Offshore oil and gas development in remote harsh environments: engineering challenges and research opportunities

Adumene, Sidum; Khan, Faisal; Adedigba, Sunday; Mamudu, Abbas; Rosli, Masli Irwan

doi:10.1007/s42797-022-00057-1

Cited by 10 publications

(2 citation statements)

References 72 publications

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“…Offshore platforms represent the backbone of the oil and gas industry, serving as crucial infrastructures for exploration, extraction, and processing activities in offshore oil and gas fields (Stroykov et al, 2021). These platforms are situated in diverse and often challenging environments, ranging from shallow waters to ultra-deep seas, and they play a pivotal role in meeting the global demand for energy resources (Adumene et al, 2023). In this review, we will delve into the significance of maintenance logistics for offshore platforms and explore the potential of Artificial Intelligence (AI) in optimizing these logistics to ensure the efficiency, safety, and sustainability of offshore operations.…”

Section: Introductionmentioning

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: Introductionmentioning

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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“…Subsea pipelines may suffer from deformation defects under various damaging factors (such as corrosion, alternating sea currents, geological deformation, and human activities) [26][27][28]. Severe interplay among these factors can exacerbate each other and may even lead to pipeline rupture, causing major safety accidents, and inestimable damage to the global environment and regional economies [29,30]. As shown in Figure 2, the oil spill from the 2010 Gulf of Mexico oil drilling platform was considered the worst marine oil spill in American history, causing massive ecological devastation [31] and sparking subsequent studies on the aftermath of this event by numerous scholars [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

In-Line Inspection (ILI) Techniques for Subsea Pipelines: State-of-the-Art

Zhu,

Chen,

Lin

et al. 2024

JMSE

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Offshore oil and gas resources play a crucial role in supplementing the energy needs of human society. The crisscrossing subsea pipeline network, which serves as vital infrastructure for the storage and transportation of offshore oil and gas, requires regular inspection and maintenance to ensure safe operation and prevent ecological pollution. In-line inspection (ILI) techniques have been widely used in the detection and inspection of potential hazards within the pipeline network. This paper offers an overview of ILI techniques used in subsea pipelines, examining their advantages, limitations, applicable scenarios, and performance. It aims to provide valuable insights for the selection of ILI technologies in engineering and may be beneficial for those involved in pipeline integrity management and planning.

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Advances in Failure Prediction of Subsea Components Considering Complex Dependencies

Peng

Adumene

et al. 2023

Studies in Systems, Decision and Control

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Offshore oil and gas development in remote harsh environments: engineering challenges and research opportunities

Cited by 10 publications

References 72 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

In-Line Inspection (ILI) Techniques for Subsea Pipelines: State-of-the-Art

Advances in Failure Prediction of Subsea Components Considering Complex Dependencies

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