Design and Implementation of Intelligent Oilfield Monitoring and Data Transmission System Based on Cloud-Edge Collaboration Technology

Design and Implementation of Intelligent Oilfield Monitoring and Data Transmission System Based on Cloud-Edge Collaboration Technology

With the rapid advancement of the Industrial Internet, technologies such as unmanned factories and smart factories have become increasingly pivotal for industrial transformation and upgrading. A key aspect of this transformation is the intelligent management of oilfield monitoring, which is vital for improving operational efficiency and reducing costs. This paper introduces a sophisticated intelligent platform designed for sensing, transmission, computation, and control within the oilfield monitoring sector, aligned with the Industrial Internet framework. Our platform is built on a cloud-edge integration architecture that integrates state-of-the-art data acquisition, communication technologies, and intelligent algorithms, enabling efficient data collection, secure transmission, and intelligent processing of oilfield data. We detail the platform’s three-tier architecture, including the cloud server layer, Mobile Edge Computing (MEC) server layer, and Remote Terminal Unit (RTU) layer, and discuss the implementation of key technologies such as homomorphic encryption for secure data transmission and OFDM for efficient communication. We also present the computation offloading strategy based on the Markov Decision Process (MDP) and the CEC-WGD approach, which leverages gradient descent to optimize task offloading decisions dynamically. Experimental verification across various oilfield environments confirms the platform’s significant potential to enhance monitoring efficiency, ensure production safety, and elevate operational intelligence. The findings demonstrate the platform’s ability to meet the high demands for real-time performance and security in oilfield monitoring and data transmission systems, positioning it as a powerful tool for advancing smart industrial management.