An intelligent decision-making system for dynamic running depth of deep hole multi-stage casing

Abstract

The present invention relates to the technical field of deep hole casing management, and in particular to an intelligent decision-making system for the dynamic running depth of deep hole multi-stage casing, comprising a casing running management center, a scheme feasibility unit, a multi-coupling model unit, a running combination unit, a real-time safety unit, a working condition verification unit, and an adjustment response unit; the present invention preliminarily analyzes the running scheme from the perspective of the safety of the running scheme, preliminarily divides the running schemes of each stage of casing into feasible schemes and infeasible schemes and stores them, and simultaneously analyzes from the perspective of multi-data processing to obtain a multi-physical field coupling model, and analyzes the feasibility schemes of each stage of casing in an information progressive manner, and finally combines the obtained preferred schemes to obtain a multi-stage casing running scheme, further supervises and analyzes the actual running process to improve the running safety and reliability of the target casing, and simultaneously analyzes the running error so as to carry out targeted management of the target casing.

Description

Technical Field

[0001] The present invention relates to the technical field of deep hole casing management, and in particular to an intelligent decision-making system for the dynamic running depth of deep hole multi-stage casing. Background Art

[0002] Oil casing is a steel pipe used to support the wellbore of oil and gas wells to ensure the normal operation of the entire oil well during the drilling process and after completion. Each well uses several layers of casing according to the different drilling depths and geological conditions. After the casing is lowered into the well, cement is used. Unlike oil pipes and drill pipes, it cannot be reused and is a disposable consumable material.

[0003] In deephole drilling projects, casing running is one of the key links. The reasonable decision of its running depth directly affects the safety, reliability and economy of the drilling project. However, in the existing technology, it is difficult to accurately evaluate the comprehensive impact of various factors on the casing running depth during the multi-stage casing running process, which can easily lead to casing wear, drill sticking or cementing quality defects. In addition, it is impossible to achieve real-time monitoring and intelligent decision-making of the casing running process, making it difficult to adjust the running strategy in time when unexpected working conditions occur, increasing project risks and construction costs. At the same time, it is difficult to analyze the casing running error, resulting in excessive casing running deviation, which is not conducive to timely management.

[0004] In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent decision-making system for the dynamic running depth of deep hole multi-stage casing to solve the technical defects mentioned above. The present invention preliminarily analyzes the running scheme from the perspective of safety, preliminarily divides the running scheme of each stage of casing into feasible schemes and infeasible schemes and stores them, and analyzes from the perspective of multi-data processing to obtain a multi-physical field coupling model, and further performs working condition synchronization analysis on the multi-physical field coupling model to ensure the dynamic correction performance of the multi-physical field coupling model, while improving the synchronization of the multi-physical field coupling model with the actual working conditions, and analyzes the feasibility schemes of each stage of casing in an information progressive manner, and then selects the most suitable running scheme for each stage of casing, and finally combines the obtained preferred schemes to obtain a multi-stage casing running scheme, and further supervises and analyzes the actual running process to improve the running safety and reliability of the target casing, and at the same time analyzes the running error, so as to intuitively understand whether the target casing is qualified through text display, so as to carry out targeted management of the target casing.

[0006] The object of the present invention can be achieved by the following technical solutions: an intelligent decision-making system for dynamic running depth of deep hole multi-stage casing, comprising a casing running management center, a scheme feasibility unit, a multi-coupling model unit, a running combination unit, a real-time safety unit, a working condition verification unit, and an adjustment response unit;

[0007] The casing running management center is used to collect casing types of various levels of casing and send the casing types to the scheme feasibility unit for feasibility analysis of casing running decisions to obtain feasible schemes and infeasible schemes;

[0008] The multi-coupling model unit is used to perform multi-physics field coupling correlation data processing and synchronization analysis on the collected mechanical parameters, motion parameters, friction parameters and environmental parameters to obtain a multi-physics field coupling model, and to perform discrimination processing on the obtained update time interval to obtain a stable signal or a delayed signal;

[0009] The running combination unit is used to perform optimal adaptability analysis of the obtained feasibility scheme for casing running and obtain a multi-stage casing running scheme;

[0010] The real-time safety unit is used to conduct safety supervision analysis of the actual running condition of the collected friction resistance F and casing force safety factor S of the target casing to obtain a warning signal or a normal signal. The working condition verification unit is used to conduct a running error risk feedback analysis on the actual parameter error information collected for the target casing, perform discrimination processing on the actual running error degree obtained, and obtain a qualified signal or a unqualified signal.

[0011] Preferably, the casing running decision feasibility analysis process is as follows:

[0012] Obtain the casing type of each level of casing and the target deep hole insertion depth. The casing type includes outer diameter, wall thickness, and tensile strength. Generate the casing type of each level of casing based on the casing type and the target deep hole insertion depth. An entry plan, is a natural number greater than zero;

[0013] The axial tension of the casing at each level measured by the tension sensor is obtained, and the measured axial tension of the casing is judged: if the measured axial tension of the casing is less than the preset axial tension threshold of the casing, it is judged to be in a compressive state; if the measured axial tension of the casing is greater than or equal to the preset axial tension threshold of the casing, it is judged to be in a tensile state.

[0014] Preferably, when it is determined to be a compression-resistant state: the axial pressure safety factor of the casing corresponding to the compression-resistant state is obtained based on the casing type and the insertion depth. The axial pressure safety factor represents the ratio between the casing compressive strength limit and the actual axial pressure absolute value, and the axial pressure safety factor is judged and processed to obtain a safety signal or a risk signal.

[0015] Preferably, when the casing is determined to be in a tensile state: an axial tensile safety factor of the casing corresponding to the tensile state is obtained based on the casing type and the running depth, the axial tensile safety factor representing the ratio between the axial tensile strength limit of the casing and the axial tensile force of the casing measured by the tension sensor, and the axial tensile safety factor is discriminated and processed to obtain a safety signal or a risk signal;

[0016] The plan corresponding to the generated safety signal is set as a feasible plan, and the plan corresponding to the generated risk signal is set as an infeasible plan.

[0017] Preferably, the multi-physics field coupling correlation data processing and synchronization analysis process is as follows:

[0018] Obtain the mechanical parameters, motion parameters, friction parameters, and environmental parameters involved in the casing running process at all levels, preprocess the mechanical parameters, motion parameters, friction parameters, and environmental parameters, and build a multi-physics field coupling model based on the preprocessed mechanical parameters, motion parameters, friction parameters, and environmental parameters. The multi-physics field coupling model includes a kinematic field model and a tribological field model.

[0019] The update time interval of the multi-physics field coupling model is obtained, and the update time interval is discriminated and processed to obtain a stable signal or a delayed signal.

[0020] Preferably, the optimal adaptability analysis process for casing running is as follows:

[0021] The friction resistance F, casing force safety factor S, running efficiency E and casing wall temperature Tw of each level of casing in each feasible scheme are calculated through the multi-physical field coupling model. The friction resistance F, casing force safety factor S, running efficiency E and casing wall temperature Tw of each level of casing in each feasible scheme are substituted into the objective function for calculation, and the fitness J corresponding to each level of casing in each feasible scheme is obtained. The maximum value of the fitness J corresponding to each level of casing is obtained, and the maximum value of the fitness J is set as the optimal fitness J. The feasible scheme corresponding to the optimal fitness J is set as the preferred scheme. Based on the preferred scheme of each level of casing, the preferred schemes of each level of casing are combined to obtain a multi-stage casing running scheme.

[0022] Preferably, the actual running condition safety supervision analysis process is as follows:

[0023] The first casing run is set as the target casing. Based on the multi-stage casing running plan, the duration between the start and end of the target casing running is obtained. The duration between the start and end of the target casing running is set as the running period. The friction resistance F and the casing force safety factor S of the target casing during the running period are obtained in real time. The casing force safety factor S is taken as follows: if the target casing is in a compressive state, S is the axial pressure safety factor; if the target casing is in a tensile state, S is the axial tension safety factor.

[0024] The friction resistance F and the casing stress safety factor S are judged and processed to obtain a warning signal or a normal signal.

[0025] Preferably, the input error risk feedback analysis process is as follows:

[0026] Actual parameter error information of the target casing is obtained, the actual parameter error information including the friction resistance error value and the actual running depth. At the same time, predicted error information of the target casing is obtained, the predicted error information including the predicted friction resistance error value and the predicted running depth. The actual parameter error information and the predicted error information are analyzed correspondingly to obtain error information of the target casing, the error information including the friction resistance error rate and the running depth error value. The error information is discriminated and processed to obtain a discrimination processing result of the error information, the discrimination processing result including qualified and unqualified. The number of qualified results of the error information is obtained, and the number of qualified results of the error information is set as the actual running error degree. The actual running error degree is discriminated and processed to obtain a qualified signal or an unqualified signal.

[0027] The beneficial effects of the present invention are as follows:

[0028] (1) The present invention preliminarily analyzes the running scheme from the perspective of safety in order to divide the running schemes of each level of casing into safety categories. The running schemes of each level of casing are preliminarily divided into feasible schemes and infeasible schemes and stored. At the same time, the present invention analyzes from the perspective of multi-data processing to obtain a multi-physics field coupling model, and further performs working condition synchronization analysis on the multi-physics field coupling model to ensure the dynamic correction performance of the multi-physics field coupling model and improve the synchronization of the multi-physics field coupling model with the actual working conditions;

[0029] (2) The present invention analyzes the feasibility schemes of each level of casing in an information progressive manner, and then selects the most suitable running scheme for each level of casing. Finally, the preferred schemes are combined to obtain a multi-level casing running scheme, that is, the feasibility schemes are selected in a step-by-step optimization manner to improve the feasibility of the multi-level casing running scheme. The actual running process is further supervised and analyzed so that the lowering speed and rotation speed can be adjusted according to the information feedback to improve the running safety and reliability of the target casing. At the same time, the running error is analyzed so that the target casing can be intuitively understood through text display whether it is qualified, so as to carry out targeted management of the target casing. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention will be further described below with reference to the accompanying drawings;

[0031] Figure 1 It is a flow chart of the system of the present invention;

[0032] Figure 2 This is a local analysis diagram of Example 1 of the present invention. DETAILED DESCRIPTION

[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0034] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments;

[0035] Example 1:

[0036] See also Figures 1 to 2As shown, the present invention is an intelligent decision-making system for the dynamic running depth of deep hole multi-stage casing, including a casing running management center, a scheme feasibility unit, a multi-coupling model unit, a running combination unit, a real-time safety unit, a working condition verification unit and an adjustment response unit. The casing running management center is connected to the scheme feasibility unit in a two-way communication, the casing running management center is connected to the multi-coupling model unit in a one-way communication, the multi-coupling model unit is connected to the running combination unit in a one-way communication, the running combination unit is connected to the real-time safety unit and the working condition verification unit in a one-way communication, and the real-time safety unit and the working condition verification unit are both connected to the adjustment response unit in a one-way communication.

[0037] The casing running management center is used to collect casing types at all levels and send the casing types to the scheme feasibility unit for casing running decision feasibility analysis, thereby obtaining feasible and infeasible schemes for each level of casing, so as to preliminarily perform safety classification on the lower schemes. The specific casing running decision feasibility classification analysis process is as follows:

[0038] Obtain the casing type of each level of casing and the target deep hole penetration depth. The casing type includes outer diameter, wall thickness, tensile strength, etc.

[0039] Generate casing levels based on casing type and target deep hole depth An entry plan, is a natural number greater than zero. For example, by learning from the experience of casing running at all levels in historical projects through the existing intelligent algorithm model, a casing running plan for all levels in the current target deep hole is generated.

[0040] Obtain the casing axial tension measured by the tension sensor at each level, and perform discrimination processing on the measured casing axial tension: if the measured casing axial tension is less than the preset casing axial tension threshold, it is determined to be in a compressive state; if the measured casing axial tension is greater than or equal to the preset casing axial tension threshold, it is determined to be in a tensile state;

[0041] When the state is determined to be stress-resistant:

[0042] The axial pressure safety factor of the casing corresponding to the compressive state is obtained based on the casing type and the running depth. The axial pressure safety factor represents the ratio between the casing compressive strength limit and the absolute value of the actual axial pressure. The axial pressure safety factor is then judged: if the axial pressure safety factor is greater than or equal to the preset axial pressure safety factor threshold, a safety signal is generated; if the axial pressure safety factor is less than the preset axial pressure safety factor threshold, a risk signal is generated.

[0043] When it is judged to be in tensile state:

[0044] The axial tension safety factor of the casing corresponding to the tensile state is obtained based on the casing type and the running depth. The axial tension safety factor represents the ratio between the axial tensile strength limit of the casing and the axial tension of the casing measured by the tension sensor. The axial tension safety factor is then judged and processed: if the axial tension safety factor is greater than or equal to the preset axial tension safety factor threshold, a safety signal is generated; if the axial tension safety factor is less than the preset axial tension safety factor threshold, a risk signal is generated;

[0045] The running plan corresponding to the generated safety signal is set as a feasible plan, and the running plan corresponding to the generated risk signal is set as an infeasible plan. The casing running management center divides and stores the feasible and infeasible plans for each level of casing;

[0046] The multi-coupling model unit is used to perform multi-physics coupling correlation data processing and synchronization analysis on the collected mechanical parameters, motion parameters, friction parameters, and environmental parameters to obtain a multi-physics coupling model and a stable signal or a delayed signal. The specific multi-physics coupling correlation data processing and synchronization analysis process is as follows:

[0047] Obtain the mechanical parameters, motion parameters, friction parameters, and environmental parameters involved in the casing running process at each level within the time threshold. Mechanical parameters include axial force, torque, and normal force; motion parameters include running speed and rotation speed; friction parameters include friction coefficient and friction resistance; and environmental parameters include well inclination angle and formation temperature.

[0048] Preprocessing of mechanical parameters, motion parameters, friction parameters and environmental parameters, including cleaning and normalization;

[0049] Construct a multi-physics coupling model based on pre-processed mechanical parameters, motion parameters, friction parameters, and environmental parameters. The multi-physics coupling model includes a kinematic field model, a tribological field model, and the like.

[0050] Kinematic Field Model: , where Va represents the casing lowering speed, Vr represents the overall movement speed of the casing, and Vc represents the casing rotation speed;

[0051] Tribological field model: ,in, is the wellbore area variable, is the axial friction coefficient, N is the normal force per unit casing string length, and F is the friction resistance;

[0052] The update time interval of the multi-physics coupling model is obtained and the update time interval is judged and processed. If the update time interval is less than or equal to the preset update time interval threshold, a stable signal is generated. If the update time interval is greater than the preset update time interval threshold, a delay signal is generated. The response unit is adjusted to respond to the stable signal or the delay signal, and the preset warning operation corresponding to the stable signal or the delay signal is immediately performed, such as executing the continuous supervision corresponding to the stable signal and executing the alarm operation corresponding to the delay signal, so as to ensure the dynamic correction performance of the multi-physics coupling model and improve the synchronization of the multi-physics coupling model with the actual working conditions.

[0053] Example 2:

[0054] The running combination unit is used to perform optimal adaptability analysis on the obtained feasibility plan and obtain a multi-stage casing running plan. The specific optimal adaptability analysis process for casing running is as follows:

[0055] The friction resistance F, casing force safety factor S, running efficiency E, and casing wall temperature Tw of each level of casing in each feasibility scheme are calculated through the multi-physics field coupling model, and the friction resistance F, casing force safety factor S, running efficiency E, and casing wall temperature Tw of each level of casing in each feasibility scheme are substituted into the objective function for calculation, and the fitness J corresponding to each level of casing in each feasibility scheme is obtained. The maximum value of the fitness J corresponding to each level of casing is obtained, and the maximum value of the fitness J is set as the optimal fitness J. The feasibility scheme corresponding to the optimal fitness J is set as the preferred scheme. Based on the preferred scheme of each level of casing, the preferred schemes of each level of casing are combined to obtain a multi-stage casing running scheme, that is, the feasibility scheme is selected from a step-by-step optimization method to improve the feasibility of the multi-stage casing running scheme, and the response unit is adjusted to immediately display the multi-stage casing running scheme to improve the stability and safety of the casing running at each level.

[0056] The goals are to minimize friction Fmin, maximize safety factor Smax, maximize lowering efficiency Emax, and optimize operating temperature Ty;

[0057] Get the target function , where F is the friction resistance, S is the casing force safety factor (axial pressure safety factor / axial tension safety factor), E is the running efficiency, Tw is the casing wall temperature, and Ty is the optimal operating temperature. 、 、 as well as are weight coefficients, 、 、 as well as are greater than zero, 、 、 as well as All are adjusted according to project requirements;

[0058] Constraints: Casing strength constraints (such as tensile strength and compressive strength), wellbore size constraints (such as the clearance requirements between the casing and the wellbore), drilling equipment capacity constraints (such as lowering tension and rotation torque limits), etc., to ensure that the optimization results are within the practical feasibility of the project;

[0059] The real-time safety unit is used to conduct safety supervision analysis on the collected target casing friction resistance F and casing stress safety factor S during actual running conditions. This allows the running speed and rotation speed to be adjusted based on the information feedback to improve the running safety and reliability of the target casing. The specific actual running safety supervision analysis process is as follows:

[0060] The first casing run is set as the target casing. Based on the multi-stage casing running plan, the duration between the start and end of the target casing running is obtained. The duration between the start and end of the target casing running is set as the running period. The friction resistance F and the casing force safety factor S of the target casing during the running period are obtained in real time. The casing force safety factor S is taken as follows: if the target casing is in a compressive state, S is the axial pressure safety factor; if the target casing is in a tensile state, S is the axial tension safety factor.

[0061] The friction resistance F and the casing force safety factor S are judged and processed: if the friction resistance F is greater than or equal to the preset friction resistance threshold, or the casing force safety factor S is less than or equal to the preset casing force safety factor threshold, a warning signal is generated; if the friction resistance F is less than the preset friction resistance threshold, and the casing force safety factor S is greater than the preset casing force safety factor threshold, a normal signal is generated, and the response unit is adjusted to respond to the warning signal or the normal signal, and the preset warning text corresponding to the warning signal or the normal signal is immediately displayed, so as to adjust the lowering speed and the rotation speed according to the information feedback to improve the safety and reliability of the target casing;

[0062] The working condition verification unit is used to perform running error risk feedback analysis on the actual parameter error information of the collected target casing, so as to intuitively understand whether the target casing has been run in a qualified manner through text display, so as to carry out targeted management of the target casing. The specific running error risk feedback analysis process is as follows:

[0063] The actual parameter error information of the target casing is obtained, including the friction resistance error value, the actual insertion depth, etc. At the same time, the predicted error information of the target casing is obtained, including the predicted friction resistance error value, the predicted insertion depth, etc. The actual parameter error information and the predicted error information are analyzed correspondingly to obtain the error information of the target casing, including the friction resistance error rate, the insertion depth error value, etc. The error information is discriminated and processed to obtain the discrimination processing result of the error information, including qualified and unqualified. The number of qualified results of the error information is set as the actual running error, and the actual running error is judged and processed. If the actual running error is equal to a preset threshold, a qualified signal is generated. If the actual running error is not equal to the preset threshold, a failed signal is generated. The response unit is adjusted to respond to the qualified signal or the failed signal, and the preset warning text corresponding to the qualified signal or the failed signal is immediately displayed, so that the user can intuitively understand whether the target casing is qualified through the text display, so as to carry out targeted management of the target casing.

[0064] Friction resistance error rate = ratio of |friction resistance error value - predicted friction resistance error value| to predicted friction resistance error value; insertion depth error value = actual insertion depth - predicted insertion depth;

[0065] For example, if the friction resistance error rate is less than a preset friction resistance error rate threshold, it is determined to be qualified; if the friction resistance error rate is greater than or equal to the preset friction resistance error rate threshold, it is determined to be unqualified; if the entry depth error falls within the threshold entry depth error range, it is determined to be qualified; if the entry depth error does not fall within the threshold entry depth error range, it is determined to be unqualified, and so on;

[0066] In summary, the present invention preliminarily analyzes the safety of the running scheme to divide the running schemes of each stage into safety categories, preliminarily divides the running schemes of each stage into feasible schemes and infeasible schemes and stores them, and simultaneously analyzes from the perspective of multi-data processing to obtain a multi-physics field coupling model, and further performs a working condition synchronization analysis on the multi-physics field coupling model to ensure the dynamic correction performance of the multi-physics field coupling model, while improving the synchronization of the multi-physics field coupling model with the actual working conditions, and analyzes the feasibility schemes of each stage of casing in an information progressive manner, and then selects the most suitable running scheme for each stage of casing, and finally combines the obtained preferred schemes to obtain a multi-stage casing running scheme, that is, the feasibility schemes are selected in a step-by-step optimization manner to improve the feasibility of the multi-stage casing running scheme, and further supervises and analyzes the actual running process to adjust the lowering speed and rotation speed according to the information feedback to improve the running safety and reliability of the target casing, and analyzes the running error to intuitively understand whether the target casing is qualified through text display, so as to carry out targeted management of the target casing.

[0067] The threshold is set for result comparison and analysis in order to determine whether it is good or bad. The value of the threshold is set based on a combination of large-scale model analysis of sample data and manual experience to enter and store it. It can also be appropriately adjusted based on seasonal or common sense influencing conditions.

[0068] The size of the coefficient is to quantify each parameter to obtain a specific numerical value, which is convenient for subsequent comparison. The size of the coefficient depends on the amount of sample data and the preliminary setting of the corresponding operating coefficient for each set of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0069] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. An intelligent decision-making system for dynamic running depth of deep hole multi-stage casing, characterized in that: It includes casing running management center, scheme feasibility unit, multi-coupling model unit, running combination unit, real-time safety unit, working condition verification unit and adjustment response unit; The casing running management center is used to collect casing types of various levels of casing and send the casing types to the scheme feasibility unit for feasibility analysis of casing running decisions to obtain feasible schemes and infeasible schemes; The multi-coupling model unit is used to perform multi-physics field coupling correlation data processing and synchronization analysis on the collected mechanical parameters, motion parameters, friction parameters and environmental parameters to obtain a multi-physics field coupling model, and to perform discrimination processing on the obtained update time interval to obtain a stable signal or a delayed signal; The running combination unit is used to perform optimal adaptability analysis of the obtained feasibility scheme for casing running and obtain a multi-stage casing running scheme; The real-time safety unit is used to conduct safety supervision analysis of the actual running condition of the collected friction resistance F and casing force safety factor S of the target casing to obtain a warning signal or a normal signal. The working condition verification unit is used to conduct a running error risk feedback analysis on the actual parameter error information collected for the target casing, and to perform discrimination processing on the actual running error degree to obtain a qualified signal or a unqualified signal. The error information includes the friction resistance error rate and the running depth error value.

2. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 1 is characterized in that: The feasibility analysis process of casing running decision is as follows: Obtain the casing type of each level of casing and the target deep hole insertion depth. The casing type includes outer diameter, wall thickness, and tensile strength. Generate the casing type of each level of casing based on the casing type and the target deep hole insertion depth. An entry plan, is a natural number greater than zero; The axial tension of the casing at each level measured by the tension sensor is obtained, and the measured axial tension of the casing is judged: if the measured axial tension of the casing is less than the preset axial tension threshold of the casing, it is judged to be in a compressive state; if the measured axial tension of the casing is greater than or equal to the preset axial tension threshold of the casing, it is judged to be in a tensile state.

3. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 2 is characterized in that: When a compressive state is determined, the axial pressure safety factor of the casing corresponding to the compressive state is obtained based on the casing type and running depth. The axial pressure safety factor represents the ratio between the casing compressive strength limit and the absolute value of the actual axial pressure. The axial pressure safety factor is then discriminated and processed to obtain a safety signal or a risk signal.

4. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 3 is characterized in that: When the casing is judged to be in a tensile state, the axial tensile safety factor of the casing corresponding to the tensile state is obtained based on the casing type and running depth. The axial tensile safety factor represents the ratio between the axial tensile strength limit of the casing and the axial tensile force of the casing measured by the tension sensor. The axial tensile safety factor is then processed to obtain a safety signal or a risk signal. The plan corresponding to the generated safety signal is set as a feasible plan, and the plan corresponding to the generated risk signal is set as an infeasible plan.

5. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 1 is characterized in that: The multi-physics field coupling correlation data processing and synchronization analysis process is as follows: Obtain the mechanical parameters, motion parameters, friction parameters, and environmental parameters involved in the casing running process at all levels, preprocess the mechanical parameters, motion parameters, friction parameters, and environmental parameters, and build a multi-physics field coupling model based on the preprocessed mechanical parameters, motion parameters, friction parameters, and environmental parameters. The multi-physics field coupling model includes a kinematic field model and a tribological field model. The update time interval of the multi-physics field coupling model is obtained, and the update time interval is discriminated and processed to obtain a stable signal or a delayed signal.

6. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 1 is characterized in that: The optimal adaptability analysis process for casing running is as follows: The friction resistance F, casing force safety factor S, running efficiency E and casing wall temperature Tw of each level of casing in each feasible scheme are calculated through the multi-physical field coupling model. The friction resistance F, casing force safety factor S, running efficiency E and casing wall temperature Tw of each level of casing in each feasible scheme are substituted into the objective function for calculation, and the fitness J corresponding to each level of casing in each feasible scheme is obtained. The maximum value of the fitness J corresponding to each level of casing is obtained, and the maximum value of the fitness J is set as the optimal fitness J. The feasible scheme corresponding to the optimal fitness J is set as the preferred scheme. Based on the preferred scheme of each level of casing, the preferred schemes of each level of casing are combined to obtain a multi-stage casing running scheme.

7. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 1 is characterized in that: The actual safety supervision analysis process of the running-in working condition is as follows: The first casing run is set as the target casing. Based on the multi-stage casing running plan, the duration between the start and end of the target casing running is obtained. The duration between the start and end of the target casing running is set as the running period. The friction resistance F and the casing force safety factor S of the target casing during the running period are obtained in real time. The casing force safety factor S is taken as follows: if the target casing is in a compressive state, S is the axial pressure safety factor; if the target casing is in a tensile state, S is the axial tension safety factor. The friction resistance F and the casing stress safety factor S are judged and processed to obtain a warning signal or a normal signal.

8. The intelligent decision-making system for dynamic running depth of deep hole multi-stage casing according to claim 1 is characterized in that: The input error risk feedback analysis process is as follows: Actual parameter error information of the target casing is obtained, the actual parameter error information including the friction resistance error value and the actual running depth. At the same time, predicted error information of the target casing is obtained, the predicted error information including the predicted friction resistance error value and the predicted running depth. The actual parameter error information and the predicted error information are analyzed correspondingly to obtain the error information of the target casing, perform discrimination processing on the error information, obtain a discrimination processing result of the error information, the discrimination processing result including qualified and unqualified, obtain the number of qualified results of the discrimination processing of the error information, set the number of qualified results of the discrimination processing of the error information as the actual running error degree, perform discrimination processing on the actual running error degree, and obtain a qualified signal or an unqualified signal.

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