A method, system, and readable medium for deepwater drilling riser condition monitoring and fatigue prediction

Abstract

This invention belongs to the field of marine oil and gas engineering technology, and relates to a method, system, and readable medium for monitoring the condition and predicting fatigue of deep-water drilling risers. The method includes: collecting monitoring data; inputting the monitoring data into a dynamic analysis model of the riser system; calculating the riser acceleration and bending stress based on the external load on the riser; comparing the calculated riser acceleration with the on-site measured acceleration to determine the reliability of the dynamic analysis model; when the reliability meets the requirements, obtaining the bending stress time history curve from the riser bending stress calculated by the dynamic analysis model; obtaining the cyclic stress S-fatigue life N curve through the stress amplitude and the number of stress cycles; and calculating the fatigue damage of the riser system using the S-N curve. This invention can monitor platform motion, waves, currents, and acceleration vibrations with a small number of monitoring devices, thereby accurately monitoring complex seawater environments and calculating structural responses.

Description

Technical Field

[0001] This invention relates to a method, system, and readable medium for monitoring the condition and predicting fatigue of risers in deepwater drilling, belonging to the field of marine oil and gas engineering technology. Background Technology

[0002] As global oil and gas exploration and development moves towards the deep and ultra-deep sea, deepwater drilling operations face increasingly complex and harsh environments. The deepwater drilling riser is a critical "lifeline" connecting the surface drilling platform and the subsea blowout preventer assembly. During operation, it is subjected to alternating loads caused by platform movement, waves, and ocean currents. These alternating loads generate cyclic stress within the riser, leading to fatigue damage. Fatigue damage is one of the most significant risks threatening the structural integrity and operational safety of deepwater risers. If the riser breaks due to accumulated fatigue, it will not only cause enormous economic losses but may also trigger severe marine ecological disasters and personnel safety accidents. Therefore, real-time and accurate condition monitoring and fatigue life prediction of deepwater drilling risers are crucial for predictive maintenance, ensuring operational safety, and reducing operating costs.

[0003] Due to the harsh deep-sea operating environment, high costs of sensor deployment and maintenance, and complex engineering implementation conditions, it is currently difficult to achieve a high-density, full-coverage sensor network along the entire length of the riser. Accelerometers can only be installed at a few key locations. Therefore, each sensor can only collect local vibration signals at its installation point, resulting in spatially discrete and fragmented monitoring data. This prevents existing monitoring methods from directly and completely capturing and reflecting the true dynamic response along the entire length of the riser. This lack of global dynamic state information due to limitations in monitoring methods leads to significant uncertainty in the overall stress distribution inversion or estimation based on limited data. This directly affects the accuracy of subsequent structural stress analysis and the reliability of fatigue damage accumulation calculations, posing a potential risk to operational safety assessments. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide a method, system, and readable medium for monitoring the condition and predicting fatigue of deep-water drilling risers. This method can monitor platform motion, waves, currents, and acceleration vibrations using a small number of monitoring devices, thereby accurately monitoring complex marine environments and calculating structural responses.

[0005] To achieve the above objectives, the present invention proposes the following technical solution: a method for monitoring the condition and predicting the fatigue of a riser in deep water drilling, comprising the following steps: collecting monitoring data; inputting the monitoring data into a dynamic analysis model of the riser system, calculating the riser acceleration and bending stress based on the external load on the riser; comparing the calculated riser acceleration with the on-site measured acceleration to determine the reliability of the dynamic analysis model of the riser system; when the reliability meets the requirements, obtaining the bending stress time history curve through the riser bending stress calculated by the dynamic analysis model of the riser system, obtaining the cyclic stress S-fatigue life N curve through the stress amplitude and the number of stress cycles, and calculating the fatigue damage of the riser system through the S-N curve.

[0006] Furthermore, the monitoring data includes wave height, wave period, ocean current velocity, platform motion data, and acceleration monitoring data. The platform motion data includes sway, roll, and heave data. The method for collecting the monitoring data is as follows: install monitoring devices corresponding to each monitoring data according to the environment where the riser system is located; obtain each monitoring data through the monitoring devices.

[0007] Furthermore, the method for establishing the dynamic analysis model of the riser system is as follows: A transverse vibration model, an external load model, and an axial vibration model of the riser system are established; the motion boundary of the riser system is defined based on platform motion data; an overall finite element model of the riser system is established based on the external load, the transverse vibration model, the axial vibration model, and the motion boundary; the overall finite element model of the riser system is solved using the Newmark-β method to obtain the dynamic response data of the riser system; the dynamic response data of the riser system includes displacement, velocity, and acceleration; the bending moment is obtained by performing a second difference on the displacement, and the bending stress is obtained through the bending moment.

[0008] Furthermore, the lateral vibration model of the riser system is as follows:

[0009]

[0010] in, Mass per unit length of riser in deepwater drilling; c The damping coefficient; E The elastic modulus of the riser in deep-water drilling; I The moment of inertia of the cross section; T ( z () represents the effective axial tension; F ( z , t () represents the lateral load applied per unit length of the riser in a deepwater drilling system; It's the water pipe in ; t It is the time variable in mechanical analysis; It is a water-proof pipe ; It's the water pipe in x The lateral load per unit length in the direction; y It's the water pipe in It's the water pipe in y The lateral load per unit length in the direction; The longitudinal vibration model is as follows:

[0011] in, u ( z,t This refers to the axial vibration of the riser in deep-water drilling. T The axial hydrodynamic load applied to the riser in a deepwater drilling well; A ( z () represents the cross-sectional area of ​​the riser in deep-water drilling. m It is the total mass per unit length of the riser pipe; g It is gravitational acceleration.

[0012] Furthermore, the method for establishing the external load of the riser is as follows: the velocity of the wave water particles in the wave propagation direction is represented by an Airy wave, and the x-axis component and y-axis component of the wave water particle velocity are calculated respectively; the wave water particle velocity is differentiated to obtain the wave water particle acceleration, and the x-axis component and y-axis component of the wave water particle acceleration are calculated respectively; the external load of the riser is calculated based on the x-axis component and y-axis component of the wave water particle acceleration.

[0013] Furthermore, the external load on the riser pipe is: x-axis component of external load on riser pipe:

[0014]

[0015] in, ρ The density of seawater; The outer diameter is the hydrodynamic diameter. C D This is the drag coefficient; Indicates the inertial force coefficient; The x-axis component represents the velocity of wave particles. The y-axis component represents the velocity of the wave-water particles. The x-axis component represents the acceleration of wave-induced water particle motion. The y-axis component of the acceleration of wave-induced water particle motion; The x-component represents the ocean current velocity under steady-state conditions; The y-component represents the ocean current velocity under steady-state conditions; and These represent the velocities of the riser pipe in the x and y directions, respectively. and These represent the accelerations of the riser pipe in the x and y directions, respectively.

[0016] Furthermore, the calculated acceleration of the riser pipe is compared with the actual measured acceleration. If the main vibration frequency components and corresponding vibration amplitudes of the two are consistent, the reliability of the dynamic analysis model of the riser pipe system meets the requirements; otherwise, the reliability of the dynamic analysis model of the riser pipe system does not meet the requirements. If the reliability of the dynamic analysis model of the riser pipe system does not meet the requirements, parameter sensitivity analysis is used to identify the dynamic model parameters that have the most significant impact on the frequency response deviation. Based on the displacement frequency error and amplitude error calculated and measured by the dynamic analysis model of the riser pipe system, an objective function is constructed. A multi-objective optimization algorithm is used to automatically adjust the dynamic model parameters and perform iterative calculations with minimizing the objective function as the criterion. When the iterative optimization makes the objective function value reach the preset convergence standard, the correction process terminates, and the corrected dynamic analysis model of the riser pipe system is obtained.

[0017] Furthermore, the fatigue damage is represented as:

[0018] in, D For annual fatigue damage; n c This represents the number of loop iterations. f m Average frequency; S k For the first k Cyclic stress amplitude; m f and C f All SN Curve performance parameters; the long-term fatigue damage calculation of the riser system is based on a linear fatigue damage criterion, integrating the fatigue damage for each short-term sea state, and is expressed as:

[0019] in, D L This is due to long-term fatigue damage; N f For fatigue analysis of the total number of sea states; D i For the first i Annual fatigue damage under various sea conditions; P i For the first iThe probability of a given sea state occurring.

[0020] This invention also discloses a deep-water drilling riser condition monitoring and fatigue prediction system, comprising: a data acquisition module for acquiring monitoring data; a model calculation module for inputting the monitoring data into a riser system dynamic analysis model, and calculating the riser acceleration and bending stress based on the external load on the riser; a reliability judgment module for comparing the calculated riser acceleration with the on-site measured acceleration to determine the reliability of the riser system dynamic analysis model; and a fatigue damage calculation module for obtaining a bending stress time history curve from the riser bending stress calculated by the riser system dynamic analysis model when the reliability meets the requirements, obtaining a cyclic stress S-fatigue life N curve from the stress amplitude and the number of stress cycles, and calculating the fatigue damage of the riser system from the S-N curve.

[0021] The present invention also discloses a computer-readable storage medium storing a computer program, which is executed by a processor to implement the deep-water drilling riser condition monitoring and fatigue prediction method described in any of the preceding claims.

[0022] The technical solution of the present invention has at least the following technical effects or advantages: 1. This invention can monitor platform motion, waves, ocean currents and acceleration vibrations with a small number of monitoring devices, thereby accurately monitoring complex seawater environments and calculating structural responses.

[0023] 2. The present invention can monitor and transmit acceleration vibration data in real time through the above-mentioned monitoring device, thereby realizing continuous tracking of the marine environment and real-time monitoring of riser vibration.

[0024] 3. This invention verifies and corrects the dynamic model using real-time monitored data, and combines it with a fatigue damage model to reliably assess the cumulative damage and remaining life of key parts of the riser, thereby significantly improving the accuracy of fatigue calculation. Attached Figure Description

[0025] Figure 1 This is a flowchart of a method for monitoring the condition and predicting fatigue of a deep-water drilling riser in one embodiment of the present invention; Figure 2 This is a flowchart of a method for establishing a dynamic analysis model of a water-proof pipe system in one embodiment of the present invention. Detailed Implementation

[0026] To enable those skilled in the art to better understand the technical solutions of this invention, specific embodiments are described in detail. However, it should be understood that the specific embodiments are provided solely for the purpose of better understanding this invention and should not be construed as limiting it. In the description of this invention, it should be understood that the terminology used is for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0027] To address the limitations of existing monitoring methods in directly and comprehensively capturing and reflecting the true dynamic response along the entire length of the riser, this invention provides a method, system, and readable medium for monitoring the condition and predicting fatigue of a deep-water drilling riser. The method includes the following steps: collecting monitoring data; inputting the monitoring data into a dynamic analysis model of the riser system; calculating the riser acceleration and bending stress based on the external load on the riser; comparing the calculated riser acceleration with the field-measured acceleration to determine the reliability of the dynamic analysis model; and, if the reliability meets the requirements, obtaining the bending stress time history curve from the calculated riser bending stress using the dynamic analysis model, obtaining the cyclic stress S-fatigue life N curve using the stress amplitude and stress cycle number, and calculating the fatigue damage of the riser system using the S-N curve. This invention, through real-time monitoring and comparison of measured and calculated data, optimizes the dynamic analysis model of the riser system, significantly improving the accuracy of riser fatigue calculation.

[0028] Example 1 This embodiment discloses a method for monitoring the condition and predicting the fatigue of risers in deep-water drilling, such as... Figure 1 As shown, it includes the following steps: S1 collects monitoring data.

[0029] According to the monitoring plan, monitoring data is obtained. The monitoring data includes wave height, wave period, ocean current velocity, platform motion data, and acceleration monitoring data, etc. The platform motion data includes sway, roll, and heave data.

[0030] The method for collecting monitoring data is as follows: Based on the environment of the riser system and the monitoring plan, install monitoring devices corresponding to each monitoring data point; obtain each monitoring data point through the monitoring devices. Specifically, install platform motion monitoring devices, wave monitors, current profilers, accelerometers, etc., to monitor platform motion data, wave height, wave period, current velocity, and acceleration vibration data respectively.

[0031] S2 inputs the monitoring data into the dynamic analysis model of the riser system, and calculates the riser acceleration and bending stress based on the external load on the riser.

[0032] like Figure 2As shown, the method for establishing the dynamic analysis model of the riser system is as follows: S2.1 Establish the transverse vibration model, external load and axial vibration model of the riser system; define the motion boundary of the riser system based on the platform motion data.

[0033] The transverse vibration model of the riser system is as follows:

[0034]

[0035] in, Mass per unit length of riser in deepwater drilling; c The damping coefficient; E The elastic modulus of the riser in deep-water drilling; I The moment of inertia of the cross section; T ( z () represents the effective axial tension; F ( z , t () represents the lateral load applied per unit length of the riser in a deepwater drilling system; It's the water pipe in ; t It is the time variable in mechanical analysis; It is a water-proof pipe ; It's the water pipe in x The lateral load per unit length in the direction; y It's the water pipe in It's the water pipe in y The lateral load per unit length in the direction.

[0036] The method for establishing the external load on the riser is as follows: The velocity of wave particles in the direction of wave propagation is represented by Airy waves, and the x-axis and y-axis components of the wave particle velocity are calculated respectively.

[0037] Wave water particle velocity The calculation formula is:

[0038] in, T The wave period is obtained from wave monitoring; H Wave height obtained from wave monitoring; d Seawater depth; ω The angular frequency of the wave; k Wave number; η Wave motion in the direction of wave propagation.

[0039] x-axis component of wave-water particle velocity for:

[0040] y-axis component of wave-water particle velocity for:

[0041] in, θ For the direction of wave propagation and x Angle along the axial direction.

[0042] Differentiate the velocity of the wave-water particles to obtain the acceleration of the wave-water particles, and calculate the x-axis and y-axis components of the acceleration of the wave-water particles respectively.

[0043] Wave-water particle acceleration The calculation formula is:

[0044] x-axis component of wave-water particle acceleration for:

[0045] The y-axis component of the wave-water particle velocity is:

[0046] The external load on the riser is calculated based on the x-axis and y-axis components of the wave-water particle acceleration.

[0047] The external load on the riser is: x-axis component of external load on riser pipe:

[0048]

[0049] in, ρ The density of seawater; The outer diameter is the hydrodynamic diameter. C D This is the drag coefficient; Indicates the inertial force coefficient; The x-component represents the ocean current velocity under steady-state conditions; The y-component represents the ocean current velocity under steady-state conditions; and These represent the velocities of the riser pipe in the x and y directions, respectively. and These represent the accelerations of the riser pipe in the x and y directions, respectively.

[0050] The longitudinal vibration model is as follows:

[0051] in, u ( z,t This refers to the axial vibration of the riser in deep-water drilling. T The axial hydrodynamic load applied to the riser in a deepwater drilling well; A ( z () represents the cross-sectional area of ​​the riser in deep-water drilling. m It is the total mass per unit length of the riser pipe; g It is gravitational acceleration.

[0052] The formula for calculating the moving boundary of the riser is as follows:

[0053] in, S p,纵荡 To monitor oscillation data for the platform; S p,横荡 To monitor sway data on the platform; S p,升沉 To monitor heave and sag data for the platform; H 0 represents the platform's position coordinates; H 1 represents the coordinates of the bottom of the riser system.

[0054] S2.2 Based on the external load of the riser pipe, the transverse vibration model of the riser pipe system, the axial vibration model of the riser pipe system, and the motion boundary, establish the overall finite element model of the riser pipe system.

[0055] The calculation formula for the overall finite element model of the riser system is as follows:

[0056] in, u For the displacement vector of the riser system in deepwater drilling; M , C and K These are the overall mass matrix, the overall damping matrix, and the overall stiffness matrix, respectively. F This is the load vector for the riser system in deepwater drilling.

[0057] S2.3 The overall finite element model of the riser system is solved using the Newmark-β method to obtain the dynamic response data of the riser system. The dynamic response data of the riser system includes displacement, velocity, and acceleration; the bending moment is obtained by performing a second difference on the displacement, and the bending stress is obtained from the bending moment.

[0058] The formula for calculating bending stress is:

[0059]

[0060] in,M x , M y They are x , y Bending moment in the direction; E It is the elastic modulus; I It is the moment of inertia of the cross section; S x , S y They are x , y Bending stress in the direction; R It is the outer radius of the riser pipe.

[0061] S3 compares the calculated riser acceleration with the actual measured acceleration on site to determine the reliability of the dynamic analysis model of the riser system.

[0062] The calculated riser acceleration is compared with the on-site measured acceleration. If the main vibration frequency components and corresponding vibration amplitudes are consistent, the reliability of the riser system dynamic analysis model meets the requirements; otherwise, the reliability does not meet the requirements. If the reliability of the riser system dynamic analysis model meets the requirements, it proves that the dynamic response of the current riser system dynamic analysis model is highly consistent with the dynamic response of the riser under actual working conditions. In this case, the high-confidence displacement response output by the verified riser system dynamic analysis model can be directly adopted. If the reliability of the riser system dynamic analysis model does not meet the requirements, it indicates that the current dynamic parameter settings of the riser system dynamic analysis model fail to accurately characterize the physical characteristics of the actual system, resulting in a large difference between its dynamic response and the measured response. Therefore, the riser system dynamic analysis model needs to be corrected. In this embodiment, the dynamic parameters include, but are not limited to, boundary condition stiffness, structural damping coefficient, distributed mass, or hydrodynamic load coefficient.

[0063] If the reliability of the dynamic analysis model of the riser system does not meet the requirements, parameter sensitivity analysis is used to identify the dynamic model parameters that have the most significant impact on the frequency response deviation. Based on the displacement frequency error and amplitude error calculated and measured by the dynamic analysis model of the riser system, an objective function is constructed. The formula for calculating the objective function is as follows:

[0064] in, f s,x and f m,x The results obtained from the dynamic model and monitoring are respectively x The vibration frequency of the directional riser pipe; f s,y and fm,y The results obtained from the dynamic model and monitoring are respectively y The vibration frequency of the directional riser pipe; A s,x and A m,x The results obtained from the dynamic model and monitoring are respectively x Maximum vibration amplitude of the directional riser pipe; A s,y and A m,y The results obtained from the dynamic model and monitoring are respectively y Maximum vibration amplitude of the directional riser pipe.

[0065] A multi-objective optimization algorithm is used to automatically adjust the dynamic model parameters and perform iterative calculations based on minimizing the objective function. The optimization process is shown below:

[0066] When the iterative optimization causes the objective function value to reach the preset convergence criterion, that is, when the frequency response characteristics calculated by the dynamic analysis model of the riser system fully match the measured data, the correction process terminates, resulting in the corrected dynamic analysis model of the riser system. The displacement response of the riser system is then obtained based on this corrected model. In this embodiment, the multi-objective optimization algorithm can be a genetic algorithm, but it is not limited to this.

[0067] When the reliability requirements are met, the bending stress time history curve of the riser is obtained by calculating the bending stress of the riser through the dynamic analysis model of the riser system. The cyclic stress S-fatigue life N curve is obtained by the stress amplitude and the number of stress cycles. The fatigue damage of the riser system is calculated by the SN curve.

[0068] Fatigue damage is represented as:

[0069] in, D For annual fatigue damage; n c This represents the number of loop iterations. f m Average frequency; S k For the first k Cyclic stress amplitude; m f and C f All SN Curve performance parameters; the long-term fatigue damage calculation of the riser system is based on a linear fatigue damage criterion, integrating the fatigue damage for each short-term sea state, and is expressed as:

[0070] in, D L This is due to long-term fatigue damage; N f For fatigue analysis of the total number of sea states; D i For the first i Annual fatigue damage under various sea conditions; P i For the first i The probability of a given sea state occurring.

[0071] Example 2 Based on the same inventive concept, this embodiment discloses a deepwater drilling riser condition monitoring and fatigue prediction system, including: The data acquisition module is used to collect monitoring data; The model calculation module is used to input monitoring data into the dynamic analysis model of the riser system and calculate the acceleration and bending stress of the riser based on the external load on the riser. The reliability assessment module is used to compare the calculated acceleration of the riser with the actual measured acceleration on site to determine the reliability of the dynamic analysis model of the riser system. The fatigue damage calculation module is used to obtain the bending stress time history curve of the riser by calculating the bending stress of the riser through the dynamic analysis model of the riser system when the reliability requirements are met. It also obtains the cyclic stress S-fatigue life N curve by using the stress amplitude and the number of stress cycles, and calculates the fatigue damage of the riser system through the SN curve.

[0072] Example 3 Based on the same inventive concept, this embodiment discloses a computer-readable storage medium storing a computer program, which is executed by a processor to implement the deep-water drilling riser condition monitoring and fatigue prediction method described above.

[0073] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0075] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0076] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0077] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific embodiments of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention. The above content is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims

1. A method of monitoring the condition of a deep water drilling riser and predicting fatigue, the method comprising: Includes the following steps: Collect monitoring data; The monitoring data is input into the dynamic analysis model of the riser system, and the acceleration and bending stress of the riser are calculated based on the external load on the riser. The calculated acceleration of the riser pipe is compared with the actual measured acceleration on site to determine the reliability of the dynamic analysis model of the riser pipe system. When the reliability requirements are met, the bending stress time history curve of the riser is obtained by calculating the bending stress of the riser through the dynamic analysis model of the riser system. The cyclic stress S-fatigue life N curve is obtained by the stress amplitude and the number of stress cycles. The fatigue damage of the riser system is calculated by the SN curve.

2. The deep water riser condition monitoring and fatigue prediction method of claim 1, wherein, The monitoring data includes wave height, wave period, ocean current velocity, platform motion data, and acceleration monitoring data. The platform motion data includes sway, roll, and heave data. The method for collecting the monitoring data is as follows: install monitoring devices corresponding to each monitoring data according to the environment where the riser system is located; obtain each monitoring data through the monitoring devices.

3. The deep water riser condition monitoring and fatigue prediction method of claim 2, wherein, The method for establishing the dynamic analysis model of the riser system is as follows: Establish transverse vibration models, external load models, and axial vibration models for the riser system; Define the motion boundary of the riser system based on platform motion data; Based on the external load of the riser, the transverse vibration model and axial vibration model of the riser system, and the motion boundary, a finite element model of the overall riser system is established. The overall finite element model of the riser system is solved using the Newmark-β method to obtain the dynamic response data of the riser system. The dynamic response data of the riser system includes displacement, velocity, and acceleration. The bending moment is obtained by performing a second difference on the displacement, and the bending stress is obtained through the bending moment.

4. The method for monitoring the condition and predicting fatigue of the riser in deep water drilling as described in claim 3, characterized in that, The transverse vibration model of the riser system is as follows: in, Mass per unit length of riser in deepwater drilling; c The damping coefficient; E The elastic modulus of the riser in deep-water drilling; I The moment of inertia of the cross section; T ( z () represents the effective axial tension; F ( z , t () represents the lateral load applied per unit length of the riser in a deepwater drilling system; It's the water pipe in ; t It is the time variable in mechanical analysis; It is a water-proof pipe ; It's the water pipe in x The lateral load per unit length in the direction; y It's the water pipe in It's the water pipe in y The lateral load per unit length in the direction; The longitudinal vibration model is as follows: in, u ( z,t This refers to the axial vibration of the riser in deep-water drilling. T The axial hydrodynamic load applied to the riser in a deepwater drilling well; A ( z () represents the cross-sectional area of ​​the riser in deep-water drilling. m It is the total mass per unit length of the riser pipe; g It is gravitational acceleration.

5. The method for monitoring the condition and predicting fatigue of the riser in deep water drilling as described in claim 4, characterized in that, The method for establishing the external load on the riser is as follows: The velocity of wave particles in the direction of wave propagation is represented by Airy waves, and the x-axis component and y-axis component of the velocity of wave particles are calculated respectively. Differentiate the velocity of the wave-water particles to obtain the acceleration of the wave-water particles, and calculate the x-axis and y-axis components of the acceleration of the wave-water particles respectively; The external load on the riser is calculated based on the x-axis and y-axis components of the wave-water particle acceleration.

6. The method for monitoring the condition and predicting fatigue of the riser in deep water drilling as described in claim 5, characterized in that, The external load on the riser is: x-axis component of external load on riser pipe: in, ρ The density of seawater; The outer diameter is the hydrodynamic diameter. C D This is the drag coefficient; Indicates the inertial force coefficient; The x-axis component represents the velocity of wave particles. The y-axis component represents the velocity of the wave-water particles. The x-axis component represents the acceleration of wave-induced water particle motion. The y-axis component of the acceleration of wave-induced water particle motion; The x-component represents the ocean current velocity under steady-state conditions; The y-component represents the ocean current velocity under steady-state conditions; and These represent the velocities of the riser pipe in the x and y directions, respectively. and These represent the accelerations of the riser pipe in the x and y directions, respectively.

7. The method for monitoring the condition and predicting fatigue of the riser in deep water drilling as described in claim 1, characterized in that, The calculated acceleration of the riser is compared with the actual measured acceleration. If the main vibration frequency components and corresponding vibration amplitudes are consistent, the reliability of the riser system dynamic analysis model meets the requirements; otherwise, the reliability does not meet the requirements. If the reliability of the riser system dynamic analysis model does not meet the requirements, parameter sensitivity analysis is used to identify the riser system dynamic analysis model parameters that have the most significant impact on the frequency response deviation. Based on the displacement frequency error and amplitude error calculated and measured by the riser system dynamic analysis model, an objective function is constructed. A multi-objective optimization algorithm is used to automatically adjust the riser system dynamic analysis model parameters and perform iterative calculations with minimizing the objective function as the criterion. When the iterative optimization makes the objective function value reach the preset convergence standard, the correction process terminates, and the corrected riser system dynamic analysis model is obtained.

8. The method for monitoring the condition and predicting fatigue of the riser in deep water drilling as described in claim 1, characterized in that, The fatigue damage is represented as follows: in, D For annual fatigue damage; n c This represents the number of loop iterations. f m Average frequency; S k For the first k Cyclic stress amplitude; m f and C f All SN Curve performance parameters; The long-term fatigue damage calculation for the riser system is derived by integrating the fatigue damage for each short-term sea state using a linear fatigue damage criterion, and is expressed as follows: in, D L This is due to long-term fatigue damage; N f For fatigue analysis of the total number of sea states; D i For the first i Annual fatigue damage under various sea conditions; P i For the first i The probability of a given sea state occurring.

9. A deep-water drilling riser condition monitoring and fatigue prediction system, characterized in that, include: The data acquisition module is used to collect monitoring data; The model calculation module is used to input the monitoring data into the dynamic analysis model of the riser system, and calculate the acceleration and bending stress of the riser based on the external load on the riser. The reliability assessment module is used to compare the calculated acceleration of the riser pipe with the actual measured acceleration on site to determine the reliability of the dynamic analysis model of the riser pipe system. The fatigue damage calculation module is used to obtain the bending stress time history curve of the riser pipe by calculating the bending stress of the riser pipe through the dynamic analysis model of the riser pipe system when the reliability meets the requirements, obtain the cyclic stress S-fatigue life N curve by the stress amplitude and the number of stress cycles, and calculate the fatigue damage of the riser pipe system by the SN curve.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which is executed by a processor to implement the deepwater drilling riser condition monitoring and fatigue prediction method as described in any one of claims 1-8.

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