Kegang Ling, Guoqing Han, Xiao Ni, Chunming Xu, Jun He, P. Pei, J. Ge
{"title":"燃气管道泄漏检测新方法","authors":"Kegang Ling, Guoqing Han, Xiao Ni, Chunming Xu, Jun He, P. Pei, J. Ge","doi":"10.2118/2014-1891568-PA","DOIUrl":null,"url":null,"abstract":"lower cost. It also has the advantages of monitoring the system continuously and noninterference with pipeline operations. One of the limitations of the modeling method is that it requires flow parameters, which are not always available. Leak detection from mathematical modeling also has a higher uncertainty than that from physical inspection. Many researchers have conducted investigations on gas transient flow in pipelines to detect leaks. Huber (1981) used a computerbased pipeline simulator for batch tracking, line balance, and leak detection in the Cochin pipeline system. The instruments installed in the pipeline and the simulator in the central control office made online, real-time surveillance of the line possible. The resulting model was capable of determining pressure, temperature, density, and flow profiles for the line. The simulator was based on mass balance, and thus required a complete set of variables to detect the leak. Shell used physical methods to detect leaks in a 36-in.-diameter, 78-mile-long submarine pipeline near Bintulu, Sarawak (van der Marel and Sluyter 1984). The leaks were detected accurately by optical and acoustical equipment mounted on a remotely operated vehicle, which was guided along the pipeline from a distance of 0.5 m above the pipeline. The disadvantages of this detection method are time consumption (15 days to finish detection), and the pipeline needed to be kept at a high pressure to obtain a relatively high signal/noise ratio. Sections of the pipeline were covered by a thick layer of selected backfill. This ruled out the use of the optical technology. It is also noted that the maximum water depth was 230 ft. Applications in a deepwater environment have not been tested. Luongo (1986) studied the gas transient flow in a constantcross-section pipe. He linearized the partial-differential equation and developed a numerical solution to the linear parabolic partialdifferential equation. In his derivation, friction factor was calculated from steady-state conditions (i.e., constant friction factor for transient flow). Luongo (1986) claimed that his linearization algorithm can save 25% in the computational time without a major sacrifice in accuracy when compared with other methods. The governing equations used by Luongo (1986) required a complete data set of pressure and flow rate. Massinon (1988) proposed a real-time transient hydraulic model for leak detection and batch tracking on a liquid-pipeline system on the basis of the conservation of mass, momentum, and energy, and an equation of state. Although this model can detect leaks in a timely manner, it required intensive acquisition of complete data sets, both in the space domain (the pipeline lengths between sensors are very short) and in the time domain (time interval between two consecutive measurements is short), which are impossible for many pipelines. Mactaggart (1989) applied a compensated volume-balance method at a cost less than a transient-model-based leak detection for sour-gas-leak detection. The method is cost effective, but is applied only to well-instrumented pipelines. Pressure and rate at the inlet and the outlet of the pipeline are required for this analysis. Scott et al. (1999) modeled the deepwater leak in a multiphase production flowline. Their method can detect a multiphase leak, but Copyright © 2015 Society of Petroleum Engineers","PeriodicalId":19446,"journal":{"name":"Oil and gas facilities","volume":"56 1","pages":"97-106"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"A New Method for Leak Detection in Gas Pipelines\",\"authors\":\"Kegang Ling, Guoqing Han, Xiao Ni, Chunming Xu, Jun He, P. Pei, J. Ge\",\"doi\":\"10.2118/2014-1891568-PA\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"lower cost. It also has the advantages of monitoring the system continuously and noninterference with pipeline operations. One of the limitations of the modeling method is that it requires flow parameters, which are not always available. Leak detection from mathematical modeling also has a higher uncertainty than that from physical inspection. Many researchers have conducted investigations on gas transient flow in pipelines to detect leaks. Huber (1981) used a computerbased pipeline simulator for batch tracking, line balance, and leak detection in the Cochin pipeline system. The instruments installed in the pipeline and the simulator in the central control office made online, real-time surveillance of the line possible. The resulting model was capable of determining pressure, temperature, density, and flow profiles for the line. The simulator was based on mass balance, and thus required a complete set of variables to detect the leak. Shell used physical methods to detect leaks in a 36-in.-diameter, 78-mile-long submarine pipeline near Bintulu, Sarawak (van der Marel and Sluyter 1984). The leaks were detected accurately by optical and acoustical equipment mounted on a remotely operated vehicle, which was guided along the pipeline from a distance of 0.5 m above the pipeline. The disadvantages of this detection method are time consumption (15 days to finish detection), and the pipeline needed to be kept at a high pressure to obtain a relatively high signal/noise ratio. Sections of the pipeline were covered by a thick layer of selected backfill. This ruled out the use of the optical technology. It is also noted that the maximum water depth was 230 ft. Applications in a deepwater environment have not been tested. Luongo (1986) studied the gas transient flow in a constantcross-section pipe. He linearized the partial-differential equation and developed a numerical solution to the linear parabolic partialdifferential equation. In his derivation, friction factor was calculated from steady-state conditions (i.e., constant friction factor for transient flow). Luongo (1986) claimed that his linearization algorithm can save 25% in the computational time without a major sacrifice in accuracy when compared with other methods. The governing equations used by Luongo (1986) required a complete data set of pressure and flow rate. Massinon (1988) proposed a real-time transient hydraulic model for leak detection and batch tracking on a liquid-pipeline system on the basis of the conservation of mass, momentum, and energy, and an equation of state. Although this model can detect leaks in a timely manner, it required intensive acquisition of complete data sets, both in the space domain (the pipeline lengths between sensors are very short) and in the time domain (time interval between two consecutive measurements is short), which are impossible for many pipelines. Mactaggart (1989) applied a compensated volume-balance method at a cost less than a transient-model-based leak detection for sour-gas-leak detection. The method is cost effective, but is applied only to well-instrumented pipelines. Pressure and rate at the inlet and the outlet of the pipeline are required for this analysis. Scott et al. (1999) modeled the deepwater leak in a multiphase production flowline. 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引用次数: 9
A New Method for Leak Detection in Gas Pipelines
lower cost. It also has the advantages of monitoring the system continuously and noninterference with pipeline operations. One of the limitations of the modeling method is that it requires flow parameters, which are not always available. Leak detection from mathematical modeling also has a higher uncertainty than that from physical inspection. Many researchers have conducted investigations on gas transient flow in pipelines to detect leaks. Huber (1981) used a computerbased pipeline simulator for batch tracking, line balance, and leak detection in the Cochin pipeline system. The instruments installed in the pipeline and the simulator in the central control office made online, real-time surveillance of the line possible. The resulting model was capable of determining pressure, temperature, density, and flow profiles for the line. The simulator was based on mass balance, and thus required a complete set of variables to detect the leak. Shell used physical methods to detect leaks in a 36-in.-diameter, 78-mile-long submarine pipeline near Bintulu, Sarawak (van der Marel and Sluyter 1984). The leaks were detected accurately by optical and acoustical equipment mounted on a remotely operated vehicle, which was guided along the pipeline from a distance of 0.5 m above the pipeline. The disadvantages of this detection method are time consumption (15 days to finish detection), and the pipeline needed to be kept at a high pressure to obtain a relatively high signal/noise ratio. Sections of the pipeline were covered by a thick layer of selected backfill. This ruled out the use of the optical technology. It is also noted that the maximum water depth was 230 ft. Applications in a deepwater environment have not been tested. Luongo (1986) studied the gas transient flow in a constantcross-section pipe. He linearized the partial-differential equation and developed a numerical solution to the linear parabolic partialdifferential equation. In his derivation, friction factor was calculated from steady-state conditions (i.e., constant friction factor for transient flow). Luongo (1986) claimed that his linearization algorithm can save 25% in the computational time without a major sacrifice in accuracy when compared with other methods. The governing equations used by Luongo (1986) required a complete data set of pressure and flow rate. Massinon (1988) proposed a real-time transient hydraulic model for leak detection and batch tracking on a liquid-pipeline system on the basis of the conservation of mass, momentum, and energy, and an equation of state. Although this model can detect leaks in a timely manner, it required intensive acquisition of complete data sets, both in the space domain (the pipeline lengths between sensors are very short) and in the time domain (time interval between two consecutive measurements is short), which are impossible for many pipelines. Mactaggart (1989) applied a compensated volume-balance method at a cost less than a transient-model-based leak detection for sour-gas-leak detection. The method is cost effective, but is applied only to well-instrumented pipelines. Pressure and rate at the inlet and the outlet of the pipeline are required for this analysis. Scott et al. (1999) modeled the deepwater leak in a multiphase production flowline. Their method can detect a multiphase leak, but Copyright © 2015 Society of Petroleum Engineers