FPSO installation operation risk analysis method

Abstract

The invention relates to the technical field of petroleum ocean engineering risk prediction, in particular to an FPSO (Floating Production Storage and Offloading) installation operation risk analysis method, which comprises the following steps of: establishing a fault tree of each installation operation process; determining an evaluation index of each installation operation process risk item to form a comprehensive evaluation model; obtaining a risk assessment score of each key factor of each evaluation index, and calculating a weight of each evaluation index and an evaluation index coordination degree; performing defuzzification on the comprehensive fuzzy function to obtain a fuzzy failure probability of the basic event; the fuzzy failure probability of the basic event is substituted into the FPSO installation operation fault tree, the minimum cut set probability is obtained, and then the top event probability is obtained; and identifying high-risk items according to the top event probability, and putting forward management and control measures. According to the method provided by the invention, the risk of the FPSO installation operation can be reduced, and the safety of the FPSO installation operation is improved.

Description

Technical Field

[0001] The invention relates to the technical field of risk prediction of petroleum marine engineering, and in particular to a FPSO installation operation risk analysis method. Background Art

[0002] At present, the degree of offshore oil and gas exploitation is relatively low, especially in the deep sea. Due to the difficulty of exploitation and high operational risks, there are a large number of deep-sea oil and gas resources that need to be exploited. FPSO, also known as floating production storage and offloading unit, plays a vital role in the development of important resources such as offshore oil and natural gas, and is becoming the mainstream equipment for countries to develop oil and gas resources at different water depths.

[0003] FPSO installation operations are subject to great risks due to the particularity of the environment. Currently, the engineering risk assessment methods that are widely used usually require a large amount of statistical data on failure or accident instances, which is obviously difficult to achieve for marine engineering projects. People began to build FPSOs in the mid-1970s. It has been a short period of time, which makes it difficult to form a precise database of actual accidents. Therefore, it is difficult to accurately assess the risks of FPSO installation operations, which may affect the progress of FPSO installation operations or cause serious safety accidents. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a FPSO installation operation risk analysis method, which can reduce the risk of FPSO installation operations and improve the safety of FPSO installation operations.

[0005] The present invention is achieved through the following technical solutions: A method for risk analysis of FPSO installation operations comprises the following steps: S1: Analyze each installation operation process of FPSO, identify the risk items of each installation operation process, and establish a fault tree for each installation operation process; S2: Based on the collected specific information of key factors of each evaluation index of historical projects, determine the evaluation index of each installation operation process risk item, analyze the influence of key factors affecting each evaluation index, and form a comprehensive evaluation model; S3: Input the specific information of the key factors of each evaluation indicator of the specific project to be analyzed into the comprehensive evaluation model, obtain the risk assessment score of each key factor of each evaluation indicator, determine the importance of each key factor to the evaluation indicator through the hierarchical analysis method, calculate the weight of each evaluation indicator, and calculate the risk assessment consistency, average consistency and relative consistency of each evaluation indicator, integrate the weight of each evaluation indicator and the risk assessment consistency, average consistency and relative consistency of each evaluation indicator, and obtain the coordination degree of the evaluation indicator; S4: Use the fuzzy membership function to defuzzify the comprehensive fuzzy function according to the risk assessment scores of each key factor of the evaluation index and the coordination degree of each evaluation index, and then obtain the fuzzy failure probability of the basic event; S5: Substitute the fuzzy failure probability of the basic event into the fault tree of each installation operation process to obtain the minimum cut set probability, and then obtain the top event probability; S6: Take control measures for the basic events in the minimum cut set whose top event probability exceeds the acceptable failure probability.

[0006] Optimized, the FPSO installation operation process in step S1 includes a mooring system installation process, a new hull part installation process, an underwater production equipment installation process, an unloading system installation process and a supporting system installation process.

[0007] Optimized, the evaluation indicators in step S3 include marine environmental conditions, technical capabilities, cost control and material transportation, and the key factors of each evaluation indicator include installation period, project cost, staffing and accident rate.

[0008] Furthermore, in step S3, the weight of each evaluation index is calculated by the following method: S311: Conduct correlation analysis on the four key factors of installation cycle, project cost, staffing and accident rate, and calculate the correlation coefficient between each key factor and project success rate; S312: construct a judgment matrix according to the correlation coefficient between each key factor and the project success rate, calculate the importance of the relative relationship between the key factors, and assign values ​​to the judgment matrix according to the importance; S313: Divide each column of the judgment matrix by its sum, and convert the judgment matrix into a normalized matrix; S314: Calculate the average value of each row of the normalized matrix to obtain the weight of each key factor of each evaluation indicator; S315: Perform a weighted summation of the weight of each key factor in each evaluation indicator and the risk assessment score of the corresponding key factor to obtain the weight of the corresponding evaluation indicator.

[0009] Optimized, the importance of the relative relationship of the key factors is the ratio of the corresponding correlation coefficients of the two key factors.

[0010] Further, in step S3, the risk assessment consistency, average consistency and relative consistency of each evaluation indicator are calculated by the following method: S321: Take any two evaluation indicators as a combination, convert their risk assessment for a certain event into a trapezoidal fuzzy number, and calculate the risk assessment consistency of the combined evaluation indicators according to formula (1): , until the risk assessment consistency of all combined evaluation indicators is completed: (1); in: Indicates the first evaluation indicator in the combination The trapezoidal fuzzy number of parameter, Represents the second evaluation index in the combination The trapezoidal fuzzy number of parameter, Indicates the first evaluation indicator in the combination The trapezoidal fuzzy number of Represents the second evaluation index in the combination Trapezoidal fuzzy number of ; S322: Calculate the average consistency of the evaluation index according to formula (2) : (2); in: represents the number of evaluation index combinations, Indicates the serial number of the evaluation index combination, Indicates The consistency of risk assessment for a combination of evaluation indicators; S323: Calculate the relative consistency of the evaluation index according to formula (3) : (3); in: Indicates The consistency of risk assessment of a combination of evaluation indicators.

[0011] Further, in step S3, the coordination degree of the evaluation index is calculated according to formula (4): : (4); in: represents the adjustment factor, Represents the weight of the evaluation index.

[0012] Further, in step S4, the fuzzy failure probability of the basic event is obtained according to the following method: S41: Calculate the risk assessment score of each evaluation indicator according to the risk assessment score of the key factor of each evaluation indicator, then calculate the score rate of each evaluation indicator, and obtain the fuzzy number of each evaluation indicator according to the score rate of each evaluation indicator and the trapezoidal fuzzy number, and perform weighted summation of the fuzzy number of each evaluation indicator and the coordination degree of the evaluation indicator to obtain a comprehensive fuzzy number; S42: Convert the comprehensive fuzzy number into the fuzzy possibility score as formula (5): (5); in: represents the fuzzy likelihood score, It means calculating the score of the comprehensive fuzzy number in the maximum possible interval. It means calculating the score of the comprehensive fuzzy number in the smallest possible interval; S43: Obtain the fuzzy failure probability of the basic event according to formula (6) through the fuzzy possibility score : (6); in: Represents the fuzzy failure probability adjustment factor.

[0013] Furthermore, in step S5, the minimum cut set probability is calculated according to formula (7): (7); in: Indicates The minimum cut set probability, Indicates A minimal cut set, Indicates The basic events contained in the minimum cut set The fuzzy failure probability, Indicates The basic events contained in the minimum cut set The fuzzy failure probability.

[0014] Further, in step S5, the top event probability is calculated according to formula (8): : in: Represents the total number of minimum cut sets.

[0015] Beneficial effects of the invention: The present invention provides a FPSO installation operation risk analysis method. The FPSO installation operation process is studied in detail, risk items are identified, fault trees of various installation operation processes are established, and a comprehensive evaluation model is formed, thereby determining the weight of various evaluation indicators, integrating the weights of various evaluation indicators to obtain the coordination degree of the evaluation indicators, and then integrating the coordination degree of the evaluation indicators. The fuzzy failure probability of basic events is calculated through fuzzy theory to obtain the top event probability, and high-risk items are identified according to the top event probability, and safety criteria and acceptable failure probability are determined. Control measures are taken for basic events in the minimum cut set whose top event probability exceeds the acceptable failure probability, so that the calculated value of the top event probability is more credible, thereby reducing the risk of FPSO installation operations and improving the safety of FPSO installation operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0017] A method for risk analysis of FPSO installation operations, the flow diagram of which is as follows: Figure 1 As shown, the specific steps include: S1: Analyze each installation operation process of FPSO, identify the risk items of each installation operation process, and establish a fault tree for each installation operation process; The FPSO installation operation process here includes five parts: mooring system installation process, new hull installation process, underwater production equipment installation process, unloading system installation process and supporting system installation process.

[0018] The basic events of the mooring system installation process fault tree are shown in Table 1: Table 1

[0019] The basic events of the fault tree of the new hull installation process are shown in Table 2: Table 2

[0020] The basic events of the fault tree of the underwater production equipment installation process are shown in Table 3: Table 3

[0021] The basic events of the uninstall system installation process fault tree are shown in Table 4: Table 4

[0022] The basic events of the supporting system installation process fault tree are shown in Table 5: Table 5

[0023] S2: Collect specific information on key factors of each evaluation index of historical projects, determine the evaluation index of each installation operation process risk item, analyze the degree of influence of key factors affecting each evaluation index, and form a comprehensive evaluation model; The evaluation indicators of the risk items of each installation operation process include marine environmental conditions, technical capabilities, cost control and material transportation that affect the FPSO installation operation capability. The key factors of each evaluation indicator include installation cycle, project cost, staffing and accident rate. The importance of the relative relationship between the key factors is the ratio of the corresponding correlation coefficients of the two key factors.

[0024] S3: Input the specific information of the key factors of each evaluation indicator of the specific project to be analyzed into the comprehensive evaluation model, obtain the risk assessment score of each key factor of each evaluation indicator, determine the importance of each key factor to the evaluation indicator through the hierarchical analysis method, calculate the weight of each evaluation indicator, and calculate the risk assessment consistency, average consistency and relative consistency of each evaluation indicator, integrate the weight of each evaluation indicator and the risk assessment consistency, average consistency and relative consistency of each evaluation indicator, and obtain the coordination degree of the evaluation indicator; Specifically, the weight of each evaluation index can be calculated by the following method: S311: Conduct correlation analysis on the four key factors of installation cycle, project cost, staffing and accident rate, and calculate the correlation coefficient between each key factor and project success rate; S312: construct a judgment matrix according to the correlation coefficient between each key factor and the project success rate, calculate the importance of the relative relationship between the key factors, and assign values ​​to the judgment matrix according to the importance; Assuming that through correlation analysis, the correlation coefficient of installation cycle to project success is 0.45, and the correlation coefficient of staffing to project success is 0.16, then the contribution ratio of installation cycle to project cost is , rounding the comparison value, the relative importance of the installation period in the project cost can be assigned a value of 3. According to this method, the judgment matrix can be constructed as shown in Table 6: Table 6

[0025] S313: Divide each column of the judgment matrix by its sum, and convert the judgment matrix into a normalized matrix; The specific normalized matrix is ​​shown in Table VII: Table 7

[0026] S314: Calculate the average value of each row of the normalized matrix to obtain the weight of each key factor in each evaluation index.

[0027] The weights of key factors are shown in Table 8: Table 8

[0028] S315: Perform a weighted summation of the weight of each key factor in each evaluation indicator and the risk assessment score of the corresponding key factor to obtain the weight of the corresponding evaluation indicator.

[0029] The risk assessment scores of key factors are shown in Table 9: Table 9

[0030] Specifically, the risk assessment consistency, average consistency and relative consistency of each evaluation indicator can be calculated by the following method: S321: Take any two evaluation indicators as a combination, convert their risk assessment for a certain event into a trapezoidal fuzzy number, and calculate the risk assessment consistency of the combined evaluation indicators according to formula (1): , until the risk assessment consistency of all combined evaluation indicators is completed: (1); in: Indicates the first evaluation indicator in the combination The trapezoidal fuzzy number of parameter, Represents the second evaluation index in the combination The trapezoidal fuzzy number of parameter, Indicates the first evaluation indicator in the combination The trapezoidal fuzzy number of Represents the second evaluation index in the combination Trapezoidal fuzzy number of ; S322: Calculate the average consistency of the evaluation index according to formula (2) : (2); in: represents the number of evaluation index combinations, Indicates the serial number of the evaluation index combination, Indicates The consistency of risk assessment for a combination of evaluation indicators; S323: Calculate the relative consistency of the evaluation index according to formula (3) : (3); in: Indicates The consistency of risk assessment of a combination of evaluation indicators.

[0031] Further, in step S3, the coordination degree of the evaluation index is calculated according to formula (4): : (4); in: represents the adjustment coefficient, which represents the combination of the evaluation index weight and the consistency of the evaluation index. ,when =0, the influence of each evaluation index weight is ignored, and the evaluation indexes are regarded as having the same weight; =1, it proves that the consistency of each evaluation index is ignored, and only the influence of the weight of each evaluation index on the evaluation is considered. Represents the weight of the evaluation index.

[0032] S4: Use the fuzzy membership function to defuzzify the comprehensive fuzzy function according to the risk assessment scores of each key factor of the evaluation index and the coordination degree of each evaluation index, and then obtain the fuzzy failure probability of the basic event; Further, in step S4, the fuzzy failure probability of the basic event is obtained according to the following method: S41: Calculate the risk assessment score of each evaluation indicator according to the risk assessment score of the key factor of each evaluation indicator, then calculate the score rate of each evaluation indicator, and obtain the fuzzy number of each evaluation indicator according to the score rate of each evaluation indicator and the trapezoidal fuzzy number, and perform weighted summation of the fuzzy number of each evaluation indicator and the coordination degree of the evaluation indicator to obtain a comprehensive fuzzy number; First, the risk assessment score of each evaluation indicator is equal to the sum of the risk assessment scores of the key factors of the evaluation indicator; the risk assessment score of each evaluation indicator is divided by the full score of the risk assessment of each evaluation indicator to obtain the score rate of each evaluation indicator; The form of trapezoidal fuzzy number is: : Represents the lower left boundary, indicating the minimum value of the fuzzy number, which means the minimum possibility of the event occurring.

[0033] Represents the upper left boundary, indicating the starting point of the fuzzy number possibility, and the event begins to have a greater possibility of occurring.

[0034] Represents the upper right boundary, indicating the maximum interval of fuzzy number possibility and the area where the event is most likely to occur.

[0035] Represents the lower right boundary, indicating the end point of the fuzzy number, where the probability of the event occurring tends to zero.

[0036] Specifically, assume that the evaluation values ​​of the key factors of the evaluation indicators are: The installation cycle is , the project cycle is , staffing is The accident rate is , the full score of each key factor is 10 points, so the score rate of this evaluation index is for , so the fuzzy number of the evaluation index is ( , , , ).

[0037] Assume that two evaluation indicators (A1, A2) are used for evaluation. The fuzzy numbers of the two evaluation indicators for basic events are: =(0.1,0.2,0.2,0.3), = (0, 0, 0.1, 0.2), assuming that the coordination degree of evaluation index A1 is 0.3 and the coordination degree of evaluation index A2 is 0.2, then the transformed is 0.3×(0.1,0.2,0.2,0.3)=(0.3,0.6,0.6,0.9), after conversion is 0.2×(0.1,0.2,0.2,0.3)=(0.2,0.4,0.4,0.6), then the final comprehensive fuzzy number is is (0.5, 1.0, 1.0, 1.5).

[0038] S42: Convert the comprehensive fuzzy number into the fuzzy possibility score as formula (5): (5); in: represents the fuzzy likelihood score, It means calculating the score of the comprehensive fuzzy number in the maximum possible interval. It means calculating the score of the comprehensive fuzzy number in the smallest possible interval; Here It can be calculated by the following formula: ; in: Represents the membership function of the comprehensive fuzzy number. ,have ; represents the independent variable of the membership function of the comprehensive fuzzy number, , It means taking the minimum value of two function values. It means taking the maximum value of the function. Indicates taking the absolute value, represents the fuzzy maximum set, ; by Taking (0.5, 1.0, 1.0, 1.5) as an example, then .

[0039] It can be calculated by the following formula: ; Among them: indicates Fuzzy minimal set, .

[0040] S43: Obtain the fuzzy failure probability of the basic event according to formula (6) through the fuzzy possibility score : (6); in: represents the fuzzy failure probability adjustment factor, .

[0041] S5: Substitute the fuzzy failure probability of the basic event into the fault tree of each installation operation process to obtain the minimum cut set probability, and then obtain the top event probability; The basic events described here are the basic events that lead to top events in the system, such as equipment failure, human operation errors, etc.

[0042] The top event is the most serious event in the system, usually indicating the failure or accident of the entire FPSO system. The top event is caused by a combination of several basic events.

[0043] The minimum cut set is the smallest set of basic events in the fault tree, so that when these events occur simultaneously, the top event will occur. The minimum cut set is the smallest combination that causes system failure. The fewer events in the cut set, the lower the reliability of the system.

[0044] Furthermore, in step S5, the minimum cut set probability is calculated according to formula (7): (7); in: Indicates The minimum cut set probability, Indicates A minimal cut set, Indicates The basic events contained in the minimum cut set The fuzzy failure probability, Indicates The basic events contained in the minimum cut set The fuzzy failure probability.

[0045] Further, in step S5, the top event probability is calculated according to formula (8): : in: Represents the total number of minimum cut sets.

[0046] S6: Take control measures for the basic events in the minimum cut set whose top event probability exceeds the acceptable failure probability. For optimization, the acceptable failure probability is less than or equal to 0.1%.

[0047] The present invention provides a FPSO installation operation risk analysis method. The method includes conducting a detailed study on the FPSO installation operation process, identifying risk items, establishing fault trees for each installation operation process, and forming a comprehensive evaluation model, thereby determining the weight of each evaluation index, and then integrating the weight of each evaluation index to obtain the coordination degree of the evaluation index. The coordination degree of the evaluation index is then integrated, and the fuzzy failure probability of the basic event is calculated by fuzzy theory to obtain the top event probability. High-risk items are identified according to the top event probability, safety criteria and acceptable failure probability are determined, and control measures are taken for the basic events in the minimum cut set whose top event probability exceeds the acceptable failure probability, so that the calculated value of the top event probability is more credible, thereby reducing the risk of the FPSO installation operation and improving the safety of the FPSO installation operation.

[0048] In summary, the present invention provides a method for risk analysis of FPSO installation operations. The calculated value of the top event probability is relatively credible. By taking control measures on the basic events in the minimum cut set whose top event probability exceeds the acceptable failure probability, the risk of FPSO installation operations can be reduced and the safety of FPSO installation operations can be improved.

[0049] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A FPSO installation operation risk analysis method, characterized in that: The steps include: S1: Analyze each installation operation process of FPSO, identify the risk items of each installation operation process, and establish a fault tree for each installation operation process; S2: Based on the collected specific information of key factors of each evaluation index of historical projects, determine the evaluation index of each installation operation process risk item, analyze the influence of key factors affecting each evaluation index, and form a comprehensive evaluation model; S3: Input the specific information of the key factors of each evaluation indicator of the specific project to be analyzed into the comprehensive evaluation model, obtain the risk assessment score of each key factor of each evaluation indicator, determine the importance of each key factor to the evaluation indicator through the hierarchical analysis method, calculate the weight of each evaluation indicator, and calculate the risk assessment consistency, average consistency and relative consistency of each evaluation indicator, integrate the weight of each evaluation indicator and the risk assessment consistency, average consistency and relative consistency of each evaluation indicator, and obtain the coordination degree of the evaluation indicator; S4: Use the fuzzy membership function to obtain the comprehensive fuzzy number according to the risk assessment scores of each key factor of the evaluation index and the coordination degree of each evaluation index, and then defuzzify the comprehensive fuzzy function to obtain the fuzzy failure probability of the basic event; S5: Substitute the fuzzy failure probability of the basic event into the fault tree of each installation operation process to obtain the minimum cut set probability, and then obtain the top event probability; S6: Take control measures for the basic events in the minimum cut set whose top event probability exceeds the acceptable failure probability.

2. A FPSO installation operation risk analysis method according to claim 1, characterized in that: The FPSO installation operation process in step S1 includes a mooring system installation process, a new hull installation process, an underwater production equipment installation process, an unloading system installation process and a supporting system installation process.

3. A FPSO installation operation risk analysis method according to claim 1, characterized in that: The evaluation indicators in step S3 include marine environmental conditions, technical capabilities, cost control and material transportation, and the key factors of each evaluation indicator include installation cycle, project cost, staffing and accident rate.

4. A FPSO installation operation risk analysis method according to claim 1, characterized in that: In step S3, the weight of each evaluation index is determined by the following method: S311: Conduct correlation analysis on the four key factors of installation cycle, project cost, staffing and accident rate, and calculate the correlation coefficient between each key factor and project success rate; S312: construct a judgment matrix according to the correlation coefficient between each key factor and the project success rate, calculate the importance of the relative relationship between the key factors, and assign values ​​to the judgment matrix according to the importance; S313: Divide each column of the judgment matrix by its sum, and convert the judgment matrix into a normalized matrix; S314: Calculate the average value of each row of the normalized matrix to obtain the weight of each key factor of each evaluation indicator; S315: Perform a weighted summation of the weight of each key factor in each evaluation indicator and the risk assessment score of the corresponding key factor to obtain the weight of the corresponding evaluation indicator.

5. A FPSO installation operation risk analysis method according to claim 4, characterized in that: The importance of the relative relationship between key factors is the ratio of the correlation coefficients of the two key factors.

6. The FPSO installation operation risk analysis method according to claim 1, characterized in that: In step S3, the risk assessment consistency, average consistency and relative consistency of each evaluation indicator are calculated by the following method: S321: Take any two evaluation indicators as a combination, convert their risk assessment for a certain event into a trapezoidal fuzzy number, and calculate the risk assessment consistency of the combined evaluation indicators according to formula (1): , until the risk assessment consistency of all combined evaluation indicators is completed: （1）； in: Indicates the first evaluation indicator in the combination The trapezoidal fuzzy number of parameter, Represents the second evaluation index in the combination The trapezoidal fuzzy number of parameter, Indicates the first evaluation indicator in the combination The trapezoidal fuzzy number of Represents the second evaluation index in the combination Trapezoidal fuzzy number of ; S322: Calculate the average consistency of the evaluation index according to formula (2) : （2）； in: represents the number of evaluation index combinations, Indicates the serial number of the evaluation index combination, Indicates The consistency of risk assessment for a combination of evaluation indicators; S323: Calculate the relative consistency of the evaluation index according to formula (3) : （3）； in: Indicates The consistency of risk assessment of a combination of evaluation indicators.

7. A FPSO installation operation risk analysis method according to claim 6, characterized in that: In step S3, the coordination degree of the evaluation index is calculated according to formula (4): : （4）； in: represents the adjustment factor, Represents the weight of the evaluation index.

8. A FPSO installation operation risk analysis method according to claim 7, characterized in that: In step S4, the fuzzy failure probability of the basic event is obtained as follows: S41: Calculate the risk assessment score of each evaluation indicator according to the risk assessment score of the key factor of each evaluation indicator, then calculate the score rate of each evaluation indicator, and obtain the fuzzy number of each evaluation indicator according to the score rate of each evaluation indicator and the trapezoidal fuzzy number, and perform weighted summation of the fuzzy number of each evaluation indicator and the coordination degree of the evaluation indicator to obtain a comprehensive fuzzy number; S42: Convert the comprehensive fuzzy number into the fuzzy possibility score as formula (5): (5)； in: represents the fuzzy likelihood score, It means calculating the score of the comprehensive fuzzy number in the maximum possible interval. It means calculating the score of the comprehensive fuzzy number in the smallest possible interval; S43: Obtain the fuzzy failure probability of the basic event according to formula (6) through the fuzzy possibility score : （6）； in: Represents the fuzzy failure probability adjustment factor.

9. A FPSO installation operation risk analysis method according to claim 8, characterized in that: In step S5, the minimum cut set probability is calculated according to formula (7): (7)； in: Indicates The minimum cut set probability, Indicates A minimal cut set, Indicates The basic events contained in the minimum cut set The fuzzy failure probability, Indicates The basic events contained in the minimum cut set The fuzzy failure probability.

10. A FPSO installation operation risk analysis method according to claim 9, characterized in that: In step S5, the top event probability is calculated according to formula (8): : in: Represents the total number of minimum cut sets.

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