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Serverless Edge Computing for Green Oil and Gas Industry

机译:绿色石油和天然气行业的无服务器边缘计算

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Escalating demand of petroleum led the Oil and Gas (O&G) industry to extend oil extraction operation in the remote reservoirs. Oil extraction is a fault intolerant process where the maximum penalty is disaster impacting the environment seriously. Therefore, efficient and nature-friendly green oil extraction is a challenging operation, especially with location constrained in accessing the sites. To overcome these challenges and protect the environment from pollution, smart oil fields with numerous sensors (e.g., for pipeline pressure, gas leakage, air pollution) are established to achieve clean O&G extraction. Conventionally, cloud datacenters are utilized to process the generated data. High-latency satellite communication are used for data transfer, which is not suitable for time-sensitive operations/tasks. To process such latency-sensitive tasks, edge computing can be a suitable candidate, however, their computational power goes downhill at disaster time due to surge demand of many coordinated activities. Therefore, we propose green smart oil fields that operate based on edge computing. To overcome shortage of resources and rapid deployment of the edge computing systems, we propose to use lightweight serverless computing on a federation of edge computing resources from nearby oil rigs. Our solution coordinates urgent coordinated operations/tasks to prevent disasters in oil fields and enable the idea of green smart oil fields. Evaluation results demonstrate the efficacy of our proposed solution in compare to conventional solutions for smart oil fields.
机译:不断增长的石油需求导致石油和天然气(O&G)行业扩大了偏远油藏的采油作业。采油是一个不容错的过程,其中最大的损失是严重影响环境的灾难。因此,高效且自然友好的绿油提取是一项具有挑战性的操作,尤其是在位置受限的情况下。为了克服这些挑战并保护环境免受污染,建立了具有众多传感器(例如,用于管道压力,气体泄漏,空气污染)的智能油田,以实现清洁的油气采出。按照惯例,云数据中心用于处理生成的数据。高延迟卫星通信用于数据传输,不适用于对时间敏感的操作/任务。为了处理此类对延迟敏感的任务,边缘计算可能是合适的选择,但是,由于许多协调活动的激增需求,它们在灾难发生时的计算能力下降。因此,我们提出了基于边缘计算的绿色智能油田。为了克服资源短缺和边缘计算系统的快速部署,我们建议在附近石油钻井平台的边缘计算资源联合中使用轻量级无服务器计算。我们的解决方案协调紧急协调的操作/任务,以防止油田发生灾难,并实现绿色智能油田的构想。评估结果证明了我们提出的解决方案与智能油田常规解决方案相比的有效性。

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