Mathematical Problems in Engineering

Intelligent Management of Oil and Gas Storage and Transportation Systems


Publishing date
01 Sep 2021
Status
Published
Submission deadline
07 May 2021

Lead Editor
Guest Editors

1University of Tokyo, Tokyo, Japan

2University of Lisbon, Lisbon, Portugal

3China University of Petroleum, Beijing, China


Intelligent Management of Oil and Gas Storage and Transportation Systems

Description

Intelligent technology has made great progress in recent years, with ‘smart’ infrastructure concepts developing successfully. In the gas and oil industries, smart gas and oil pipelines, smart storage, and smart logistics systems have gradually attracted attention. Enabled by digital and intelligent technologies, oil and gas storage and transportation systems have gradually developed from manual operation, semi-automatic operation, and automatic control towards a new stage of intelligent management. Having up-to-date information on system condition is the crucial basis for continuously monitoring and predicting system risk. Today, it is easy to collect, store, manage, and interpret real-time data by integrated applications that involve supervisory control and data acquisition systems (SCADA), geographic information systems (GIS), enterprise resource planning systems (ERP), radio-frequency identification (RFID), and Internet of Things. Data integration and information sharing make it feasible to resolve the problem of ‘isolated information’ inside the system, contributing to the optimization of resource allocation in the whole system. Furthermore, data mining and artificial intelligence help operators extract the best value from massive data, raise situational awareness, and ensure the right work is done. Drawing on these features, intelligent management significantly accelerates business benefits, improves system reliability, enhances work efficiency, and reduces the workload for operators.

Recent research in the field of oil and gas storage and transportation has also focused on how to implement intelligent management with emerging advanced concepts or technologies. Challenges to current research include: how to minimize emissions of carbon dioxide and methane during the design and operation stages of the system; methods for risk assessment and prediction of oil and gas storage and transportation; technologies for data mining and organization; data-driven self-monitoring and self-healing mechanisms to increase operational efficiency; effective ways to improve the reliability of transport and storage systems; management and design technologies considering uncertainties of different factors influencing the economic, safety, and efficiency of the system; and flexible scheduling to effectively respond to rapidly changing oil and gas demand profiles. More importantly, it is important that studies can be applied in real-world projects to reflect their practical significance rather than case studies with a small scale.

This Special Issue encourages researchers to explore the architecture, operating principle, and design method of intelligent management systems. The Issue will provide a platform to enhance interdisciplinary research and share the most recent ideas. The target audience includes both academic researchers and industrial practitioners. We are looking for original research articles as well as comprehensive review articles.

Potential topics include but are not limited to the following:

  • Overviews of state-of-the-art technologies, challenges, and opportunities in intelligent management
  • Design, retrofitting, implementation, and application of intelligent management systems
  • Data integration, mining, organization, visualization, and mapping for the whole process of oil and gas storage and transportation
  • Data-driven/event-driven/on-line approach for simulation, prediction, risk alert, risk evaluation, planning, scheduling, control, and emergence management
  • Methods and technologies for the evaluation of economics, sustainability, and safety of oil and gas storage and transportation system
  • New tools and analytical models/methods for quantifying the flexibility and reliability in oil and gas storage and transportation systems
  • Modelling and advanced intelligent algorithms for the intelligent management system of oil and gas storage and transportation considering uncertainties, multi-scale systems, and multi-period demands
  • Geographic Information Technologies and analysis for oil and gas storage and transportation systems
  • Software for intelligent management of oil and gas storage and transportation systems
Mathematical Problems in Engineering
 Journal metrics
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Acceptance rate11%
Submission to final decision118 days
Acceptance to publication28 days
CiteScore2.600
Journal Citation Indicator-
Impact Factor-

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