A method, system, device and storage medium for establishing a deep drilling sticking early warning

Abstract

The application discloses a deep pipe sticking early warning method, system, device and storage medium, and belongs to the deep pipe sticking early warning field.The method comprises the following steps: collecting the standpipe pressure data in the deep drilling process in real time; processing and analyzing the standpipe pressure data, and identifying the pressure abnormal state; identifying the waveform change characteristics based on the standpipe pressure data after the pressure abnormality, and determining the corresponding risk change trend; generating a quantitative pipe sticking risk index according to the risk change trend, and triggering the early warning of the corresponding level based on the pipe sticking risk index.The application converts the standpipe pressure sine / cosine wave change into the mathematical parameters and the risk index which can be accurately calculated by constructing a quantitative calculation model, effectively avoids the defects of the traditional technology disturbed by various factors, significantly improves the accuracy of the early signal identification of the deep pipe sticking, and greatly reduces the false positive rate and the false negative rate.

Description

Technical Field

[0001] This application belongs to the field of deep stuck drill bit early warning, and specifically relates to a method, system, device and storage medium for establishing a deep stuck drill bit early warning system. Background Technology

[0002] In deep oil and gas drilling operations, stuck pipe is a frequent and serious downhole accident. The complex deep drilling environment, with its variable formation pressure systems, diverse rock mechanical properties, and high difficulty in wellbore trajectory control, makes it highly susceptible to sticking between the drill string and the wellbore. Once stuck pipe occurs, it not only prolongs the drilling cycle and significantly increases construction costs, but can also lead to serious consequences such as wellbore abandonment, equipment damage, and even threaten the lives of drilling personnel.

[0003] Currently, the commonly used stuck pipe early warning technology in the industry mainly relies on traditional integrated logging technology, which judges the risk of stuck pipe by monitoring changes in conventional drilling parameters such as drilling pressure, torque, and rotational speed. However, these traditional technologies have obvious limitations: on the one hand, conventional drilling parameters are affected by various factors, such as changes in drilling fluid properties and drill string assembly adjustments, resulting in low accuracy of stuck pipe early warning and a high risk of false alarms or missed alarms; on the other hand, traditional technologies lack quantitative calculation models to support them, and their ability to capture early stuck pipe signals in deep drilling is insufficient. They often only issue warnings when the risk of stuck pipe has become quite serious, leaving very limited time for drilling to react and making it difficult to effectively prevent stuck pipe accidents.

[0004] Therefore, there is an urgent need for a stuck drilling early warning method that can accurately capture early signals of deep drilling, has a scientific quantitative calculation model, strong anti-interference ability, and high timeliness of early warning, in order to solve the shortcomings of existing technologies and ensure the safe and efficient conduct of deep drilling operations. Summary of the Invention

[0005] To address the above problems, this application provides a method for establishing a deep stuck drill bit early warning system, the method comprising: Real-time acquisition of riser pressure data during deep drilling; The riser pressure data is processed and analyzed to identify abnormal pressure conditions; Based on riser pressure data after pressure anomalies, waveform change characteristics are identified, and corresponding risk change trends are determined. Based on the aforementioned risk change trend, a quantitative stuck drill risk index is generated, and a corresponding level of early warning is triggered based on the stuck drill risk index. The stuck drill risk index is updated based on continuously collected riser pressure data, and the warning level is dynamically adjusted until the warning is lifted or emergency response is triggered.

[0006] According to some embodiments of this disclosure, before the real-time acquisition of riser pressure data during deep drilling, the method further includes: Establish an early warning model; Based on historical data of drilled wells within the target area, the parameters in the early warning model are determined; wherein, the parameters in the early warning model include a smoothness threshold, an anomaly determination threshold, a first amplitude stability threshold, a first risk threshold, a second risk threshold, an early warning cancellation threshold, and an emergency shutdown threshold.

[0007] According to some embodiments of this disclosure, the above-described early warning method is executed based on the established early warning model and the determined parameters.

[0008] According to some embodiments of this disclosure, the riser pressure data is processed and analyzed to identify abnormal pressure states, including: The riser pressure data is preprocessed to obtain effective pressure data; Based on the effective pressure data, determine whether the riser pressure is abnormal.

[0009] According to some embodiments of this disclosure, the riser pressure data is preprocessed to obtain effective pressure data, including: Kalman filtering is used to preprocess the riser pressure data and the smoothness of the filtered data is determined; when the smoothness is greater than or equal to the smoothness threshold, it is determined to be valid pressure data.

[0010] According to some embodiments of this disclosure, determining whether the riser pressure is abnormal based on the effective pressure data includes: Based on the effective pressure data during the continuous period before the pressure anomaly occurred, determine the riser pressure baseline value. The real-time effective pressure data is compared with the riser pressure reference value; When the results of multiple consecutive comparisons exceed the anomaly detection threshold, the riser pressure is determined to be abnormal.

[0011] According to some embodiments of this disclosure, based on riser pressure data after a pressure anomaly, waveform change characteristics are identified, and corresponding risk change trends are determined, including: Waveform fitting is performed on the effective pressure data after the anomaly to construct an effective basic waveform model, and waveform parameters are extracted; wherein, the waveform parameters include amplitude and waveform period; Based on the amplitude change trend of multiple consecutive waveform cycles, a corresponding amplitude change quantification model is matched; wherein, the amplitude change quantification model includes an ideal no-intervention model, a positive change model, and a danger aggravation model.

[0012] According to some embodiments of this disclosure, waveform fitting is performed on the effective pressure data after an anomaly to construct an effective basic waveform model, and waveform parameters are extracted, including: Waveform fitting is performed on the effective pressure data after the anomaly to construct a basic waveform model; Determine the coefficient of determination based on the waveform fitting results; When the coefficient of determination is greater than or equal to the coefficient of determination threshold, the basic waveform model is determined to be a valid basic waveform model, and the waveform parameters are extracted.

[0013] According to some embodiments of this disclosure, based on the amplitude change trend of multiple consecutive waveform periods, a corresponding amplitude change quantization model is matched, including: When the absolute value of the amplitude difference between adjacent cycles is less than or equal to the first amplitude stability threshold, it is determined to be an ideal no-intervention model; When the amplitude decreases exponentially with the period number and the decay coefficient is greater than 0, it is determined to be a positive change model. When the amplitude increases linearly with the period number and the growth coefficient is greater than 0, it is determined to be a dangerous aggravation model.

[0014] According to some embodiments of this disclosure, a quantified stuck drill risk index is generated based on the risk change trend, and a corresponding level of early warning is triggered based on the stuck drill risk index, including: Based on the matched amplitude change quantization model and the waveform parameters, the stuck drill risk index is obtained; Based on the stuck drill risk index, a stuck drill warning signal of the corresponding level is triggered, and the corresponding warning strategy is executed.

[0015] According to some embodiments of this disclosure, a stuck drill risk index is obtained based on the matched amplitude change quantization model and the waveform parameters, including: The basic risk index is determined based on the matched amplitude change quantification model; Determine whether the currently matched amplitude change quantization model is a danger aggravation model; If so, the pressure mutation correction coefficient is determined based on the magnitude of the pressure mutation, and the basic risk index is corrected using the pressure mutation correction coefficient to obtain the stuck drill risk index. If not, then the aforementioned basic risk index will be used as the stuck drill risk index.

[0016] According to some embodiments of this disclosure, based on the stuck drill risk index, a corresponding level of stuck drill warning signal is triggered, including: When the ideal no-intervention model is matched and the stuck drill risk index is greater than or equal to the first risk threshold, a level one warning is triggered. When the model matches a positive change and the stuck drill risk index is less than the second risk threshold, a level two warning is triggered. A Level 3 alert is triggered when any of the following conditions are met: The matching risk aggravation model is used, and the stuck drill risk index is ≥ the second risk threshold; where the second risk threshold is > the first risk threshold. Or, a stress mutation event may occur.

[0017] According to some embodiments of this disclosure, the warning level is dynamically adjusted, including: Based on the real-time updated stuck drill risk index, the matched amplitude change quantification model, and whether there is a sudden change in riser pressure, the triggered warning level is upgraded, downgraded, or canceled according to preset rules.

[0018] According to some embodiments of this disclosure, the preset rules include warning escalation rules, warning downgrade rules, and warning cancellation rules; The warning escalation rule is that when the stuck drill risk index reaches a higher level of risk threshold and / or the riser pressure changes abruptly, the current warning level will be upgraded to the corresponding higher level. The warning downgrade rule is that when the stuck drill risk index continues to be lower than the risk threshold corresponding to the current warning level, the current warning level will be downgraded step by step. The warning cancellation rule is that when the stuck drill risk index is lower than the warning cancellation threshold and the riser pressure remains stable for a preset time, all warnings are cancelled.

[0019] According to some embodiments of this disclosure, the warning level is dynamically adjusted until the warning is lifted or an emergency response is triggered, including: If the stuck drill risk index remains above the emergency shutdown threshold after a Level 3 warning is triggered, an emergency shutdown command will be issued. When any level of warning is triggered, if the stuck drill risk index is less than the warning cancellation threshold and the riser pressure remains stable for a preset duration, the warning will be cancelled.

[0020] This application also provides a system for establishing a deep stuck drill bit early warning system, the system comprising: The real-time acquisition module is used to acquire riser pressure data in real time during the deep drilling process; The identification module is used to process and analyze the riser pressure data and identify abnormal pressure conditions. The determination module is used to identify waveform change characteristics and determine the corresponding risk change trend based on riser pressure data after pressure anomalies. The early warning module is used to generate a quantified stuck drill risk index based on the risk change trend, and trigger an early warning of the corresponding level based on the stuck drill risk index. The adjustment module is used to update the stuck drill risk index based on continuously collected riser pressure data and dynamically adjust the warning level until the warning is lifted or emergency response is triggered.

[0021] This application also provides an electronic device, including: Processor and memory; The processor invokes the computer program stored in the memory to execute the method for establishing a deep stuck drill bit early warning system.

[0022] This application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, enables the processor to perform the method for establishing a deep stuck drill bit early warning system.

[0023] Compared with the prior art, this application has the following advantages: This invention constructs a quantitative calculation model to transform the sinusoidal / cosine wave variation of riser pressure into precisely calculable mathematical parameters and risk indices. This effectively avoids the shortcomings of traditional technologies, which are susceptible to interference from various factors, significantly improving the accuracy of early signal identification in deep drilling rigs and drastically reducing false alarm and missed alarm rates. With targeted early warning models and judgment criteria, timely warnings can be issued at the nascent stage of drilling rig risk. In particular, real-time monitoring of dangerous trends through growth coefficients and risk indices allows sufficient time for drilling operations, significantly improving the timeliness and scientific rigor of early warnings. Simultaneously, drilling operations can be quantified through risk assessment. The risk index provides a clear picture of the risk level, allowing for early prediction of wellbore instability factors and the implementation of targeted measures. This effectively reduces accidents such as stuck drill pipe, ensures the continuity and smoothness of the drilling process, shortens the construction cycle, reduces costs, and provides strong protection for the safety of construction personnel and equipment. Furthermore, this quantitative calculation model can be adapted to different regions and well types based on geological and drilling conditions by adjusting threshold parameters. The data acquisition equipment is conventional, the calculation algorithm is simple and efficient, and it is easy to upgrade existing equipment. It has a wide range of applications and strong practicality, laying a solid technical foundation for the efficient and safe exploitation of deep oil and gas resources.

[0024] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 A diagram illustrating a method for establishing a deep stuck drill bit early warning system according to an embodiment of this application is shown. Figure 2 A schematic diagram showing the pressure variation trend of deep drilling riser according to an embodiment of this application is shown; Figure 3 A schematic diagram of an ideal, intervention-free model according to an embodiment of this application is shown; Figure 4 A schematic diagram of a positive change model according to an embodiment of this application is shown; Figure 5 A schematic diagram of a danger aggravation model according to an embodiment of this application is shown; Figure 6 A diagram illustrating the establishment of a deep stuck drill bit early warning system according to an embodiment of this application is shown; Figure 7 An electronic device diagram according to an embodiment of this application is shown. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0028] The purpose of this application is to overcome the shortcomings of existing deep stuck drill early warning technologies, such as low early warning accuracy, weak early signal capture capability, poor anti-interference, and lack of quantitative support, and to provide a method, system, device, and storage medium for establishing deep stuck drill early warning.

[0029] By analyzing the sinusoidal and cosine wave variation patterns of riser pressure during deep drilling, a scientific and quantitative calculation model and early warning model are constructed to achieve early identification, accurate quantitative judgment, and timely warning of stuck pipe risks. This allows sufficient time for drilling to take targeted measures to avoid stuck pipe accidents, thereby improving the safety and continuity of deep drilling operations, shortening the construction cycle, and reducing construction costs.

[0030] like Figure 1 As shown, this application discloses a method for establishing a deep stuck drill bit early warning system, the method comprising: Real-time acquisition of riser pressure data during deep drilling; The riser pressure data is processed and analyzed to identify abnormal pressure conditions; Based on riser pressure data after pressure anomalies, waveform change characteristics are identified, and corresponding risk change trends are determined. Based on the aforementioned risk change trend, a quantitative stuck drill risk index is generated, and a corresponding level of early warning is triggered based on the stuck drill risk index. The stuck drill risk index is updated based on continuously collected riser pressure data, and the warning level is dynamically adjusted until the warning is lifted or emergency response is triggered.

[0031] Specifically, before acquiring the riser pressure data in real time during deep drilling, the method further includes: Establish an early warning model; Based on historical data of drilled wells within the target area, the parameters in the early warning model are determined; wherein, the parameters in the early warning model include a smoothness threshold, an anomaly determination threshold, a first amplitude stability threshold, a first risk threshold, a second risk threshold, an early warning cancellation threshold, and an emergency shutdown threshold.

[0032] Specifically, based on the established early warning model and the determined parameters, the aforementioned early warning method is executed.

[0033] The early warning model in this method is a comprehensive quantitative analysis system consisting of data preprocessing, waveform recognition, trend quantification, risk calculation, and hierarchical early warning rules.

[0034] Specifically, the riser pressure data is processed and analyzed to identify abnormal pressure states, including: The riser pressure data is preprocessed to obtain effective pressure data; Based on the effective pressure data, determine whether the riser pressure is abnormal.

[0035] Specifically, the riser pressure data is preprocessed to obtain effective pressure data, including: Kalman filtering is used to preprocess the riser pressure data and the smoothness of the filtered data is determined; when the smoothness is greater than or equal to the smoothness threshold, it is determined to be valid pressure data.

[0036] Specifically, based on the effective pressure data, determining whether the riser pressure is abnormal includes: Based on the effective pressure data during the continuous period before the pressure anomaly occurred, determine the riser pressure baseline value. The real-time effective pressure data is compared with the riser pressure reference value; When the results of multiple consecutive comparisons exceed the anomaly detection threshold, the riser pressure is determined to be abnormal.

[0037] Specifically, based on riser pressure data following pressure anomalies, waveform change characteristics are identified, and corresponding risk change trends are determined, including: Waveform fitting is performed on the effective pressure data after the anomaly to construct an effective basic waveform model, and waveform parameters are extracted; wherein, the waveform parameters include amplitude and waveform period; Based on the amplitude change trend of multiple consecutive waveform cycles, a corresponding amplitude change quantification model is matched; wherein, the amplitude change quantification model includes an ideal no-intervention model, a positive change model, and a danger aggravation model.

[0038] Specifically, waveform fitting is performed on the effective pressure data after the anomaly to construct an effective basic waveform model, and waveform parameters are extracted, including: Waveform fitting is performed on the effective pressure data after the anomaly to construct a basic waveform model; Determine the coefficient of determination based on the waveform fitting results; When the coefficient of determination is greater than or equal to the coefficient of determination threshold, the basic waveform model is determined to be a valid basic waveform model, and the waveform parameters are extracted.

[0039] Specifically, based on the amplitude variation trend of multiple consecutive waveform periods, a corresponding amplitude variation quantization model is matched, including: When the absolute value of the amplitude difference between adjacent cycles is less than or equal to the first amplitude stability threshold, it is determined to be an ideal no-intervention model; When the amplitude decreases exponentially with the period number and the decay coefficient is greater than 0, it is determined to be a positive change model. When the amplitude increases linearly with the period number and the growth coefficient is greater than 0, it is determined to be a dangerous aggravation model.

[0040] Specifically, based on the aforementioned risk change trend, a quantified stuck drill risk index is generated, and a corresponding level of early warning is triggered based on the stuck drill risk index, including: Based on the matched amplitude change quantization model and the waveform parameters, the stuck drill risk index is obtained; Based on the stuck drill risk index, a stuck drill warning signal of the corresponding level is triggered, and the corresponding warning strategy is executed.

[0041] Specifically, based on the matched amplitude change quantization model and the waveform parameters, a stuck drill risk index is obtained, including: The basic risk index is determined based on the matched amplitude change quantification model; Determine whether the currently matched amplitude change quantization model is a danger aggravation model; If so, the pressure mutation correction coefficient is determined based on the magnitude of the pressure mutation, and the basic risk index is corrected using the pressure mutation correction coefficient to obtain the stuck drill risk index. If not, then the aforementioned basic risk index will be used as the stuck drill risk index.

[0042] Specifically, based on the stuck drill risk index, a corresponding level of stuck drill warning signal is triggered, including: When the ideal no-intervention model is matched and the stuck drill risk index is greater than or equal to the first risk threshold, a level one warning is triggered. When the model matches a positive change and the stuck drill risk index is less than the second risk threshold, a level two warning is triggered. A Level 3 alert is triggered when any of the following conditions are met: The matching risk aggravation model is used, and the stuck drill risk index is ≥ the second risk threshold; where the second risk threshold is > the first risk threshold. Or, a stress mutation event may occur.

[0043] Specifically, the warning levels will be dynamically adjusted, including: Based on the real-time updated stuck drill risk index, the matched amplitude change quantification model, and whether there is a sudden change in riser pressure, the triggered warning level is upgraded, downgraded, or canceled according to preset rules.

[0044] Specifically, the preset rules include warning escalation rules, warning downgrade rules, and warning cancellation rules; The warning escalation rule is that when the stuck drill risk index reaches a higher level of risk threshold and / or the riser pressure changes abruptly, the current warning level will be upgraded to the corresponding higher level. The warning downgrade rule is that when the stuck drill risk index continues to be lower than the risk threshold corresponding to the current warning level, the current warning level will be downgraded step by step. The warning cancellation rule is that when the stuck drill risk index is lower than the warning cancellation threshold and the riser pressure remains stable for a preset time, all warnings are cancelled.

[0045] Specifically, the warning level will be dynamically adjusted until the warning is lifted or an emergency response is triggered, including: If the stuck drill risk index remains above the emergency shutdown threshold after a Level 3 warning is triggered, an emergency shutdown command will be issued. When any level of warning is triggered, if the stuck drill risk index is less than the warning cancellation threshold and the riser pressure remains stable for a preset duration, the warning will be cancelled.

[0046] The core of this application is to construct a full-process quantitative calculation system and a graded early warning model based on the sinusoidal / cosine wave abnormal change characteristics of riser pressure in deep drilling, so as to realize early identification, accurate quantification and timely warning of stuck pipe risk. The following are the steps of deepening the technical principle, constructing the quantitative calculation model in all dimensions, refining the graded early warning model and judgment criteria, and implementing the early warning in the whole process.

[0047] I. Deepening the understanding of technical principles: In deep drilling operations, the mechanical equilibrium state between the drill string and the wellbore is directly reflected in the stability of the riser pressure. Under normal operating conditions: the wellbore is stable, the drilling fluid circulates smoothly, and the riser pressure is maintained at the reference value. Nearby, pressure fluctuation range after pump stop / start There is no periodic waveform change; Abnormal precursor conditions: When the wellbore experiences problems such as blockage, narrowing, drilling fluid loss, or drill string wear, the mechanical balance between the drill string and the wellbore is broken, and the drilling fluid circulation resistance changes periodically. This causes the riser pressure to deviate from the reference value, forming a continuous and identifiable sine / cosine wave periodic change. The amplitude and period of the waveform change dynamically with the degree of stuck pipe risk. Critical stuck pipe condition: When the amplitude of the sine / cosine wave continues to increase to the critical value, the riser pressure will exceed the fluctuation range and remain at a high constant value. At this time, the drill string and the well wall have formed a jam, which will directly lead to a stuck pipe accident.

[0048] Core technical features: The sinusoidal / cosine wave variation of riser pressure is the only early quantifiable precursor signal of deep stuck drill bit. The dynamic variation law of its waveform parameters (amplitude, period, initial phase) is strongly correlated with the stuck drill bit risk level, and the risk can be quantitatively characterized through mathematical modeling.

[0049] II. Comprehensive Construction of Quantitative Calculation Model: This section, based on basic waveform modeling, supplements data preprocessing calculation formulas, waveform identification validity judgment formulas, risk index correction formulas, etc., to construct a complete calculation system from raw data to risk quantification. All parameters have clearly defined physical meanings, calculation methods, and value boundaries to ensure the scientific nature and uniqueness of the model.

[0050] (a) Data preprocessing calculations: The raw data acquired by the riser pressure sensor is processed by Kalman filtering to remove interference signals such as drilling fluid pulses, sensor noise, and drill string vibration, and to extract the effective pressure data. The filtering iteration formula is: State prediction: ; Filter gain: ; Error update: ; in: for Predicted pressure at any time (MPa); for Optimal pressure filter value at any given time (MPa); for Original pressure data at any given time (MPa); This represents the Kalman filter gain, with a value ranging from 0.1 to 0.3. for Time-major filtering error covariance; for -1 time point filtering error covariance; The process noise covariance is taken as 0.001~0.005; To measure the noise covariance, a range of 0.002 to 0.006 is used.

[0051] Validity determination after preprocessing: smoothness of the filtered data The data is valid at that time. ,in This is the average value of the filtered data. This is the average of the original data. For the first abnormality The effective filtered pressure value (MPa) collected each time.

[0052] (II) Calculation of benchmark values ​​and pressure anomaly judgment: Riser pressure reference value Calculate the average value of the effective filtered data from the 10 consecutive minutes prior to the occurrence of the pressure anomaly, at the following sampling frequency. Hz, therefore the total number of samplings The calculation formula is: ; in, For the first abnormality The effective filtered pressure value (MPa) collected each time.

[0053] Pressure anomaly detection: When continuous Next (in this embodiment, take) The absolute value of the difference between the collected effective filter pressure value and the baseline value is greater than the anomaly detection threshold. When the pressure is 0.1 MPa, it is determined to be an abnormal pressure. The waveform recognition program is then activated, and the determination formula is as follows: .

[0054] (III) Basic Waveform Mathematical Modeling and Parameter Calculation: Sine / cosine wave fitting is performed on the effective pressure data after the anomaly to construct a basic waveform model. A goodness-of-fit formula for waveform fitting is added to ensure the model's effectiveness in fitting actual pressure changes. Waveforms that do not meet the criteria are re-identified and analyzed.

[0055] 1. Basic waveform expression: Sine wave model: ; Cosine wave model: ; The physical meaning, units, and core calculation formulas of each parameter are shown in Table 1. Table 1

[0056] 2. Waveform fit goodness of fit determination: Using the coefficient of determination To determine the validity of waveform fitting, only when... If the fitted sine / cosine wave model is valid, then waveform identification is performed again. The calculation formula is as follows: ; in, Calculated based on the basic waveform model Constant pressure value; This represents the average effective filter pressure within a single cycle after the anomaly. For the first abnormality The effective filtered pressure value (MPa) collected each time.

[0057] like Figure 2 As shown in the figure, the horizontal axis represents drilling depth (unit: m), and the vertical axis represents standpipe pressure (unit: MPa). The figure clearly shows the complete process from the emergence of abnormal standpipe pressure at a depth of 5271m, exhibiting a sine / cosine waveform change, maintaining a high pressure at 5281m, and finally experiencing a stuck pipe accident at 5286m. This visually demonstrates the correlation between standpipe pressure waveform changes and stuck pipe accidents. This figure proves that the sine / cosine waveform change of standpipe pressure is an effective precursor signal for deep stuck pipe.

[0058] (iv) Amplitude variation quantification model: To address the three dynamic trends of riser pressure waveform after pressure anomalies, three amplitude quantification models are constructed: ideal without intervention, positive change, and increased danger. The model matching judgment threshold and coefficient validity calculation are supplemented to ensure the accuracy of model matching and avoid mismatch.

[0059] 1. Model 1: Ideal Uninterrupted Model (Amplitude Stable): Judgment criterion: The absolute value of the amplitude difference between adjacent periods is less than or equal to the amplitude stability threshold. (Values ​​range from 0.05 to 0.1 MPa, determined by statistical analysis of historical drilling data in the region), the formula is: ; Amplitude validity determination: Amplitude variation coefficient over three consecutive periods , , The amplitude is the average of three cycles, ensuring that the amplitude fluctuates steadily rather than changing randomly; in, For the first Amplitude value per cycle (MPa); For the first Amplitude value (MPa) per cycle. ; This is the amplitude stability threshold.

[0060] like Figure 3 As shown in the figure, the horizontal axis represents time (unit: t), and the vertical axis represents riser pressure (unit: MPa). The figure illustrates the trend of the riser pressure sine / cosine waveform maintaining a stable equilibrium state after the anomaly occurs, and the baseline value is marked. ,amplitude and cycle , along with the corresponding mathematical expression.

[0061] 2. Model 2: Positive Change Model (Exponential Decrease in Amplitude): Judgment criteria: The amplitude decreases exponentially with the period number, and the decay coefficient is... The amplitudes of adjacent periods satisfy The quantization model is as follows: ; Attenuation coefficient Calculation: Take continuous One cycle ( The amplitude data is calculated to ensure the statistical validity of the coefficients. The formula is as follows: ; Attenuation validity assessment: Correlation coefficient of attenuation fitting This ensures that the amplitude exhibits a significant exponential decay trend; in, The amplitude value (MPa) for the first cycle; The attenuation coefficient (1 / period) reflects the amplitude attenuation rate. The larger the value, the faster the decay, and the more significant the reduction in the risk of the drill getting stuck.

[0062] like Figure 4 As shown in the figure, the horizontal axis represents time (unit: t), and the vertical axis represents riser pressure (unit: MPa). The figure illustrates the trend of the riser pressure sine / cosine waveform amplitude gradually decreasing after the anomaly occurs, and the amplitude values ​​and attenuation coefficients for different periods are marked. and risk index The variation curve, along with the amplitude decay quantization model expression.

[0063] 3. Model 3: Danger Escalation Model (Linear Amplitude Growth): Judgment criteria: The amplitude increases linearly with the period number, and the growth coefficient is... The amplitudes of adjacent periods satisfy The quantization model is as follows: ; growth coefficient Calculation: Take continuous One cycle ( The amplitude data of ) is calculated using the following formula: ; Determining the effectiveness of growth: Correlation coefficient of growth fit This ensures that the amplitude exhibits a significant linear growth trend; in, The growth factor (MPa / period) reflects the rate of increase in amplitude. The larger the diameter, the faster the risk of the drill getting stuck increases.

[0064] like Figure 5 As shown in the figure, the horizontal axis represents time (unit: t), and the vertical axis represents riser pressure (unit: MPa). The figure illustrates the trend of gradually increasing amplitude of the sine / cosine waveform of riser pressure after the anomaly occurs, and the amplitude values ​​and growth coefficients for different periods are marked. and risk index The variation curve, along with the quantitative model expression for amplitude growth.

[0065] (v) Calculation of the risk index for stuck drill bit: Constructing a basic risk index With the risk index of stuck drill To supplement the pressure mutation correction coefficient, and to solve the problem of missed detection of stuck drill risk caused by non-periodic pressure mutations. The risk index, used for the final early warning judgment, ranges from 0 to 1. The higher the value, the higher the risk of stuck drill. All thresholds are determined by statistical analysis of historical stuck drill accident data in the region to ensure the regional adaptability of the index.

[0066] 1. Basic Risk Index calculate: Based on the matched amplitude change model, the basic risk index and core threshold are calculated respectively: The maximum permissible amplitude threshold (MPa) is 80% of the maximum amplitude value before the occurrence of a stuck drilling accident in the region. Risk growth coefficient threshold (MPa / cycle) It was determined to be high risk at that time; : Maximum attenuation coefficient (1 / cycle), taken as the maximum attenuation coefficient value among the successful cases of handling stuck drill bit hazards in the region; : No. Amplitude value per cycle; Attenuation coefficient; Growth coefficient;

[0067] 2. Drilling Risk Index calculate: To address the extreme case in Model 3 where a pressure mutation occurs before a full cycle, a pressure mutation correction coefficient is introduced. ( The basic risk index is adjusted to address the issue of insufficient risk quantification in extreme situations. The formula is as follows: ; Among them, the pressure sudden change correction coefficient The calculation is as follows: ; In the formula: R is the basic risk index; 'This is the risk index for stuck drill bits;' This represents the maximum effective filter pressure (MPa) of the previous cycle. The pressure surge threshold (MPa) is 0.2~0.3 MPa. The effective filter pressure value (MPa) at the abrupt change moment within the non-periodic period, and satisfying the following conditions: ; This is a pressure surge correction factor, ranging from 1 to 2. The larger the pressure surge amplitude, the greater the correction factor. The larger the value, the higher the adjusted risk index.

[0068] Model 1 / 2 Correction Notes: When there is no stress mutation in Models 1 and 2, , If a sudden change in pressure occurs in Model 1 or 2, switch directly to Model 3 to calculate the risk index.

[0069] III. Refinement of the Tiered Early Warning Model and Judgment Criteria: Based on the revised stuck drill risk index Based on the characteristics of the amplitude change model, a first-level, second-level, and third-level early warning model is constructed. The judgment conditions for upgrading / downgrading the early warning level and the threshold range are supplemented. The triggering conditions, early warning strategies, and monitoring frequencies corresponding to each early warning level are clarified to ensure the timeliness and operability of the early warning. All judgment conditions are determined by multiple parameters to avoid false early warnings caused by a single parameter.

[0070] (1) Definition of core threshold for early warning level: The core early warning thresholds set in this application have all been verified by regional historical data and can be fine-tuned according to different regions and well types. The threshold ranges are as follows: Level 1 warning threshold: ; Level 2 warning threshold: (Exclusive to Model 2); Level 3 warning threshold: (Model 3) or non-periodic stress mutation ( ); Warning cancellation threshold: And the pressure stabilization time is ≥30 minutes; Emergency shutdown threshold: (Model 3 continues to trigger).

[0071] (2) Judgment conditions and early warning strategies for the graded early warning model: 1. Level 1 Warning (Model 1: Ideal No Intervention): Joint judgment conditions: ① Amplitude variation matching model 1, satisfying And amplitude variation coefficient ; ② Drilling risk index ; ③ No stress mutation ( ).

[0072] Early warning strategy: Immediately issue a Level 1 warning signal (audio-visual warning + system pop-up window) to remind the drilling team to pay attention to the wellbore status; The wellbore monitoring enhancement program was activated, increasing the riser pressure data acquisition frequency to 2Hz, updating pressure data and amplitude every 5 minutes. and the risk index of stuck diamonds ; It is recommended to check the drilling fluid properties and drill string assembly status during drilling, suspend drill string lowering operations, and maintain low-speed drilling fluid circulation.

[0073] Downgrade / upgrade conditions: Relegation: If If the status remains stable for ≥20 minutes, it will be downgraded to Level 2 monitoring (no early warning). Upgrade: If a sudden pressure change occurs or The alert level has been immediately upgraded to Level 3.

[0074] 2. Level II Early Warning (Model 2: Positive Changes): Joint judgment conditions: ① Amplitude variation matching model 2, which satisfies , Attenuation fitting correlation coefficient ; ② Drilling risk index ; ③ No stress mutation ( ).

[0075] Early warning strategy: Issue a Level 2 warning signal (system pop-up + SMS notification) and continuously monitor the attenuation coefficient. ,amplitude and the risk index of stuck diamonds ; The riser pressure data acquisition frequency is maintained at 1Hz, and the early warning status is updated every 10 minutes. It is recommended to continuously optimize drilling fluid performance, appropriately increase drilling fluid circulation rate, and track changes in wellbore trajectory.

[0076] Downgrade / upgrade conditions: Relegation: If Continuously increasing If the pressure remains stable for ≥30 minutes, the warning will be lifted; Upgrade: If Decrease (the decay rate slows down) If a sudden change in pressure occurs, the alert level will be immediately upgraded to Level 1 / Level 3.

[0077] 3. Level 3 Warning (Model 3: Increased Danger, Highest Level): Joint determination conditions (meeting any one of them is sufficient): ① Amplitude variation matching model 3, satisfies , Growth Fit Correlation Coefficient and ; ② Before Model 3 has completed one cycle, a sudden pressure change occurs, satisfying the condition. ; ③ After a stress mutation occurs in Model 1 / 2, switching to Model 3 is necessary. .

[0078] Early warning strategy: Immediately issue a Level 3 warning signal (strong audible and visual warning + dual reminder via SMS / telephone), forcibly triggering the drilling system warning pop-up window; Drilling operations must be immediately suspended, and emergency measures must be taken promptly (adjusting drilling fluid density / viscosity, circulating and cleaning the wellbore, raising the drill string to a safe section, etc.). The riser pressure data acquisition frequency has been increased to 5Hz, updating pressure data and growth coefficients every minute. ,amplitude and the risk index of stuck diamonds ; The emergency response procedure for stuck drill bit was initiated, and professional technicians were dispatched to the site to analyze the wellbore condition.

[0079] Shutdown / Release Conditions: Emergency Stop: If Model 3 continues to trigger and Immediately initiate the emergency shutdown procedure for drilling equipment to prevent stuck drill bit accidents; Solution: If, after taking corrective measures, the amplitude switches to Model 2 and If the pressure remains stable for ≥30 minutes, the warning is lifted and drilling operations are resumed (low-speed exploration).

[0080] (3) Rules for dynamic adjustment of early warning levels: A closed-loop adjustment mechanism for early warning levels is established. Based on real-time changes in pressure data, waveform parameters, and risk indices, the mechanism automatically downgrades, upgrades, and cancels early warning levels without manual intervention, ensuring the dynamic and timely nature of early warnings. The core rules are as follows: A high-level warning can be downgraded to a low-level warning, but a low-level warning cannot be upgraded to a high-level warning; a gradual transition is required (except for sudden changes in pressure). All warning levels must meet certain conditions to be lifted. + Pressure stability ≥ 30 minutes (dual condition); A sudden change in pressure becomes the trigger condition for a level 3 alert. If any model experiences a sudden change in pressure, it will be directly upgraded to a level 3 alert.

[0081] IV. Steps for Implementing Early Warning: This section breaks down the early warning implementation steps into eight core stages, supplementing each stage with operational standards, effectiveness criteria, and anomaly handling measures. This forms a closed-loop process from raw data collection to early warning cancellation / emergency shutdown, ensuring the feasibility of the technical solution. Each stage is interconnected, and if the previous stage fails to meet the effectiveness criteria, it is re-executed to avoid early warning failure due to errors in a single stage.

[0082] Step 1: Real-time data acquisition: Raw riser pressure data is collected in real time during deep drilling using a high-precision riser pressure sensor (measurement accuracy ±0.01MPa). The basic acquisition frequency is... When drilling reaches a high-risk section where the drill string is stuck (determined by regional geological data), the acquisition frequency is increased to 2Hz in advance, and the acquired data is transmitted to the drilling monitoring system in real time. The data is stored in a two-dimensional dataset of "time-pressure value".

[0083] Step 2: Data preprocessing and validity assessment: The raw pressure data collected is subjected to Kalman filtering, and the effective pressure data after filtering is calculated according to the formula in Part (I) of this section. And calculate smoothness : like If the preprocessing is effective, proceed to step 3; like Readjust the Kalman filter gain (Increase by 0.05~0.1), perform filtering again, until... .

[0084] Step 3: Baseline Value Calculation and Pressure Anomaly Judgment: Calculate the riser pressure benchmark value in real time according to the formula for calculating the benchmark value and pressure anomaly judgment in section (II) above. The baseline value is updated every 5 minutes to ensure it matches the drilling conditions. Continuously judge the effective filter pressure value collected in 5 consecutive tests and The difference is determined according to the anomaly detection formula: If the pressure is determined to be abnormal, proceed to step 4; If the pressure is determined to be normal, return to step 1 and continue collecting data in real time.

[0085] Step 4: Waveform Recognition and Effective Model Construction: The Fast Fourier Transform (FFT) algorithm is used to perform frequency domain analysis on the effective filtered data after anomalies to identify the waveform type (sine wave / cosine wave). The amplitude is calculated by fitting the basic waveform formula from the basic waveform mathematical modeling and parameter calculation section (III) above. angular frequency Initial phase Parameters, and calculate the coefficient of determination. : like If the waveform fitting is effective, construct a real-time pressure calculation model and proceed to step 5. like Then, re-perform FFT waveform identification and expand the analysis period (increase by 1 to 2 periods) until the fit is effective.

[0086] Step 5: Amplitude variation model matching and validity verification: Collect amplitude data for ≥3 consecutive periods and calculate the amplitude variation coefficient. attenuation coefficient Growth coefficient and correlation coefficient ; According to the amplitude change model determination conditions in the amplitude change quantification model in section (IV) above, match the corresponding models (1 / 2 / 3) and verify their validity: If the model match is valid, proceed to step 6; If the model matching is invalid (e.g., there is no obvious stabilization / decline / growth trend), return to step 4 and repeat waveform identification and fitting.

[0087] Step 6: Risk Index Calculation and Early Warning Triggering: Calculate the basic risk index according to the formula in section (V) above for calculating the risk quantification index of stuck drill. If a pressure mutation occurs, calculate the pressure mutation correction factor. Obtain the risk index of stuck diamonds ; According to the judgment conditions of the hierarchical early warning model of the present invention, the corresponding level of early warning signal is triggered, the corresponding early warning strategy is executed, and the process proceeds to step 7.

[0088] Step 7: Real-time updates of warning status and dynamic adjustment of warning levels: Pressure data is continuously collected according to the monitoring frequency required for each warning level, and waveform parameters are updated in real time. Pipe jamming risk index ; Based on the dynamic adjustment rules for warning levels, real-time assessments are made to determine whether a warning level needs to be downgraded or upgraded. If the warning level changes, the warning strategy for the new level will be implemented. If the warning level remains unchanged, monitoring will continue.

[0089] Step 8: Warning lifted or emergency shutdown: If the conditions for lifting the warning are met ( (And if the pressure remains stable for ≥30 minutes), cancel all warning signals, restore the normal monitoring frequency for drilling operations, and return to step 1; If the emergency shutdown conditions are met (Model 3 continues to trigger and...) Immediately initiate the emergency shutdown procedure for drilling equipment, notify the drilling rig to take emergency measures to address the stuck drill bit hazard, and repeat steps 1-7 after the hazard is resolved to attempt to resume drilling operations.

[0090] V. Model Parameter Region Adaptation Method: To ensure that the quantitative calculation model and early warning model of this invention can be adapted to geological and drilling conditions of different regions and well types, a regionalized parameter calibration method is supplemented. The values ​​of each threshold parameter are determined through statistical analysis of historical regional data to ensure the model's universality and practicality. The calibration steps are as follows: Collect complete data on drilled wells within the target area (including riser pressure data, stuck pipe incident records, drilling operating parameters, etc.). Analyze key data such as the maximum amplitude, growth coefficient, and attenuation coefficient before the stuck drill accident, and calculate... , , ; Analyze pressure fluctuation data to determine the risk of stuck drill bit. , , Equal threshold parameters; Substitute the calibrated parameters into the quantitative calculation model of this invention, and verify the accuracy of the model by backtesting historical data. When the backtesting accuracy rate is ≥90%, the adaptation is complete. During drilling, parameters are dynamically fine-tuned based on real-time drilling conditions (fine-tuning range). This ensures that the model matches the actual working conditions.

[0091] like Figure 6 As shown, this application also provides a system for establishing a deep stuck drill bit early warning system, the system comprising: The real-time acquisition module is used to acquire riser pressure data in real time during the deep drilling process; The identification module is used to process and analyze the riser pressure data and identify abnormal pressure conditions. The determination module is used to identify waveform change characteristics and determine the corresponding risk change trend based on riser pressure data after pressure anomalies. The early warning module is used to generate a quantified stuck drill risk index based on the risk change trend, and trigger an early warning of the corresponding level based on the stuck drill risk index. The adjustment module is used to update the stuck drill risk index based on continuously collected riser pressure data and dynamically adjust the warning level until the warning is lifted or emergency response is triggered.

[0092] like Figure 7As shown, corresponding to the method for establishing a deep stuck drill bit early warning system provided above, this disclosure also provides an electronic device. Since the embodiment of this device is similar to the method embodiment described above, the description is relatively simple. For relevant details, please refer to the description in the method embodiment section above. The device described below is merely illustrative. This device may include: a processor 1, a memory 2, a communication bus (i.e., the aforementioned device bus), and a lookup engine. The processor 1 and memory 2 communicate with each other through the communication bus and communicate with external systems through a communication interface. The processor 1 can call logical instructions in the memory 2 to execute the method for establishing a deep stuck drill bit early warning system.

[0093] Furthermore, the logical instructions in the aforementioned memory 2 can be implemented as software functional units and sold or used as independent products, and can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as memory chips, USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0094] On the other hand, this disclosure also provides a processor-readable storage medium storing a computer program 3, which, when executed by a processor 1, is implemented to perform the method for establishing a deep stuck drill bit early warning provided in the above embodiments.

[0095] The processor-readable storage medium can be any available medium or data storage device that the processor 1 can access, including but not limited to magnetic memory (e.g., floppy disk, hard disk, magnetic tape, magneto-optical disk (MO)), optical memory (e.g., CD, DVD, BD, HVD), and semiconductor memory (e.g., ROM, EPROM, EEPROM, non-volatile memory (NAND FLASH), solid-state drive (SSD)).

[0096] Embodiments of this disclosure also provide a computer program product comprising a computer program that includes computer program code means stored on a computer-readable medium or carrier wave, the computer program code means being configured to cause a computer or processor to control the execution of steps of a method according to any embodiment of this disclosure.

[0097] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for establishing early warning of deep stuck drill bits, characterized in that, The method includes: Real-time acquisition of riser pressure data during deep drilling; The riser pressure data is processed and analyzed to identify abnormal pressure conditions; Based on riser pressure data following pressure anomalies, waveform change characteristics are identified, and corresponding risk change trends are determined. Specifically, waveform fitting is performed on the valid pressure data following the anomaly to construct an effective basic waveform model, and waveform parameters are extracted. These waveform parameters include amplitude and waveform period. Based on the amplitude change trends of multiple consecutive waveform periods, a corresponding amplitude change quantification model is matched. This amplitude change quantification model includes an ideal no-intervention model, a positive change model, and a risk aggravation model. Based on the risk change trend, a quantified stuck drill risk index is generated, and a corresponding level of early warning is triggered based on the stuck drill risk index; wherein, the stuck drill risk index is obtained based on the matched amplitude change quantification model and the waveform parameters; based on the stuck drill risk index, a stuck drill early warning signal of the corresponding level is triggered, and the corresponding early warning strategy is executed. The step of obtaining the stuck drill risk index based on the matched amplitude change quantization model and the waveform parameters includes: determining a basic risk index based on the matched amplitude change quantization model; determining whether the currently matched amplitude change quantization model is a risk aggravation model; if so, determining a pressure change correction coefficient based on the magnitude of the pressure change, and using the pressure change correction coefficient to correct the basic risk index to obtain the stuck drill risk index; if not, using the basic risk index as the stuck drill risk index. The stuck drill risk index is updated based on continuously collected riser pressure data, and the warning level is dynamically adjusted until the warning is lifted or emergency response is triggered.

2. The method for establishing a deep stuck drill bit early warning system according to claim 1, characterized in that, Before acquiring standpipe pressure data in real time during deep drilling, the method further includes: Establish an early warning model; Based on historical data of drilled wells within the target area, the parameters in the early warning model are determined; wherein, the parameters in the early warning model include a smoothness threshold, an anomaly determination threshold, a first amplitude stability threshold, a first risk threshold, a second risk threshold, an early warning cancellation threshold, and an emergency shutdown threshold.

3. The method for establishing a deep stuck drill bit early warning system according to claim 2, characterized in that, Based on the established early warning model and the determined parameters, the early warning method as described in claim 1 is executed.

4. The method for establishing a deep stuck drill bit early warning system according to claim 1, characterized in that, The riser pressure data is processed and analyzed to identify abnormal pressure conditions, including: The riser pressure data is preprocessed to obtain effective pressure data; Based on the effective pressure data, determine whether the riser pressure is abnormal.

5. The method for establishing a deep stuck drill bit early warning system according to claim 4, characterized in that, The riser pressure data is preprocessed to obtain effective pressure data, including: Kalman filtering is used to preprocess the riser pressure data and the smoothness of the filtered data is determined; when the smoothness is greater than or equal to the smoothness threshold, it is determined to be valid pressure data.

6. The method for establishing a deep stuck drill bit early warning system according to claim 4, characterized in that, Based on the effective pressure data, determine whether the riser pressure is abnormal, including: Based on the effective pressure data during the continuous period before the pressure anomaly occurred, determine the riser pressure baseline value. The real-time effective pressure data is compared with the riser pressure reference value. When the results of multiple consecutive comparisons exceed the anomaly detection threshold, the riser pressure is determined to be abnormal.

7. The method for establishing a deep stuck drill bit early warning system according to claim 1, characterized in that, Waveform fitting is performed on the effective pressure data after the anomaly to construct an effective basic waveform model, and waveform parameters are extracted, including: Waveform fitting is performed on the effective pressure data after the anomaly to construct a basic waveform model; Determine the coefficient of determination based on the waveform fitting results; When the coefficient of determination is greater than or equal to the coefficient of determination threshold, the basic waveform model is determined to be a valid basic waveform model, and the waveform parameters are extracted.

8. The method for establishing a deep stuck drill bit early warning system according to claim 1, characterized in that, Based on the amplitude variation trend of multiple consecutive waveform periods, a corresponding amplitude variation quantization model is matched, including: When the absolute value of the amplitude difference between adjacent cycles is less than or equal to the first amplitude stability threshold, it is determined to be an ideal no-intervention model; When the amplitude decreases exponentially with the period number and the decay coefficient is greater than 0, it is determined to be a positive change model. When the amplitude increases linearly with the period number and the growth coefficient is greater than 0, it is determined to be a dangerous aggravation model.

9. The method for establishing a deep stuck drill bit early warning system according to claim 1, characterized in that, Based on the aforementioned stuck drill risk index, a corresponding level of stuck drill warning signal is triggered, including: When the ideal no-intervention model is matched and the stuck drill risk index is greater than or equal to the first risk threshold, a level one warning is triggered. When the model matches a positive change and the stuck drill risk index is less than the second risk threshold, a level two warning is triggered. A Level 3 alert is triggered when any of the following conditions are met: The matching risk aggravation model is used, and the stuck drill risk index is ≥ the second risk threshold; where the second risk threshold is > the first risk threshold. Or, a stress mutation event may occur.

10. The method for establishing a deep stuck drill bit early warning system according to claim 1, characterized in that, Dynamically adjust the warning level, including: Based on the real-time updated stuck drill risk index, the matched amplitude change quantification model, and whether there is a sudden change in riser pressure, the triggered warning level is upgraded, downgraded, or canceled according to preset rules.

11. The method for establishing a deep stuck drill bit early warning system according to claim 10, characterized in that, The preset rules include warning escalation rules, warning downgrade rules, and warning cancellation rules; The warning escalation rule is that when the stuck drill risk index reaches a higher level of risk threshold and / or the riser pressure changes abruptly, the current warning level will be upgraded to the corresponding higher level. The warning downgrade rule is that when the stuck drill risk index continues to be lower than the risk threshold corresponding to the current warning level, the current warning level will be downgraded step by step. The warning cancellation rule is that when the stuck drill risk index is lower than the warning cancellation threshold and the riser pressure remains stable for a preset time, all warnings are cancelled.

12. The method for establishing a deep stuck drill bit early warning system according to claim 11, characterized in that, The warning level will be dynamically adjusted until the warning is lifted or an emergency response is triggered, including: If the stuck drill risk index remains above the emergency shutdown threshold after a Level 3 warning is triggered, an emergency shutdown command will be issued. When any level of warning is triggered, if the stuck drill risk index is less than the warning cancellation threshold and the riser pressure remains stable for a preset duration, the warning will be cancelled.

13. A system for establishing a deep stuck drill bit early warning system, characterized in that, The system includes: The real-time acquisition module is used to acquire riser pressure data in real time during the deep drilling process; The identification module is used to process and analyze the riser pressure data and identify abnormal pressure conditions. The determination module is used to identify waveform change characteristics and determine the corresponding risk change trend based on riser pressure data after pressure anomalies. Specifically, it performs waveform fitting on the effective pressure data after the anomaly to construct an effective basic waveform model and extract waveform parameters, including amplitude and waveform period. Based on the amplitude change trend of multiple consecutive waveform periods, it matches the corresponding amplitude change quantification model, which includes an ideal no-intervention model, a positive change model, and a risk aggravation model. A trigger warning module is used to generate a quantified stuck drill risk index based on the risk change trend, and trigger a warning of the corresponding level based on the stuck drill risk index; wherein, the stuck drill risk index is obtained based on the matched amplitude change quantification model and the waveform parameters; a stuck drill warning signal of the corresponding level is triggered based on the stuck drill risk index, and a corresponding warning strategy is executed; the step of obtaining the stuck drill risk index based on the matched amplitude change quantification model and the waveform parameters includes: determining a basic risk index based on the matched amplitude change quantification model; determining whether the currently matched amplitude change quantification model is a danger aggravation model; if so, determining a pressure change correction coefficient based on the amplitude of the pressure change, and using the pressure change correction coefficient to correct the basic risk index to obtain the stuck drill risk index; if not, using the basic risk index as the stuck drill risk index; The adjustment module is used to update the stuck drill risk index based on continuously collected riser pressure data and dynamically adjust the warning level until the warning is lifted or emergency response is triggered.

14. An electronic device, characterized in that, include: Processor and memory; The processor invokes the computer program stored in the memory to execute the method for establishing a deep stuck drill bit early warning as described in any one of claims 1 to 12.

15. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, enables the processor to perform the method for establishing a deep stuck drill bit early warning as described in any one of claims 1 to 12.

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