Offshore oil spill monitoring and detection: Improving risk management for offshore petroleum cyber-physical systems: (Invited paper)

Xiaodao Chen, Dongmei Zhang, Yuewei Wang, Lizhe Wang, Albert Y. Zomaya, Shiyan Hu
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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%.
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海上溢油监测与检测:改进海上石油信息物理系统的风险管理:(特邀论文)
石油行业已经开始采用先进的石油信息物理系统(CPS)技术。海上石油CPS的建造尤其困难,主要是由于在检测和防止海上石油泄漏方面存在挑战。在石油勘探和运输过程中,通常使用遥感多传感技术进行泄漏检测,从而实现海上石油CPS的水下建模。但是,这种技术存在遥感资源不足和计算开销大的问题。本文提出了一种基于交叉熵优化的泄漏检测技术来检测石油泄漏,这也有助于对石油泄漏引起的海洋污染的认识。蓬莱溢油事故的实验结果表明,该方法能有效识别溢油源,识别准确率达90.78%。
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