Resilient design method for control system of well control equipment in offshore oil and gas development

Abstract

The present application belongs to the field of marine engineering equipment design and detection technology, and particularly relates to a kind of marine oil and gas development well control equipment control system toughness design method.The design method takes marine oil and gas development well control equipment control system as engineering background, takes full life cycle as design optimization time scale, comprehensively considers the coupling of system natural degradation and external impact, combines dynamic reliability, redundancy configuration and maintenance strategy, realizes the optimal control of system reliability and total cost in full life cycle.The design method includes: evaluating the dynamic reliability of marine oil and gas development well control equipment control system in full life cycle;evaluating the total cost of marine oil and gas development well control equipment control system in full life cycle;determining the integrated optimization target of reliability and redundancy;obtaining the Pareto optimal frontier solution of reliability and redundancy;using TOPSIS decision method, obtaining the optimal solution of toughness design.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of marine engineering equipment design and detection, and particularly relates to a marine oil and gas development well control equipment control system toughness design method. BACKGROUND

[0002] As an important device for ensuring the safety of oil and gas well operation, the marine oil and gas development well control equipment can quickly control the wellhead pressure when a blowout accident occurs, thereby protecting the safety of personnel and equipment. The well control equipment control system, as the control core of the well control equipment, relies on composite electric control technology to achieve rapid response and accurate execution of emergency outburst accidents in extremely harsh working conditions, thereby meeting the requirements of high safety and long-period continuous operation of offshore drilling operations.

[0003] At present, the design of the control system of the existing well control equipment mainly relies on reliability engineering methods and multiple redundant architectures to ensure the stability and fault tolerance of the control system during service. However, the existing design method usually develops design from the perspective of static or phased time scale, and does not consider the maintenance resources and maintenance strategies in the whole life cycle into the optimization framework. In addition, the existing design method also lacks an integrated collaborative optimization mechanism for reliability and redundancy, ignores the cost-performance constraint relationship between the two, and is difficult to achieve the optimal balance between the toughness and economy of the control system. Therefore, it is particularly necessary for those skilled in the art to design a new marine oil and gas development well control equipment control system toughness design method. SUMMARY

[0004] The application provides a marine oil and gas development well control equipment control system toughness design method. The marine oil and gas development well control equipment control system toughness design method takes the marine oil and gas development well control equipment control system as the engineering background, takes the whole life cycle as the design optimization time scale, comprehensively considers the coupling effect of system natural degradation and external impact, combines dynamic reliability, redundancy configuration and maintenance strategy, and builds a reliability and redundancy integrated allocation and decision model, thereby achieving optimal control of system reliability and total cost in the whole life cycle, significantly improving the anti-interference ability of the marine oil and gas development well control equipment control system under extreme environmental impact, effectively reducing the failure risk of the system, and realizing high toughness and economic feasibility of the marine oil and gas development well control equipment control system.

[0005] To solve the above technical problems, the application adopts the following technical solutions:

[0006] The marine oil and gas development well control equipment control system toughness design method comprises the following steps:

[0007] Step S1: evaluating the dynamic reliability of the offshore oil and gas well control equipment control system in the whole life cycle;

[0008] Step S2: evaluating the total cost of the offshore oil and gas well control equipment control system in the whole life cycle;

[0009] Step S3: determining the reliability and redundancy integrated optimization target;

[0010] Step S4: constructing a reliability and redundancy integrated optimization model based on a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal frontier solution of reliability and redundancy;

[0011] Step S5: using a TOPSIS decision method to select an optimal solution for the offshore oil and gas well control equipment control system from the Pareto optimal frontier solution.

[0012] More preferably, the process of evaluating the dynamic reliability of the offshore oil and gas well control equipment control system in the whole life cycle in step S1 is specifically described as follows:

[0013] Under natural degradation, assuming that the reliability of a component m in the offshore oil and gas well control equipment control system at time t k is Rm(t k ), then the reliability Rm(t k+1 ) at time t k+1 satisfies: ;

[0014] where ΔRm(t k+1 ) is the reliability change amount of component m between time t k+1 and time t k .

[0015] Considering the influence of the degradation dependency relationship between components, ΔRm(t k+1 ) satisfies: ;

[0016] where ΔRmm(t k+1 ) represents the inherent reliability change amount of component m, and ΔRmn(t k+1 ) represents the additional reliability change amount considering the degradation dependency influence of component n on component m.

[0017] Similarly, the reliability of a component n in the offshore oil and gas well control equipment control system at time t k is Rn(t k ), then the reliability Rn(t k+1 ) at time t k+1 satisfies: ;

[0018] Wherein, ΔRn(t) k+1 ) for t k+1 Time and t k The change in reliability of component n over time;

[0019] Considering the impact of degradation dependencies between components, ΔRn(t) k+1 ),satisfy: ;

[0020] Wherein, ΔRnn(t) k+1 ) represents the inherent reliability variation of component n itself, ΔRnm(t) k+1 This indicates the additional reliability change resulting from considering the degradation dependency of component m on component n;

[0021] Since the components in the control system of well control equipment for offshore oil and gas development are mainly electronic components, it is assumed that their inherent reliability degradation follows an exponential degradation law, i.e., t k The reliability of components at any given time must satisfy: ;

[0022] Taking component m as an example, ΔRmn(t) represents the additional reliability change caused by considering the degradation dependence of component n on component m. k+1 ),satisfy: ;

[0023] in, The degradation dependency of component n on component m;

[0024] Considering component redundancy, the control system for offshore oil and gas development well control equipment is designed for t k Reliability R at any moment sys (t k ),satisfy: ;

[0025] Among them, R i (t k ) represents the i-th component in t k The reliability at any given time, where cn is the total number of components in the control system of the well control equipment for offshore oil and gas development, and ni is the redundancy level of the i-th component;

[0026] Assuming the arrival time of external shock events faced by the control system of offshore oil and gas development well control equipment follows a non-homogeneous Poisson process; then from 0 to t k During the time period, an external shock occurred. num The probability of this event satisfies: ;

[0027] Wherein, N(t) k ) represents time [0, t] kThe total number of impact events occurring within time [0, t k+1 ] ; N(t k+1 ) represents the total number of impact events occurring within time [0, t I ] ; the variable a represents time; and l(a) represents the instantaneous rate of external impact event occurrence at a specific time point a, which is estimated based on historical impact event data to estimate the intensity function of the non-homogeneous Poisson process;

[0028] The degree of influence of external impact on the control system of well control equipment for offshore oil and gas development is assumed to follow a generalized extreme value distribution; wherein the cumulative distribution function of the generalized extreme value distribution satisfies: ;

[0029] Wherein z(w) represents the intensity of the wth external impact; v is a location parameter, representing the central position of the generalized extreme value distribution; is a scale parameter, representing the scale position of the generalized extreme value distribution, and 0 is a shape parameter;

[0030] In summary, the dynamic reliability of the control system of well control equipment for offshore oil and gas development in the whole life cycle considers the system reliability and the degree of influence of cumulative external impact under the degradation dependence relationship, and the following is obtained: 。

[0031] More preferably, the process of evaluating the total cost of the control system of well control equipment for offshore oil and gas development in the whole life cycle in step S2 specifically includes the following steps:

[0032] Step S2.1: constructing a reliability-cost function model;

[0033] Step S2.2: constructing a maintenance cost evaluation model;

[0034] Step S2.3: based on the reliability-cost function model and the maintenance cost evaluation model, a total cost evaluation model of the control system of well control equipment for offshore oil and gas development in the whole life cycle is constructed.

[0035] More preferably, the reliability-cost function model C I constructed in step S2.1 satisfies: ;

[0036] Wherein f i is the manufacturing cost coefficient of the ith component; R i is the reliability of component i under natural degradation conditions in a given life cycle; R i,min is the initial reliability of component i; R i,max is the maximum value of the reliability that component i can theoretically achieve; a i and b i are cost correction coefficients of component i, which are assumed by investigating the cost of each component;

[0037] The step S2.2 constructs the maintenance cost evaluation model C M , satisfying: ;

[0038] Wherein, N is the total maintenance times of the well control equipment control system of the offshore oil and gas development in the whole life cycle, D M (x) is the time of the xth maintenance activity, C d is the downtime loss per unit time, C r is the maintenance resource cost per unit time.

[0039] More preferably, the TOPSIS decision method is used in the step S5 to select the optimal solution of the well control equipment control system of the offshore oil and gas development from the Pareto optimal frontier solution, and the process specifically includes the following steps:

[0040] Step S5.1: According to the reliability and the total cost of the whole life cycle, the reliability and redundancy configuration of the well control equipment control system of the offshore oil and gas development is evaluated, and a decision matrix D is constructed;

[0041] Step S5.2: The decision matrix D is normalized;

[0042] Step S5.3: The reliability and cost weights are dynamically adjusted; the normalized decision matrix D is weighted processed by using the dynamically adjusted weights;

[0043] Step S5.4: The ideal solution and the negative ideal solution are determined; wherein the ideal solution is the solution of maximizing the reliability and minimizing the cost, and the negative ideal solution is the solution of minimizing the reliability and maximizing the cost;

[0044] Step S5.5: The distances of each solution from the ideal solution and the negative ideal solution are calculated;

[0045] Step S5.6: The relative closeness of each solution is calculated, and the optimal solution is sorted.

[0046] The application provides a well control equipment control system of offshore oil and gas development resilience design method. The well control equipment control system of offshore oil and gas development resilience design method includes the following steps: evaluating the dynamic reliability of the well control equipment control system of offshore oil and gas development in the whole life cycle; evaluating the total cost of the well control equipment control system of offshore oil and gas development in the whole life cycle; determining the integrated optimization target of reliability and redundancy; constructing the integrated optimization model of reliability and redundancy based on the multi-objective particle swarm optimization algorithm to obtain the Pareto optimal frontier solution of reliability and redundancy; and selecting the optimal solution of the well control equipment control system of offshore oil and gas development resilience design from the Pareto optimal frontier solution by using the TOPSIS decision method.

[0047] The marine oil and gas development well control equipment control system resilience design method with the above step characteristics has at least the following technical advantages compared with the prior art:

[0048] 1) The marine oil and gas development well control equipment control system resilience design method provided by the application takes the marine oil and gas development well control equipment control system as the engineering background, takes the whole life cycle as the design optimization time scale, comprehensively considers the comprehensive influence of natural degradation and external impact of the well control equipment control system, combines dynamic reliability, redundancy and maintenance strategy of the whole life cycle, realizes maximization of reliability and minimization of total cost in the whole life cycle, and guarantees the anti-impact ability of the marine oil and gas development well control equipment control system under external impact.

[0049] 2) The marine oil and gas development well control equipment control system resilience design method provided by the application avoids the extreme case of failure of the marine oil and gas development well control equipment control system to the greatest extent, fully considers the cost-performance constraint relationship between reliability and redundancy through an integrated collaborative optimization mechanism of reliability and redundancy, and realizes optimal resilience design of the marine oil and gas development well control equipment control system based on integrated optimization of reliability and redundancy. BRIEF DESCRIPTION OF DRAWINGS

[0050] The accompanying drawings are used to provide further understanding of the application, and constitute a part of the specification, together with embodiments of the application, to explain the application, and do not constitute a limitation on the application. In the following drawings:

[0051] Figure 1 The flowchart of the marine oil and gas development well control equipment control system resilience design method provided by the application. DETAILED DESCRIPTION

[0052] The application provides a marine oil and gas development well control equipment control system resilience design method. The marine oil and gas development well control equipment control system resilience design method takes the marine oil and gas development well control equipment control system as the engineering background, takes the whole life cycle as the design optimization time scale, comprehensively considers the coupling effect of natural degradation and external impact of the system, combines dynamic reliability, redundancy configuration and maintenance strategy, constructs a reliability and redundancy integrated allocation and decision model, realizes optimal control of system reliability and total cost in the whole life cycle, significantly improves the anti-interference ability of the marine oil and gas development well control equipment control system under extreme environmental impact, effectively reduces the failure risk of the system, and realizes high resilience and economic feasibility of the system design of the marine oil and gas development well control equipment control system.

[0053] As Figure 1As shown, the present application provides a kind of marine oil and gas development well control equipment control system toughness design method. Wherein, the marine oil and gas development well control equipment control system toughness design method includes the following steps:

[0054] Step S1: the dynamic reliability of marine oil and gas development well control equipment control system in whole life cycle is evaluated.

[0055] It should be noted that the main function of marine oil and gas development well control equipment control system is as the switch of controlling well control equipment (such as annular blowout preventer, gate blowout preventer, shear gate, etc.), and its internal composition mainly includes central control unit, blue box, yellow box and other types of electric control subsystem. Among them, blue box and yellow box are double redundant control. The electric signal sent by the marine oil and gas development well control equipment control system is transmitted to the underwater control module installed on the well control equipment through the umbilical cable, and the electromagnetic valve in the underwater control module receives the electric signal, opens or closes the hydraulic valve, so as to control the flow direction of hydraulic oil to the well control equipment actuator.

[0056] Therefore, for the dynamic reliability evaluation process of marine oil and gas development well control equipment control system, the degradation dependence relationship between components needs to be considered, that is, the degradation of components in the control system is affected by other components in the control system; At the same time, the degradation of itself will also affect the degradation of other components. Among them, the overall reliability of marine oil and gas development well control equipment control system is finally determined by the connection relationship between components.

[0057] As a more preferred embodiment provided by the present application, the process of evaluating the dynamic reliability of marine oil and gas development well control equipment control system in whole life cycle in step S1 is specifically described as follows:

[0058] First, consider the reliability of a component in marine oil and gas development well control equipment control system at a certain time:

[0059] Under natural degradation, assume that the reliability of a component m in marine oil and gas development well control equipment control system at t k time is Rm(t k ), then the reliability Rm(t k+1 ) at t k+1 time satisfies: ;

[0060] Among them, ΔRm(t k+1 ) is the reliability change amount of component m between t k+1 time and t k time;

[0061] Considering the influence of degradation dependence relationship between components, ΔRm(t k+1 ) satisfies: ;

[0062] where ΔRmm(t k+1 ) represents the reliability change of component m itself, and ΔRmn(t k+1 ) represents the additional reliability change of component m considering the degradation dependency of component n.

[0063] Similarly, the reliability of component n in the well control equipment control system of offshore oil and gas development at time t k is Rn(t k ), and the reliability of component n at time t k+1 is Rn(t k+1 ). The reliability of component n at time t k+1 satisfies: ;

[0064] where ΔRn(t k+1 ) is the reliability change of component n between time t k and time t k+1 .

[0065] Considering the influence of the degradation dependency between components, ΔRn(t k+1 ) satisfies: ;

[0066] where ΔRnn(t k+1 ) represents the reliability change of component n itself, and ΔRnm(t k+1 ) represents the additional reliability change of component n considering the degradation dependency of component m.

[0067] Then, the degradation dependency between components in the well control equipment control system of offshore oil and gas development is considered:

[0068] Since the components in the well control equipment control system of offshore oil and gas development are mainly electronic components, it is assumed that the inherent reliability degradation of the components obeys the exponential degradation law, i.e., the reliability of the components between time t k and time t k+1 satisfies: ;

[0069] Taking component m as an example, ΔRmn(t k+1 ) represents the additional reliability change of component m considering the degradation dependency of component n, and satisfies: ;

[0070] where is the degradation dependency of component n on component m.

[0071] Considering the redundancy of components, the reliability of the well control equipment control system of offshore oil and gas development at time t k is R sys (t k ), and satisfies: ;

[0072] wherein R i (t k ) is the reliability of the ith component at time t k , cn is the total number of components of the offshore oil and gas development well control equipment control system, and ni is the redundancy level of the ith component.

[0073] Further considering that the offshore oil and gas development well control equipment control system will face various external impacts in the running process, such as typhoon, internal wave and other natural environmental disaster impact conditions that will significantly affect the reliability of the control system:

[0074] Suppose that the arrival time of the external impact event faced by the offshore oil and gas development well control equipment control system obeys a non-homogeneous Poisson process; then the probability of e k times of external impact occurring within the time period of 0 to t num satisfies: ;

[0075] wherein N(t k ) represents the total number of impact events occurring within the time period of [0, t k ]; N(t k+1 ) represents the total number of impact events occurring within the time period of [0, t k+1 ]; the variable a represents time; and λ(a) represents the instantaneous rate of external impact time at a specific time point a, and the intensity function of the non-homogeneous Poisson process is estimated based on historical impact event data.

[0076] It is worth noting that in this process, a person skilled in the art can establish a typhoon influence model and an internal wave influence model according to historical typhoon maximum wind speed, central air pressure and other data, as well as measured internal wave flow rate and other data, to estimate the influence degree of external impact on the control system. Since the occurrence of typhoon, internal wave and other natural disasters has randomness, a large number of possible impact scenarios are generated through Monte Carlo simulation, and then the influence degree distribution is calculated; on this basis, the location parameter, scale parameter and shape parameter in the generalized extreme value distribution are fitted through the maximum likelihood estimation method based on the Monte Carlo simulation data.

[0077] Suppose that the influence degree of external impact on the offshore oil and gas development well control equipment control system obeys a generalized extreme value distribution; wherein the cumulative distribution function of the generalized extreme value distribution satisfies: ;

[0078] wherein z(w) represents the intensity of the wth external impact; v is the location parameter, representing the central position of the generalized extreme value distribution; is the scale parameter, representing the scale position of the generalized extreme value distribution, and θ is the shape parameter.

[0079] In summary, the dynamic reliability of the well control equipment control system in the whole life cycle is comprehensively considered under the influence of the degradation dependence relationship and the cumulative external impact, and the following is obtained: 。

[0080] Step S2: evaluating the total cost of the well control equipment control system in the whole life cycle.

[0081] On the basis of completing step S1, step S2 is further implemented. As a more preferred embodiment provided by the present application, the process of evaluating the total cost of the well control equipment control system in the whole life cycle in step S2 specifically includes the following steps:

[0082] Step S2.1: constructing a reliability-cost function model.

[0083] The reliability-cost function model is specifically used to represent the relationship between reliability and cost, and includes the total amount of manpower, material resources and financial resources required when improving the reliability of the well control equipment control system. Further research shows that there is a monotonically increasing relationship between reliability and manufacturing cost, that is, the improvement of reliability is accompanied by the increase of system manufacturing cost. In particular, when the reliability value approaches its maximum value, the manufacturing cost will significantly rise to a very high level.

[0084] In this process, preferably, the reliability-cost function model C I constructed in step S2.1 satisfies: 。

[0085] Where f i is the manufacturing cost coefficient of the i th component; R i is the reliability of component i under the natural degradation condition in the given life cycle; R i,min is the initial reliability of component i; R i,max is the maximum value of the reliability of component i that can be theoretically achieved; a i and b i are the cost correction coefficients of component i, which are assumed by investigating the cost of each component.

[0086] Step S2.2: constructing a maintenance cost evaluation model.

[0087] It is worth noting that the purpose of constructing the maintenance cost evaluation model is to determine the maintenance strategy of the well control equipment control system and the maintenance cost of the well control equipment control system. According to the dynamic reliability evaluation results of the control system in the whole life cycle, the preventive maintenance strategy of the control system can be determined.

[0088] Specifically, when the control system reliability is greater than 0.95, it indicates that the control system is in a high reliability state, and no maintenance is required at this time; when the control system reliability is between 0.90 and 0.95, it indicates that the control system is in a general reliability state, and if the entire well control equipment is overhauled, the maintenance activity is performed; when the control system reliability is less than 0.90, it indicates that the control system is in a low reliability state, and immediate maintenance is required.

[0089] The control system maintenance cost includes downtime loss cost and maintenance resource cost. The maintenance resource cost further includes spare parts purchase cost, maintenance tool rental cost, and maintenance personnel employment cost, etc.

[0090] In this process, preferably, the maintenance cost evaluation model C M constructed in step S2.2 satisfies: 。

[0091] Wherein, N is the total number of maintenance of the control system of the offshore oil and gas development well control equipment in the whole life cycle, D M (x) is the time of the xth maintenance activity, C d is the downtime loss per unit time, C r is the maintenance resource cost per unit time.

[0092] Step S2.3: Based on the reliability-cost function model and the maintenance cost evaluation model, a total cost evaluation model of the control system of the offshore oil and gas development well control equipment in the whole life cycle is constructed.

[0093] On the basis of completing steps S2.1 and S2.2, step S2.3 is further implemented. The whole life cycle of the control system of the offshore oil and gas development well control equipment includes the design and manufacturing stage, the running stage and the maintenance stage. Therefore, the total cost evaluation model C all of the control system of the offshore oil and gas development well control equipment in the whole life cycle satisfies: 。

[0094] Step S3: Determine the reliability and redundancy integrated optimization target.

[0095] On the basis of completing step S2, step S3 is further implemented. It is worth noting that this step S3 intends to determine a reliability and redundancy integrated double target optimization target, the purpose of which is to maximize the reliability under the condition of natural degradation of the system while minimizing the total cost of the control system of the offshore oil and gas development well control equipment in the whole life cycle. Therefore, the reliability and redundancy integrated optimization target can be referred to as: 。

[0096] Step S4: constructing a reliability and redundancy integrated optimization model based on a multi-objective particle swarm optimization algorithm to obtain a Pareto optimal front solution of reliability and redundancy.

[0097] On the basis of completing step S3, step S4 is further implemented. In the process of constructing the reliability and redundancy integrated optimization model based on the multi-objective particle swarm optimization algorithm, the decision variable refers to the inherent failure rate and redundancy level of each component in the well control equipment control system of the offshore oil and gas development.

[0098] Step S5: selecting an optimal solution of the well control equipment control system of the offshore oil and gas development for the design of the system resilience by using a TOPSIS decision method from the Pareto optimal front solution.

[0099] On the basis of completing step S4, step S5 is further implemented. It should be pointed out that the TOPSIS decision method is the Technique for Order of Preference by Similarity to Ideal Solution, which balances the different emphases of reliability and cost in the optimization process of the well control equipment control system of the offshore oil and gas development, and realizes the purpose of selecting an optimal solution. Further, a dynamic weight adjustment mechanism is introduced, and a higher weight is given to reliability in the early stage of optimization. As the optimization proceeds, the cost weight can be gradually increased, so that the reliability and cost are optimized and decided, and the optimal control system resilience design is realized.

[0100] As a more preferred embodiment provided by the present application, the process of selecting an optimal solution of the well control equipment control system of the offshore oil and gas development for the design of the system resilience by using a TOPSIS decision method from the Pareto optimal front solution in step S5 specifically includes the following steps:

[0101] Step S5.1: evaluating the reliability and redundancy configuration of the well control equipment control system of the offshore oil and gas development according to the two evaluation indexes of system reliability and total cost in the whole life cycle to construct a decision matrix D.

[0102] The decision matrix D can be expressed as: 。

[0103] Wherein, R sys (n) is the system reliability of the nth scheme, and Call(n) is the corresponding total cost.

[0104] Step S5.2: normalizing the decision matrix D.

[0105] The purpose of normalizing the decision matrix D is to eliminate the differences between the dimensions.

[0106] Step S5.3: dynamically adjusting the reliability and cost weight; and weighting the normalized decision matrix D using the dynamically adjusted weight.

[0107] On the basis of completing step S5.2, step S5.3 is further implemented. In order to reflect the different emphases of the offshore oil and gas development well control equipment control system on reliability and cost, a dynamic adjustment mechanism of reliability and cost weight is further introduced. Specifically, the initial weight is set as ω0=[ω R (0),ω C (0)]. R (0)<ω C (0) indicates that, in the initial stage of reliability and redundancy allocation decision, more attention is paid to reliability. The final weight is set as ω T =[ω R (T),ω C (T)]. Wherein, ω R (T)<ω C (T) indicates that, in the later stage of reliability and redundancy allocation decision, more attention is paid to cost. T is the number of iterations.

[0108] With the increase of the number of iterations, the weight gradually transits from the initial state to the final state. In the tth iteration, the dynamic weight adjustment formula is represented as: Then, the normalized decision matrix D can be weighted using the dynamically adjusted weight.

[0109] Step S5.4: determining the ideal solution and the negative ideal solution. The ideal solution (denoted as A+) is the solution of maximizing reliability and minimizing cost, and the negative ideal solution (denoted as A-) is the solution of minimizing reliability and maximizing cost.

[0110] Step S5.5: calculating the distance of each solution from the ideal solution and the negative ideal solution. The distance of each solution from the ideal solution A+ is represented as S+, and the distance of each solution from the negative ideal solution A- is represented as S-.

[0111] Step S5.6: calculating the relative closeness of each solution, and sorting to obtain the optimal solution.

[0112] On the basis of completing steps S5.4 and S5.5, step S5.6 is further implemented. The relative closeness CL i of the ith solution is represented as .

[0113] S i + is the distance of the ith solution from the ideal solution A+, and S i -The distance of the i-th scheme and the negative ideal solution A-. Wherein, the greater the value of the closeness, the closer the scheme to the ideal solution. Therefore, according to the calculated relative closeness, the various schemes are sorted, that is, the optimal solution is selected by sorting the scheme with the highest closeness, so as to realize the optimal configuration of the reliability and redundancy of the well control equipment control system of the offshore oil and gas development, and the resilience design.

[0114] The application provides a resilience design method for a well control equipment control system of offshore oil and gas development.

[0115] The resilience design method for the well control equipment control system of offshore oil and gas development has at least the following technical advantages compared with the prior art.

[0116] 1. The resilience design method for the well control equipment control system of offshore oil and gas development provided by the application takes the well control equipment control system of offshore oil and gas development as an engineering background, takes the whole life cycle as a design optimization time scale, comprehensively considers the comprehensive influence of natural degradation and external impact of the well control equipment control system, and realizes the maximization of reliability and the minimization of total cost in the whole life cycle by combining the dynamic reliability, redundancy and maintenance strategy of the whole life cycle, so as to guarantee the anti-impact ability of the well control equipment control system of offshore oil and gas development under external impact.

[0117] 2. The resilience design method for the well control equipment control system of offshore oil and gas development provided by the application avoids the extreme situation of failure of the well control equipment control system of offshore oil and gas development to the greatest extent, realizes the optimal design of the resilience of the well control equipment control system of offshore oil and gas development based on the integrated optimization mechanism of reliability and redundancy by fully considering the cost-performance constraint relationship between the reliability and the redundancy.

[0118] The above description is only a specific embodiment of the application, but the protection scope of the application is not limited to this. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the application, which should be covered in the protection scope of the application. Therefore, the protection scope of the application should be subject to the protection scope of the claims.

Claims

1. A resilience design method for the control system of well control equipment in offshore oil and gas development, characterized in that, The steps include the following: Step S1: Evaluate the dynamic reliability of the control system of offshore oil and gas development well control equipment throughout its entire life cycle; Step S2: Evaluate the total cost of the well control equipment control system for offshore oil and gas development over its entire life cycle; Step S3: Determine the integrated optimization objective for reliability and redundancy; Step S4: Construct an integrated reliability and redundancy optimization model based on the multi-objective particle swarm optimization algorithm to obtain the Pareto optimal front solution for reliability and redundancy; Step S5: Using the TOPSIS decision method, select the optimal solution for the resilience design of the control system of well control equipment for offshore oil and gas development from the Pareto optimal frontier solution; The process of evaluating the dynamic reliability of the offshore oil and gas development well control equipment control system throughout its entire life cycle in step S1 is specifically described as follows: Under natural degradation conditions, suppose a component m in the well control system of offshore oil and gas development experiences a degradation of t. k The reliability at time t is Rm(t) k ), then t k+1 Reliability at time Rm(t) k+1 ),satisfy: ; Wherein, ΔRm(t) k+1 ) for t k+1 Time and t k The change in the reliability of component m over time; Considering the impact of degradation dependencies between components, ΔRm(t) k+1 ),satisfy: ; Wherein, ΔRmm(t) k+1 ) represents the inherent reliability variation of component m itself, ΔRmn(t) k+1 This indicates the additional reliability change resulting from considering the degradation dependency of component n on component m; Similarly, in the control system of well control equipment for offshore oil and gas development, a certain component n is in t k The reliability at time t is Rn(t) k ), then t k+1 Reliability at time Rn(t) k+1 ),satisfy: ; Wherein, ΔRn(t) k+1 ) for t k+1 Time and t k The change in reliability of component n over time; Considering the impact of degradation dependencies between components, ΔRn(t) k+1 ),satisfy: ; Wherein, ΔRnn(t) k+1 ) represents the inherent reliability variation of component n itself, ΔRnm(t) k+1 This indicates the additional reliability change resulting from considering the degradation dependency of component m on component n; Since the components in the control system of well control equipment for offshore oil and gas development are mainly electronic components, it is assumed that their inherent reliability degradation follows an exponential degradation law, i.e., t k The reliability of components at any given time must satisfy: ; Taking component m as an example, ΔRmn(t) represents the additional reliability change caused by considering the degradation dependence of component n on component m. k+1 ),satisfy: ; in, The degradation dependency of component n on component m; Considering component redundancy, the control system for offshore oil and gas development well control equipment is designed for t k Reliability R at any moment sys (t k ),satisfy: ; Among them, R i (t k ) represents the i-th component in t k The reliability at any given time, where cn is the total number of components in the control system of the well control equipment for offshore oil and gas development, and ni is the redundancy level of the i-th component; Assuming the arrival time of external shock events faced by the control system of offshore oil and gas development well control equipment follows a non-homogeneous Poisson process; then from 0 to t k During the time period, an external shock occurred. num The probability of this event satisfies: ; Wherein, N(t) k ) represents time [0, t] k The total number of shock events occurring within [ ]; N(t k+1 ) represents time [0, t] k+1 The total number of impact events occurring within a given time period; variable α represents time; λ(α) represents the instantaneous rate of the external impact at a specific time point α, and the intensity function of the non-homogeneous Poisson process is estimated based on historical impact event data; Assume that the impact of external shocks on the control system of well control equipment in offshore oil and gas development follows a generalized extreme value distribution; wherein the cumulative distribution function of the generalized extreme value distribution satisfies: ; Where z(w) represents the intensity of the w-th external impact; v is the location parameter, representing the central location of the generalized extreme value distribution; τ is the scale parameter, representing the scale location of the generalized extreme value distribution; and θ is the shape parameter. In summary, considering both the degradation dependency and the cumulative impact of external shocks, the dynamic reliability of the control system for offshore oil and gas development well control equipment throughout its entire lifecycle is as follows: .

2. The resilience design method for the control system of offshore oil and gas development well control equipment according to claim 1, characterized in that, The process of evaluating the total cost of the offshore oil and gas development well control equipment control system over its entire life cycle in step S2 specifically includes the following steps: Step S2.1: Construct a reliability-cost function model; Step S2.2: Construct a maintenance cost evaluation model; Step S2.3: Based on the reliability-cost function model and maintenance cost evaluation model, construct the total cost evaluation model of the marine oil and gas development well control equipment control system throughout its entire life cycle.

3. The resilience design method for the control system of offshore oil and gas development well control equipment according to claim 2, characterized in that, The reliability-cost function model C obtained in step S2.1 I ,satisfy: ; Among them, f i R is the manufacturing cost coefficient for the i-th component; i R represents the reliability of component i under natural degradation conditions over a given lifespan; i,min R represents the initial reliability of component i; i,max Let a be the theoretically maximum reliability performance achievable by component i; i and b i The cost correction factor for component i is given by conducting a survey of the costs of each component; The maintenance cost evaluation model C constructed in step S2.2 M ,satisfy: ; Where N represents the total number of maintenance operations for the well control equipment control system in offshore oil and gas development throughout its entire life cycle, and D... M (x) represents the time of the x-th maintenance activity, C d C represents the downtime loss per unit time. r This refers to the cost of maintenance resources per unit of time.

4. The resilience design method for the control system of offshore oil and gas development well control equipment according to claim 1, characterized in that, Step S5, which employs the TOPSIS decision-making method to select the optimal solution for the resilience design of the offshore oil and gas development well control equipment control system from the Pareto optimal frontier solution, specifically includes the following steps: Step S5.1: Based on the two evaluation indicators of system reliability and total life cycle cost, evaluate the reliability and redundancy configuration of the well control equipment control system for offshore oil and gas development, and construct the decision matrix D; Step S5.2: Normalize the decision matrix D; Step S5.3: Dynamically adjust the reliability and cost weights; use the dynamically adjusted weights to weight the normalized decision matrix D; Step S5.4: Determine the ideal solution and the negative ideal solution; where the ideal solution is the solution that maximizes reliability and minimizes cost, and the negative ideal solution is the solution that minimizes reliability and maximizes cost; Step S5.5: Calculate the distance between each solution and the ideal solution and the negative ideal solution; Step S5.6: Calculate the relative similarity of each solution and sort them to obtain the optimal solution.

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