{"title":"考虑不确定性的海上生产系统设计","authors":"Leonardo Sales, C. Morooka","doi":"10.2118/191507-MS","DOIUrl":null,"url":null,"abstract":"\n The development of an offshore oil field is a complex and risky project. One core problem in this task is the selection of a production system that maximizes oil recovery and minimizes investments and operational costs while meeting external, economic, environmental, societal and technological demands in a scenario of uncertainties. Several studies address this problem in the literature; however, they do not consider uncertainties in the initial data neither justify objectively the chosen alternative among other feasible ones. We propose to select an offshore production system using an intelligent system that considers input uncertainties and chooses the best alternative in a rational manner. By comparing the results obtained with previous studies and real scenarios, we conclude that our methodology can obtain the optimal solution in situations where other methods cannot.","PeriodicalId":441169,"journal":{"name":"Day 3 Wed, September 26, 2018","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Design of Offshore Production Systems Considering Uncertainties\",\"authors\":\"Leonardo Sales, C. Morooka\",\"doi\":\"10.2118/191507-MS\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The development of an offshore oil field is a complex and risky project. One core problem in this task is the selection of a production system that maximizes oil recovery and minimizes investments and operational costs while meeting external, economic, environmental, societal and technological demands in a scenario of uncertainties. Several studies address this problem in the literature; however, they do not consider uncertainties in the initial data neither justify objectively the chosen alternative among other feasible ones. We propose to select an offshore production system using an intelligent system that considers input uncertainties and chooses the best alternative in a rational manner. By comparing the results obtained with previous studies and real scenarios, we conclude that our methodology can obtain the optimal solution in situations where other methods cannot.\",\"PeriodicalId\":441169,\"journal\":{\"name\":\"Day 3 Wed, September 26, 2018\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-09-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 3 Wed, September 26, 2018\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/191507-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 Wed, September 26, 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/191507-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design of Offshore Production Systems Considering Uncertainties
The development of an offshore oil field is a complex and risky project. One core problem in this task is the selection of a production system that maximizes oil recovery and minimizes investments and operational costs while meeting external, economic, environmental, societal and technological demands in a scenario of uncertainties. Several studies address this problem in the literature; however, they do not consider uncertainties in the initial data neither justify objectively the chosen alternative among other feasible ones. We propose to select an offshore production system using an intelligent system that considers input uncertainties and chooses the best alternative in a rational manner. By comparing the results obtained with previous studies and real scenarios, we conclude that our methodology can obtain the optimal solution in situations where other methods cannot.