{"title":"Crude oil industry remote monitoring and management based on Industrial Internet of things and edge computing integration: A comprehensive survey","authors":"Hazem Ramzey , Mahmoud Badawy , Adel A. Elbaset","doi":"10.1016/j.rineng.2024.103034","DOIUrl":null,"url":null,"abstract":"<div><div>Monitoring and management engineering technologies, as well as crude oil production, have recently advanced significantly. Technology advancements aside, monitoring, administration, wait times, and emergency response remain quite poor, especially for the crude oil production cycle, where real-time management and monitoring are difficult. Several methodologies and technologies utilized for continuously monitoring and managing crude oil manufacturing are analyzed in light of the integrating of the Industrial Internet of Things (IIoT) and Edge Computing (EC). The ultimate objective is to monitor and manage the whole value chain process to increase production dependability and availability and generate better economic products and services. This study goes over crude oil production guidelines and unresolved research difficulties. The IIOT and EC integration are viewed as a possible approach for establishing domestic services and corporate procedures for increasing crude oil production. One hundred eighty-eight relevant studies published between 2017 and 2023 were indexed in the WOS (Web of Science), SCOPUS, OnePetro, and IEEE Xplore databases. A survey based on a literature review showed 50 studies (selected from those studies through the literature review stages) and their architectures and frameworks to automate crude production to better monitor alerts and production control. This survey aims to provide a comprehensive overview of multiple studies to highlight the deficiencies in recent research and serve as a reference for subsequent endeavors to develop solutions for a straightforward process monitoring system. Such a system would empower process operators to promptly and effortlessly detect any sources of abnormality within the process.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":null,"pages":null},"PeriodicalIF":6.0000,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Results in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590123024012891","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Monitoring and management engineering technologies, as well as crude oil production, have recently advanced significantly. Technology advancements aside, monitoring, administration, wait times, and emergency response remain quite poor, especially for the crude oil production cycle, where real-time management and monitoring are difficult. Several methodologies and technologies utilized for continuously monitoring and managing crude oil manufacturing are analyzed in light of the integrating of the Industrial Internet of Things (IIoT) and Edge Computing (EC). The ultimate objective is to monitor and manage the whole value chain process to increase production dependability and availability and generate better economic products and services. This study goes over crude oil production guidelines and unresolved research difficulties. The IIOT and EC integration are viewed as a possible approach for establishing domestic services and corporate procedures for increasing crude oil production. One hundred eighty-eight relevant studies published between 2017 and 2023 were indexed in the WOS (Web of Science), SCOPUS, OnePetro, and IEEE Xplore databases. A survey based on a literature review showed 50 studies (selected from those studies through the literature review stages) and their architectures and frameworks to automate crude production to better monitor alerts and production control. This survey aims to provide a comprehensive overview of multiple studies to highlight the deficiencies in recent research and serve as a reference for subsequent endeavors to develop solutions for a straightforward process monitoring system. Such a system would empower process operators to promptly and effortlessly detect any sources of abnormality within the process.