A. D. Lullo, C. Passucci, K. Hester, R. Zaffaroni, R. Reinhart
{"title":"Use of Miniaturized Sensors to Optimize Cleaning Operations for In-Line Inspection of a Subsea Pipeline","authors":"A. D. Lullo, C. Passucci, K. Hester, R. Zaffaroni, R. Reinhart","doi":"10.2118/193010-MS","DOIUrl":null,"url":null,"abstract":"\n Pipeline in-line inspection requires a proper cleaning of the pipeline inner walls. In the case hereby described of a 30km 12\" offshore line, a significant amount of wax deposits was expected and a series hydro-mechanical cleaning tools were deployed, after a preliminary series of less aggressive pigs.\n Normally, the progress of the cleaning process is monitored only by the arrival conditions of the cleaning tools and of the receiving trap. To improve the process, miniaturized pressure, temperature and acceleration sensors were added to the cleaning tools, directly in the field, without any modifications to the cleaning devices and without introducing any additional risks or operating impact. After each instrumented cleaning tool, the sensor data were quickly analyzed and led to the selection of most suitable subsequent tool.\n In this way, it was observed that the pig conditions and the amount of material collected in the receiving trap did not fully indicate the true cleaning status of the pipeline, while the sensors provided a clearer picture. The pig sequence was thus optimized in number and type of pigs and the intelligent pig run was preformed successfully with no issues or data loss.\n The advantage of these tiny sensors, not foreseen in the hydro-mechanical pig design, is that they can be applied to almost any pig with minimal-to-no modifications. This information can be used in a number of ways, including detection of flow restrictions (dents, deposits), and can also be used to re-create the line elevation, profile with limited a priori information.","PeriodicalId":11014,"journal":{"name":"Day 1 Mon, November 12, 2018","volume":"72 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, November 12, 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/193010-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Pipeline in-line inspection requires a proper cleaning of the pipeline inner walls. In the case hereby described of a 30km 12" offshore line, a significant amount of wax deposits was expected and a series hydro-mechanical cleaning tools were deployed, after a preliminary series of less aggressive pigs.
Normally, the progress of the cleaning process is monitored only by the arrival conditions of the cleaning tools and of the receiving trap. To improve the process, miniaturized pressure, temperature and acceleration sensors were added to the cleaning tools, directly in the field, without any modifications to the cleaning devices and without introducing any additional risks or operating impact. After each instrumented cleaning tool, the sensor data were quickly analyzed and led to the selection of most suitable subsequent tool.
In this way, it was observed that the pig conditions and the amount of material collected in the receiving trap did not fully indicate the true cleaning status of the pipeline, while the sensors provided a clearer picture. The pig sequence was thus optimized in number and type of pigs and the intelligent pig run was preformed successfully with no issues or data loss.
The advantage of these tiny sensors, not foreseen in the hydro-mechanical pig design, is that they can be applied to almost any pig with minimal-to-no modifications. This information can be used in a number of ways, including detection of flow restrictions (dents, deposits), and can also be used to re-create the line elevation, profile with limited a priori information.