Xiaodao Chen, Dongmei Zhang, Yuewei Wang, Lizhe Wang, Albert Y. Zomaya, Shiyan Hu
{"title":"Offshore oil spill monitoring and detection: Improving risk management for offshore petroleum cyber-physical systems: (Invited paper)","authors":"Xiaodao Chen, Dongmei Zhang, Yuewei Wang, Lizhe Wang, Albert Y. Zomaya, Shiyan Hu","doi":"10.1109/ICCAD.2017.8203865","DOIUrl":null,"url":null,"abstract":"Petroleum industry has started to embrace the advanced Petroleum Cyber-Physical System (CPS) technologies. Offshore petroleum CPS is particularly difficult to build, mainly due to the challenge in detecting and preventing offshore oil leaking. During the oil exploration and transportation process, the remote multi-sensing technology is typically used for leak detection, enabling the underwater modeling of an offshore petroleum CPS. However, such a technology suffers from insufficient remote sensing resources and large computational overhead. In this work, a cross entropy optimization based leak detection technique is proposed to detect the oil leak, which also facilitates the understanding of the oil leak induced marine pollution. Experimental results on a real Penglai oil spill event demonstrate that the proposed technique can effectively identify the sources of oil spills with accuracy of up to 90.78%.","PeriodicalId":126686,"journal":{"name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD.2017.8203865","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Petroleum industry has started to embrace the advanced Petroleum Cyber-Physical System (CPS) technologies. Offshore petroleum CPS is particularly difficult to build, mainly due to the challenge in detecting and preventing offshore oil leaking. During the oil exploration and transportation process, the remote multi-sensing technology is typically used for leak detection, enabling the underwater modeling of an offshore petroleum CPS. However, such a technology suffers from insufficient remote sensing resources and large computational overhead. In this work, a cross entropy optimization based leak detection technique is proposed to detect the oil leak, which also facilitates the understanding of the oil leak induced marine pollution. Experimental results on a real Penglai oil spill event demonstrate that the proposed technique can effectively identify the sources of oil spills with accuracy of up to 90.78%.