characterization feature group in three consecutive drilling cycles. When the stage drift is in the low range and the average fluctuation of energy input density remains stable, the current stage is classified as the stable wear stage. When the stage drift enters the middle range and the discreteness of the impact frequency time interval changes from a single peak to multiple peaks, the current stage is classified as the accelerated decay stage. When the stage drift amount enters the high range and the continuous offset length of the trajectory deviation is non-periodic, the current stage is classified as the critical failure stage.

2. The PDC drill bit lifespan prediction and analysis method according to claim 1, characterized in that, The time alignment in step S1 includes: The load rise nodes are extracted from the mechanical parameter sequence, the energy peak nodes are extracted from the vibration and shock sequence, the steady-state section nodes are extracted from the torque and energy consumption sequence, the attitude turning point nodes are extracted from the drill bit attitude change sequence, and the reaction force extreme value nodes are extracted from the bottom hole reaction force fluctuation sequence, resulting in a node set of five types of nodes. The node-dense sections on the time axis are computed, and the sections where multiple types of nodes are simultaneously clustered are selected as the baseline sections. All multi-source drilling response data are initially aligned using local linear interpolation, and node calibration and alignment are performed based on the time position of nodes in the reference section to obtain synchronous sampling frames containing effective load segments, analyzable attitude segments, and stable reaction force segments.

3. The PDC drill bit lifespan prediction and analysis method according to claim 2, characterized in that, The tooth position interaction feature matrix in step S2 includes: For each tooth position, establish the load propagation path pointing to the forward tooth, the backward tooth, and the radially symmetrical tooth, and calculate the propagation amplitude ratio, propagation phase offset, and propagation time difference in the propagation path; When both the propagation amplitude ratio and the propagation phase offset exceed the corresponding growth threshold, the corresponding path is marked as a coupling path. A three-dimensional matrix is ​​generated based on the tooth position index, propagation direction index, and coupling level. A residual layer is added to the three-dimensional matrix to record the difference between the actual propagation time and the theoretical inter-tooth propagation time. The three-dimensional matrix is ​​a tooth position interaction feature matrix.

4. The PDC drill bit service life prediction and analysis method according to claim 3, characterized in that, The timing analysis in step S3 includes: The tooth position interaction feature matrix is ​​expanded into four-dimensional time series data within a continuous rotation cycle, and the coupling strength change rate, phase cumulative offset and propagation delay change are calculated. When the rate of change of coupling strength continues to increase and the cumulative phase offset shows nonlinear growth between adjacent cycles, the corresponding tooth position is recorded as the microcrack initiation tooth position. When the change in propagation delay jumps and the trajectory offset direction reverses within the synchronous sampling window, the corresponding tooth position is recorded as the tooth position with wear mutation. Establish tooth degeneration paths in all tooth positions according to the order of eruption, expansion, and mutation.

5. The PDC drill bit service life prediction and analysis method according to claim 4, characterized in that, The lifetime characterization feature set in step S4 includes: The tooth position degradation path is divided into linear degradation segment, weakly abrupt degradation segment, and strongly abrupt degradation segment according to the degradation rate; In the linear degradation zone, the mean fluctuation of energy input density is calculated; in the weak abrupt change zone, the time interval discreteness of impact frequency is calculated; and in the strong abrupt change zone, the continuous offset length of cutting trajectory deviation is calculated. The mean fluctuation, the discrete amount of time interval, and the continuous offset length are normalized, and a lifetime characterization feature group is formed based on the normalization results.

6. The PDC drill bit lifespan prediction and analysis method according to claim 5, characterized in that, Step S5, which involves identifying stage transition features, includes: The nodes of trend slope reversal, trajectory offset direction change, and propagation delay change in the lifetime characterization feature group are recorded as three types of event sequences. When two of the three types of events occur within the same sampling window, the current window is recorded as the stage transition event window. When the stage transition event window appears consecutively in two adjacent sampling windows and the increase in the offset angle of the trajectory offset direction is greater than the increase in the previous window, the current window is determined as the stage transition judgment window.

7. The PDC drill bit service life prediction and analysis method according to claim 6, characterized in that, The calculation of the drill bit life prediction includes: The stage compression amount is calculated based on the position and number of stage transition judgment windows, and lifetime back-calculation is established based on the change sequence of stage compression amount in the accelerated decay stage. By using the cumulative offset of the degradation path and the change in stage compression as inputs, the remaining life prediction of the drill bit is obtained.

8. A PDC drill bit lifespan prediction and analysis system, used to implement the PDC drill bit lifespan prediction and analysis method according to any one of claims 1-7, characterized in that, include: The data alignment module is configured to acquire multi-source drilling response data during the drilling process, including mechanical parameter sequences, vibration and impact sequences, torque and energy consumption sequences, drill bit attitude change sequences, and bottom hole reaction force fluctuation sequences; and to perform time alignment on all multi-source drilling response data based on the acquisition time. The interaction feature module is configured to construct a dynamic reconstruction model of the cutting trajectory based on time-aligned multi-source drilling response data, obtain the trajectory offset, load fluctuation rate and thermomechanical stress coupling characteristics of each PDC tooth, and construct a tooth position interaction feature matrix that includes the interaction relationship between all PDC teeth. The degradation analysis module is configured to perform time-series analysis on the tooth position interaction feature matrix, identify the microcrack evolution indicators, wear stage abrupt change points and load jump points of each PDC tooth during continuous drilling, and construct the key tooth position degradation path according to the microcrack initiation sequence, wear propagation sequence and load jump sequence. The feature extraction module is configured to extract the mean value of energy input density fluctuation, the discrete amount of impact frequency time interval, and the continuous offset length of cutting trajectory based on the changing trend of the key tooth position degradation path, forming a life characterization feature set. The life prediction module is configured to divide the drill bit life into a stable wear stage, an accelerated decay stage, and a critical failure stage based on the life characterization feature group, and use the abrupt change point of the characterization feature at the time of life stage transition as the basis for life prediction to obtain the predicted value of drill bit life.

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