Cybersecurity Challenges in the Offshore Oil and Gas Industry: An Industrial Cyber-Physical Systems (ICPS) Perspective

Mohammed, Abubakar Sadiq; Reinecke, Philipp; Burnap, Pete; Rana, Omer; Anthi, Eirini

doi:10.1145/3548691

Cited by 18 publications

(4 citation statements)

References 63 publications

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“…Offshore platforms, being critical infrastructures in the oil and gas industry, require robust maintenance strategies to ensure their operational integrity, safety, and reliability (Mohammed et al, 2022). Maintenance on these platforms is typically categorized into three main strategies: preventive maintenance, predictive maintenance, and corrective maintenance.…”

Section: Current Maintenance Strategies On Offshore Platformsmentioning

confidence: 99%

Optimizing maintenance logistics on offshore platforms with AI: Current strategies and future innovations

Ayemere Ukato,

Oludayo Olatoye Sofoluwe,

Dazok Donald Jambol

et al. 2024

World J. Adv. Res. Rev.

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Offshore platforms are vital assets for the oil and gas industry, serving as the primary facilities for exploration, extraction, and processing. Maintenance logistics plays a crucial role in ensuring these platforms operate efficiently and safely. However, the remote and harsh environments of offshore platforms present significant challenges for maintenance activities. Traditional maintenance strategies often struggle to meet the demands of these environments, leading to inefficiencies, increased costs, and potential safety risks. This review discusses the application of Artificial Intelligence (AI) in optimizing maintenance logistics on offshore platforms. Current strategies involve a combination of preventive, predictive, and corrective maintenance approaches. Preventive maintenance schedules regular inspections and replacements based on predetermined intervals, while predictive maintenance utilizes data analytics to predict equipment failures and plan maintenance activities accordingly. Corrective maintenance addresses issues as they arise, often in response to unexpected failures. AI offers opportunities to enhance these strategies by leveraging advanced data analytics, machine learning, and optimization algorithms. AI-enabled predictive maintenance can analyze vast amounts of data from sensors, historical maintenance records, and environmental factors to forecast equipment failures with greater accuracy. This allows for proactive maintenance planning, minimizing downtime and reducing maintenance costs. Furthermore, AI can optimize maintenance logistics by improving resource allocation and scheduling. Through real-time monitoring and analysis, AI systems can prioritize maintenance tasks based on urgency, equipment criticality, and resource availability. This ensures that maintenance crews are deployed efficiently, reducing idle time and improving overall productivity. Future innovations in AI for maintenance logistics on offshore platforms include the integration of Internet of Things (IoT) devices and autonomous systems. IoT sensors can provide real-time data on equipment condition and environmental factors, enabling more precise predictive maintenance models. Autonomous maintenance robots equipped with AI algorithms can perform routine inspections and minor repairs, reducing the need for human intervention in hazardous environments. However, implementing AI in offshore maintenance logistics also poses challenges, including data quality, cybersecurity, and workforce readiness. Ensuring data accuracy and reliability is crucial for effective AI models, requiring robust data collection and management processes. Cybersecurity measures must be strengthened to protect AI systems from malicious attacks that could disrupt operations or compromise safety. Additionally, workforce training and education are essential to prepare personnel for working alongside AI systems and interpreting AI-generated insights. Optimizing maintenance logistics on offshore platforms with AI offers significant benefits in terms of efficiency, cost savings, and safety. By leveraging AI technologies, current maintenance strategies can be enhanced, and future innovations can revolutionize offshore maintenance practices, making operations more sustainable and resilient in the face of evolving challenges.

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Section: Current Maintenance Strategies On Offshore Platformsmentioning

confidence: 99%

Optimizing maintenance logistics on offshore platforms with AI: Current strategies and future innovations

Ayemere Ukato,

Oludayo Olatoye Sofoluwe,

Dazok Donald Jambol

et al. 2024

World J. Adv. Res. Rev.

View full text Add to dashboard Cite

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“…Supply and demand shocks are a risk for oil and gas firms, especially because energy facilities require large amounts of capital and time to ramp up to full capacity. Concerns have been raised about any disruption in the global supply of oil and gas (O&G), which might have an impact on oil prices and, by extension, the global economy [31].…”

Section: Business Risksmentioning

confidence: 99%

“…The oil tank level spoopng Attacks are outfitted with level control sensors that send data to avoid tank overfilling. The major purpose of this approach is to deceive sensors into reporting that the tank level is lower than it actually is [31].…”

Section: Physical Risks For Petroleum Cpsmentioning

confidence: 99%

Comprehensive Risk Classification and Mitigation in the Petroleum Cyber-Physical Systems of the Oil and Gas Industry

Oudina,

Dib,

Yakoubi

et al. 2024

IJSSE

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The oil and gas (O&G) industry is the engine of the global economy. Oil and gas production passes through axes related to exploration, research, extraction, transportation, and finally the final manufacturing of energy products. All these stages permeate some risks that threaten both the human factor and the material factor. The oil industry merged with the fourth technological industry 4.0, which included multiple technologies and systems, the most important of which is the cyber-physical system (CPS), which some researchers have named petroleum cyber-physical systems if it is embodied within this industry. CPSs are collaborative systems formed of autonomous and smart devices that can handle data flows and activities while maintaining integrated physical objects. Several risks confront the energy field, with the potential to interrupt critical supply lines, hurt the environment, and trigger a financial catastrophe. In the field of O&G, there are very few scientific studies that are exposed to risks in a complementary and comprehensive manner, including only those that focus on cyber-attacks and their causes. There is a lack of comprehension and in-depth studies of all types of threats in all their aspects that surround cyber-physical systems within this field. Some risk classifications are based on internal and external risks, while others are based on the influencing and causative aspects in a general way. This study deals with the classification of risks: 1) classification of risk for the global industry of O&G. 2) in terms of the fact that the cyber-physical system is the most important component in the O&G industry and that these risks are either physical, cyber, or related to permissibility and authorization in the O&G field. A security approach is also presented that leads to mitigating the impact of risks in oil and gas zones.

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“…e optimization of the substructure not only is a static process but also must be continuously adjusted during the optimization process. erefore, it is necessary to propose a more reasonable and efficient optimization method of spatial layout of marine industry [9]. In recent years, with the development of science and technology, cloud computing technology has gradually been used in people's lives.…”

Section: Introductionmentioning

confidence: 99%

Optimization Method of Spatial Layout of Marine Industry Based on Cloud Computing

Fa-zhi

Dong

et al. 2022

Mathematical Problems in Engineering

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With the continuous expansion of the marine economy, a large number of problems have been encountered in the spatial layout of the marine industry, such as space intensification, low space utilization, unreasonable industrial structure, poor management system, inadequate scientific research and innovation capabilities, poor ecological environment, poor load balance, and large resource consumption, etc. In response to these problems, this study proposes to reoptimize the spatial layout of the marine industry on the basis of cloud computing. On the basis of collecting the Hilbert values of all data, all nodes are arranged in the order of construction time to improve the Hilbert R-tree structure. Then the idea of clustering is introduced to avoid data overlap. Using the spatial correlation coefficient, the access control model of the marine industry spatial layout platform is established to optimize the marine industry spatial layout under the background of cloud computing. When using the method proposed in this study, the time consumption was about 4 seconds when the number of blocks increased to 5000. Compared with 11 seconds and 7 seconds when using the other two methods, the proposed method greatly reduces the time consumed by the number of pieces of ocean remote sensing images in different query ranges under the ocean information cloud platform. The proposed method also shows good performance in the encryption and decryption test process of the pairing method. In summary, the feasibility and effectiveness of the proposed method in the optimization of the marine industry spatial layout is confirmed, which provides a suitable theoretical basis for the optimization of the marine industry spatial layout.

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Cybersecurity Challenges in the Offshore Oil and Gas Industry: An Industrial Cyber-Physical Systems (ICPS) Perspective

Cited by 18 publications

References 63 publications

Optimizing maintenance logistics on offshore platforms with AI: Current strategies and future innovations

Optimizing maintenance logistics on offshore platforms with AI: Current strategies and future innovations

Comprehensive Risk Classification and Mitigation in the Petroleum Cyber-Physical Systems of the Oil and Gas Industry

Optimization Method of Spatial Layout of Marine Industry Based on Cloud Computing

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