A method for predicting the failure of dynamic equipment in a surface injection and production system for a salt cavern gas storage facility.

Abstract

This invention relates to a method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility, comprising the following steps: (1) Identifying the operating characteristics of the moving equipment in the surface injection and production system of the salt cavern gas storage facility, including skid-mounted operation, cyclical operation, and frequent human intervention, and classifying failure events into mechanical failures and human-induced failures based on these operating characteristics; (2) Calculating the failure probability of mechanical failures using a general failure probability method, combined with correction coefficients for skid-mounted and cyclical operation characteristics; (3) Analyzing the human factors of human error from aspects such as organizational influence, supervisory influence, and prerequisites for unsafe behavior, thereby quantitatively calculating the failure probability of human factors. This invention can quantitatively calculate the probability of failure of moving equipment in a gas storage facility, providing a basis for the safe operation of the surface injection and production system of a salt cavern gas storage facility.

Description

Technical Field

[0001] This invention relates to a method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility, belonging to the field of safety assurance technology for salt cavern gas storage facilities, and particularly to a method for calculating the failure probability and assessing the failure risk of moving equipment in a surface injection and production system of a salt cavern gas storage facility. Background Technology

[0002] Salt cavern gas storage facilities are created by dissolving salt in underground salt layers with water to form cavities, into which commercial natural gas transported by long-distance pipelines is then injected for storage. Their primary functions are to ensure emergency gas supply and peak gas demand regulation for cities. Specifically, during periods of low downstream demand, surplus natural gas from long-distance pipelines is pressurized and injected into underground storage facilities; during peak demand periods, natural gas extracted from underground storage facilities is purified, dehydrated, and then transported back to the long-distance pipeline system to supply gas to users. The stable operation of salt cavern gas storage facilities is a crucial element in ensuring stable urban gas supply.

[0003] Typically, the gas storage process in salt cavern storage facilities involves numerous rotating equipment such as compressors and pumps driven by motors. These devices are not only directly related to the normal operation of processes like pressurization and brine injection / production, but also incur high repair costs in case of failure. Currently, determining the failure probability of moving equipment to assess its operational status and thus identify its safety is a crucial method for ensuring its safe operation.

[0004] However, there is currently no specific method for calculating the failure probability of dynamic equipment in salt cavern gas storage facilities. Most calculations are based on methods used for calculating the failure probability of static equipment in conventional gas storage stations. However, the failure factors of dynamic equipment in salt cavern gas storage facilities differ significantly from those of static equipment in conventional stations. For example, dynamic equipment is often skid-mounted, and the compact structure of skid-mounted equipment means that different internal faults can affect each other, increasing the probability of failure. Because gas storage facilities operate cyclically according to trunk line pressure and downstream gas demand, frequent start-ups and shutdowns of dynamic equipment can increase the probability of failure. Furthermore, unlike static equipment, dynamic equipment requires frequent periodic maintenance and human intervention, and human error further increases the factors contributing to failure. Traditional equipment failure probability calculation methods cannot consider these failure factors and are only applicable to a limited extent to calculating the failure probability of dynamic equipment in salt cavern gas storage facilities. This leads to inaccurate predictions of the failure probability of dynamic equipment in salt cavern gas storage facilities, hindering timely intervention and resulting in a higher risk of failure, posing a challenge to the safe and reliable operation of salt cavern gas storage facilities. Summary of the Invention

[0005] The purpose of this invention is to provide a method for predicting the failure of moving equipment in the surface injection and production system of a salt cavern gas storage facility, in order to solve the problem of inaccurate prediction of the failure probability of moving equipment in salt cavern gas storage facilities and the risk of failure.

[0006] To achieve the above objectives, the present invention includes:

[0007] An embodiment of the present invention provides a method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility. The method involves obtaining a general failure probability value for the corresponding equipment in the system; calculating a skid-mounting characteristic correction coefficient for the moving equipment based on its skid-mounting degree; calculating a periodic operation characteristic correction coefficient for the moving equipment based on its periodic operating frequency; and correcting the general failure probability value using the skid-mounting characteristic correction coefficient and the periodic operation characteristic correction coefficient to obtain a failure probability value caused by mechanical failure of the moving equipment.

[0008] Based on the failure events of the moving equipment caused by human factors, the probability value of failure caused by human factors of the moving equipment is quantitatively calculated.

[0009] The failure probability value caused by mechanical failure and the failure probability value caused by human factors are combined to obtain the failure probability value of the moving equipment.

[0010] Based on the failure probability value of the moving equipment, the failure of the moving equipment is predicted.

[0011] The method of this invention calculates the failure probability of dynamic equipment in salt cavern gas storage facilities, taking into account their characteristics such as skid-mounted design, cyclic operation, and frequent human intervention, thereby improving the accuracy of failure prediction for dynamic equipment in salt cavern gas storage facilities.

[0012] Furthermore, the general failure probability value is obtained through a failure database.

[0013] Furthermore, the failure database is the OREDA datasheet.

[0014] Furthermore, the failure probability value Pmechanical caused by mechanical failure of the moving equipment is obtained by correcting the general failure probability value as follows:

[0015] P 机械 =gff total ·F 撬装 ·F 周期

[0016] Wherein, gfftotal is the general failure probability value, Fskid refers to the skid-mounted characteristic correction coefficient, and Fcycle is the cycle operation characteristic correction coefficient.

[0017] Furthermore, the human factors include four levels of influence: organizational influence, supervisory influence, prerequisites for unsafe acts, and unsafe acts themselves. Based on the principle of addition, the probability value of failure caused by human factors is calculated by dividing the number of times each of the four human factors has occurred or been clearly identified as the cause of an accident within a maintenance cycle by the maintenance cycle as the frequency of occurrence.

[0018] Furthermore, the probability value of equipment failure caused by human factors is quantitatively calculated using the fault tree method.

[0019] Furthermore, the failure probability value P is:

[0020] P = P 机械 +P 人因

[0021] Where Pmechanical represents the failure probability caused by mechanical malfunction, and Phuman represents the failure probability caused by human factors.

[0022] Furthermore, by dividing the failure probability value P of the actual failure of the ground injection and production system of the salt cavern gas storage into intervals based on historical data, the equipment whose calculated failure probability value falls into the set interval is predicted to be the equipment that is about to fail, thus realizing the prediction of the failure of the equipment.

[0023] The present invention provides a quantitative calculation method for the failure probability of active equipment in salt cavern gas storage facilities. Based on the operating characteristics of active equipment in salt cavern gas storage facilities, this method improves the factors that contribute to the failure of such equipment and solves the problem that conventional risk assessment methods cannot be applied to the calculation of the failure probability of active equipment in salt cavern gas storage facilities. Based on the characteristics of active equipment in salt cavern gas storage facilities, this invention proposes a method for calculating the failure probability.

[0024] This invention presents a clear and concise method for quantitatively calculating the failure probability of moving equipment in a surface injection and production system for salt cavern gas storage. It identifies the influencing factors of moving equipment failure events in salt cavern gas storage and achieves quantitative calculation of their failure probabilities. By analyzing the operational characteristics of salt cavern gas storage, including skid-mounted construction, cyclical operation, and frequent human intervention, this invention categorizes moving equipment failure events into two types: mechanical failures and human factors. It also considers the increased probability of mechanical failures due to the characteristics of skid-mounted construction and cyclical operation, thus addressing the problem that conventional risk assessment methods fail to consider these operational characteristics of salt cavern gas storage, thereby underestimating the failure probability of moving equipment. The calculation method in this invention further improves the accuracy of predicting moving equipment failures in salt cavern gas storage. Attached Figure Description

[0025] Figure 1 This is a schematic diagram illustrating the concept of calculating the failure probability of dynamic equipment in the surface injection and production system of the salt cavern gas storage facility according to the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0027] This invention aims to provide a method for predicting the failure of moving equipment in the surface injection and production system of a salt cavern gas storage facility. It addresses the problem that conventional failure probability calculation and prediction methods are not applicable due to the operating characteristics of the moving equipment in the injection and production system of a salt cavern gas storage facility. By calculating the failure probability, the invention can quickly identify dangerous moving equipment at the gas storage site and carry out timely maintenance and repair work, ultimately ensuring the safe operation of the salt cavern gas storage facility.

[0028] This invention is achieved through the following technical solution:

[0029] This invention discloses a method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility, such as... Figure 1 As shown, the specific steps include:

[0030] Step 1: For failure events caused by mechanical failures of moving equipment, based on the general failure probabilities of moving equipment from domestic and international equipment failure databases, and considering characteristics such as skid-mounted and periodic operation, adjustments are made to calculate the failure probability value caused by mechanical failures of the moving equipment. The calculation formula is P. 机械 =gff total ·F 撬装 ·F 周期 ;

[0031] Among them, P 机械 This refers to the failure probability value caused by mechanical failure of the moving equipment in a salt cavern gas storage facility.

[0032] gff total The general failure probability value for manual equipment can be obtained from failure databases such as OREDA (Reliability Data Sheet for Land and Marine Equipment).

[0033] F 撬装 The skid-mounted characteristic correction coefficient measures the increase in failure probability caused by the correlation between failures in skid-mounted equipment. The value range is [1, 5]. The degree of skid-mounting is divided into 5 levels. Experts score the level between 1 and 5. A score of 1 indicates that the failures of skid-mounted equipment are not correlated, while a score of 5 indicates that the failures of skid-mounted equipment are completely correlated. The average value is taken as the skid-mounted characteristic correction coefficient of the equipment after scoring by more than 10 experts.

[0034] F 周期 The periodic operation characteristic correction coefficient measures the increased probability of failure caused by frequent equipment start-ups and shutdowns, with a value range of [1, 10]. Periodic operation characteristics are divided into 10 levels, scored by experts between 1 and 10. A score of 1 indicates no start-ups or shutdowns during a maintenance cycle, while a score of 10 indicates high-frequency start-ups and shutdowns during a maintenance cycle. The average score from at least 10 experts is used as the periodic operation characteristic correction coefficient for the equipment.

[0035] Step 2: For failure events caused by human factors such as human error, a human factor can be divided into four levels of influence: organizational influence, supervisory influence, prerequisites for unsafe behavior, and unsafe behavior. According to the principle of addition, based on the number of times each of the four different factors has occurred or been clearly identified as the cause of the accident within a maintenance cycle, the frequency of occurrence is calculated by dividing the number of occurrences by the maintenance cycle. The probability value of equipment failure caused by human factors is then obtained.

[0036] Step 3: Based on the operating characteristics of the moving equipment in salt cavern gas storage facilities, failure events can be categorized into failures caused by mechanical faults and failures caused by human factors. Therefore, the failure probability of the moving equipment can be calculated using the formula P = P 机械 +P 人因 Perform the calculation.

[0037] Wherein, P refers to the failure probability value of the active equipment in the salt cavern gas storage facility;

[0038] P 机械 The probability of mechanical failure of moving equipment in salt cavern gas storage facilities caused by factors such as skid-mounted design and cyclic operation.

[0039] P 人因 This refers to the probability of failure of the active equipment in a salt cavern gas storage facility due to human factors such as misoperation.

[0040] The failure probability value of the moving equipment is divided into intervals. The highest 80% of the failure probability values ​​of the truly failed equipment in the historical data are used as the failure warning interval. Based on the calculated failure probability of the moving equipment, if it falls into the failure warning interval, an early warning prompt is issued to the operation and maintenance personnel for prevention and maintenance. This realizes the failure prediction of the moving equipment in the surface injection and production system of the salt cavern gas storage.

[0041] The following example illustrates the method for predicting the failure of moving equipment in the surface injection and production system of a salt cavern gas storage facility according to the present invention.

[0042] This embodiment uses a compressor in a ground station of a salt cavern gas storage facility as an example to introduce the method of the present invention. This compressor is a reciprocating compressor skid-mounted with a maximum start-stop frequency of 4 times / month. Due to its skid-mounted characteristics and frequent start-stop cycles caused by cyclical operation, mechanical failure events may occur. Furthermore, the compressor undergoes numerous routine maintenance operations, which may lead to equipment failure events caused by human error. Therefore, a failure event model is established that considers both mechanical failures and human factors. Based on existing failure databases, its general failure probability value is known to be 1.57 × 10⁻⁶. -5 Using the above method, the correction coefficient for skid-mounted characteristics is 1.2, the correction coefficient for periodic operation characteristics is 3.0, and the probability value P of equipment failure caused by human factors is obtained. 人因 1.36×10-5 The failure probability of the compressor was quantitatively calculated.

[0043] Step 1: Calculate the failure probability value caused by mechanical failure of the moving equipment. Use the formula P 机械 =gff total ·F 撬装 ·F 周期 The known general failure probability value is 1.57 × 10⁻⁶. -5 F 撬装 The value is 1.2, F 周期 The value is 3.0, and P is calculated. 机械 It is 5.65×10 -5 Therefore, under the characteristics of skid-mounted and cyclic operation, the probability of mechanical failure of this compressor is 0.00565%.

[0044] Step 2: Calculate the probability of compressor failure caused by human factors such as human error. From the known data, the probability of compressor failure caused by human factors such as human error is 0.00136%.

[0045] Step 3: Calculate the failure probability of the compressor in the salt cavern gas storage tank using the formula P = P 机械 +P 人因 Combining steps one and two, the failure probability of this compressor is 7.01 × 10⁻⁶. -5 Given the characteristics of this compressor—skid-mounted design, cyclical operation, and frequent personnel intervention—its failure probability is 0.00701%.

[0046] The present invention provides a quantitative calculation method for the failure probability of active equipment in salt cavern gas storage facilities. Based on the operating characteristics of active equipment in salt cavern gas storage facilities, this method improves the factors that contribute to the failure of such equipment and solves the problem that conventional risk assessment methods cannot be applied to the calculation of the failure probability of active equipment in salt cavern gas storage facilities. Based on the characteristics of active equipment in salt cavern gas storage facilities, this invention proposes a method for calculating the failure probability.

Claims

1. A method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility, characterized in that, Obtain the general failure probability value of the corresponding equipment in the surface injection and production system of the salt cavern gas storage; calculate the skid-mounting characteristic correction coefficient of the equipment based on its skid-mounting degree; and calculate the periodic operation characteristic correction coefficient of the equipment based on its periodic operating frequency; multiply the product of the skid-mounting characteristic correction coefficient and the periodic operation characteristic correction coefficient by the general failure probability value to obtain the failure probability value caused by mechanical failure of the equipment; the skid-mounting characteristic correction coefficient measures the increase in failure probability caused by the interrelationship between failures of skid-mounted equipment, and adopts an expert scoring method, taking the average value after scoring as the skid-mounting characteristic correction coefficient of the corresponding equipment; the periodic operation characteristic correction coefficient measures the increase in failure probability caused by frequent start-up and shutdown of the equipment, and adopts an expert scoring method, taking the average value after scoring as the periodic operation characteristic correction coefficient of the corresponding equipment; For equipment failure events caused by human factors, human factors can be divided into organizational influence, supervisory influence, prerequisites for unsafe acts, and unsafe acts. According to the addition principle, based on the number of times each of the four different factors has occurred or been explicitly mentioned for construction reasons within a maintenance cycle, the frequency of occurrence is calculated by dividing the number of occurrences by the maintenance cycle. The probability value of failure caused by human factors of the equipment is then obtained. The failure probability value caused by mechanical failure and the failure probability value caused by human factors are added together to obtain the failure probability value of the moving equipment. Based on the failure probability value of the moving equipment, the failure of the moving equipment is predicted.

2. The method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility according to claim 1, characterized in that, The general failure probability value is obtained from a failure database.

3. The method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility according to claim 2, characterized in that, The failure database is the OREDA datasheet.

4. The method for predicting the failure of moving equipment in a surface injection and production system for a salt cavern gas storage facility according to claim 1, characterized in that, The skid-mounted characteristic correction coefficient has a value range of [1, 5]. It is scored by experts, with scores ranging from 1 to 5. A score of 1 indicates that no faulty parts of the skid-mounted equipment are related, while a score of 5 indicates that all faults in the skid-mounted equipment are completely related. The average score is taken as the skid-mounted characteristic correction coefficient of the equipment after scoring by more than 10 experts.

5. The method for predicting the failure of moving equipment in a surface injection and production system for a salt cavern gas storage facility according to claim 1, characterized in that, The correction coefficient for the periodic operation characteristics has a value range of [1, 10]. It is scored by experts between 1 and 10. The equipment is scored as 1 if there is no start-stop action in a maintenance cycle, and as 10 if the equipment starts and stops at a high frequency in a maintenance cycle. The average value is taken as the correction coefficient for the periodic operation characteristics of the equipment after scoring by more than 10 experts.

6. The method for predicting the failure of moving equipment in a surface injection and production system for a salt cavern gas storage facility according to claim 1, characterized in that, The probability of equipment failure caused by human factors is quantitatively calculated using the fault tree method.

7. The method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility according to claim 1, characterized in that, The moving device is a reciprocating compressor skid.

8. The method for predicting the failure of moving equipment in a surface injection and production system of a salt cavern gas storage facility according to claim 1, characterized in that, Combined with historical data on the failure probability values ​​of dynamic equipment in the surface injection and production systems of salt cavern gas storage facilities that have actually failed. P The system divides the equipment into intervals and predicts that the failure probability value of the moving equipment falls within the set interval as equipment that is about to fail, thereby enabling the prediction of failure of the moving equipment.

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