N. Atibodhi, Supha-Kitti Dhadachaipathomphong, F. Nazir, Nathachok Namwong
{"title":"泰国湾资产凝析油稳定器实时优化的数字化转型","authors":"N. Atibodhi, Supha-Kitti Dhadachaipathomphong, F. Nazir, Nathachok Namwong","doi":"10.4043/31363-ms","DOIUrl":null,"url":null,"abstract":"\n PTTEP's natural gas fields in Gulf of Thailand, has encountered losses in Condensate yield due to suboptimal operating conditions as variation in feed compositions occurs when production line up changes. As a result of this suboptimal operation, some light Condensate is lost into gas phase resulting in lower overall profitability.\n As part of company's Digital Transformation initiatives, a Condensate Stabilizer Optimization (CSO) solution has been implemented to minimize or eliminate these losses. The objective of CSO is to provide real-time recommended operating conditions to maximize condensate production while maintaining sale condensate specification using optimization technology that considers all relevant condensate stabilization process parameters.\n The CSO solution leverages Multivariable Predictive Control or Model Predictive Control (MPC) technology and communicates the obtained results to offshore teams via an online web user interface.\n Besides the dynamic models and MPC technology, the solution also includes an important component of the CSO solution which is the web based online dashboards as they are the key to communicate between the solution and the users. The dashboards include the following key features:\n – Key operating parameters of Condensate Stabilizer Units including Controlled, Manipulated, and Disturbance Variables – Recommended optimal values of Manipulated Variables to achieve maximum condensate production – Difference between actual vs predicted RVP. This is to visualize current model accuracy – Captured Benefit\n As of December 2021, the CSO solution has been fully utilized for 5 months, i.e. Go-Live since August 2021. During this period, it has successfully delivered not only safe operating window but also benefits which adds up to 1.49 MUSD/year. As the benefits of the solution have been proven, a plan to proceed with Phase 2 of this project, in which the CSO solution will be integrated with the Distributed Control System (DCS) allowing MPC Controller to automatically adjust process parameters to achieve the most optimal conditions, has been set.\n Apart from process optimization, the CSO solution can be used to evaluate operating scenarios based on given simulated process parameters, thus becoming a true \"Digital Twin\" of the Condensate Stabilizer that can replicate its operation at different operating conditions.","PeriodicalId":11011,"journal":{"name":"Day 3 Thu, March 24, 2022","volume":"108 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Digital Transformation for the Gulf of Thailand's Assets Condensate Stabilizer Real-Time Optimization\",\"authors\":\"N. Atibodhi, Supha-Kitti Dhadachaipathomphong, F. Nazir, Nathachok Namwong\",\"doi\":\"10.4043/31363-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n PTTEP's natural gas fields in Gulf of Thailand, has encountered losses in Condensate yield due to suboptimal operating conditions as variation in feed compositions occurs when production line up changes. As a result of this suboptimal operation, some light Condensate is lost into gas phase resulting in lower overall profitability.\\n As part of company's Digital Transformation initiatives, a Condensate Stabilizer Optimization (CSO) solution has been implemented to minimize or eliminate these losses. The objective of CSO is to provide real-time recommended operating conditions to maximize condensate production while maintaining sale condensate specification using optimization technology that considers all relevant condensate stabilization process parameters.\\n The CSO solution leverages Multivariable Predictive Control or Model Predictive Control (MPC) technology and communicates the obtained results to offshore teams via an online web user interface.\\n Besides the dynamic models and MPC technology, the solution also includes an important component of the CSO solution which is the web based online dashboards as they are the key to communicate between the solution and the users. The dashboards include the following key features:\\n – Key operating parameters of Condensate Stabilizer Units including Controlled, Manipulated, and Disturbance Variables – Recommended optimal values of Manipulated Variables to achieve maximum condensate production – Difference between actual vs predicted RVP. This is to visualize current model accuracy – Captured Benefit\\n As of December 2021, the CSO solution has been fully utilized for 5 months, i.e. Go-Live since August 2021. During this period, it has successfully delivered not only safe operating window but also benefits which adds up to 1.49 MUSD/year. As the benefits of the solution have been proven, a plan to proceed with Phase 2 of this project, in which the CSO solution will be integrated with the Distributed Control System (DCS) allowing MPC Controller to automatically adjust process parameters to achieve the most optimal conditions, has been set.\\n Apart from process optimization, the CSO solution can be used to evaluate operating scenarios based on given simulated process parameters, thus becoming a true \\\"Digital Twin\\\" of the Condensate Stabilizer that can replicate its operation at different operating conditions.\",\"PeriodicalId\":11011,\"journal\":{\"name\":\"Day 3 Thu, March 24, 2022\",\"volume\":\"108 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 3 Thu, March 24, 2022\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4043/31363-ms\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 3 Thu, March 24, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4043/31363-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Digital Transformation for the Gulf of Thailand's Assets Condensate Stabilizer Real-Time Optimization
PTTEP's natural gas fields in Gulf of Thailand, has encountered losses in Condensate yield due to suboptimal operating conditions as variation in feed compositions occurs when production line up changes. As a result of this suboptimal operation, some light Condensate is lost into gas phase resulting in lower overall profitability.
As part of company's Digital Transformation initiatives, a Condensate Stabilizer Optimization (CSO) solution has been implemented to minimize or eliminate these losses. The objective of CSO is to provide real-time recommended operating conditions to maximize condensate production while maintaining sale condensate specification using optimization technology that considers all relevant condensate stabilization process parameters.
The CSO solution leverages Multivariable Predictive Control or Model Predictive Control (MPC) technology and communicates the obtained results to offshore teams via an online web user interface.
Besides the dynamic models and MPC technology, the solution also includes an important component of the CSO solution which is the web based online dashboards as they are the key to communicate between the solution and the users. The dashboards include the following key features:
– Key operating parameters of Condensate Stabilizer Units including Controlled, Manipulated, and Disturbance Variables – Recommended optimal values of Manipulated Variables to achieve maximum condensate production – Difference between actual vs predicted RVP. This is to visualize current model accuracy – Captured Benefit
As of December 2021, the CSO solution has been fully utilized for 5 months, i.e. Go-Live since August 2021. During this period, it has successfully delivered not only safe operating window but also benefits which adds up to 1.49 MUSD/year. As the benefits of the solution have been proven, a plan to proceed with Phase 2 of this project, in which the CSO solution will be integrated with the Distributed Control System (DCS) allowing MPC Controller to automatically adjust process parameters to achieve the most optimal conditions, has been set.
Apart from process optimization, the CSO solution can be used to evaluate operating scenarios based on given simulated process parameters, thus becoming a true "Digital Twin" of the Condensate Stabilizer that can replicate its operation at different operating conditions.