Predictive big data analytics for drilling downhole problems: A review

M., Aslam Abdullah; A., Aseel; Roy, Rithul; Sunil, Pranav

doi:10.1016/j.egyr.2023.05.028

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Cited by 3 publications

References 55 publications

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Digitalizing Marginal Field Operations: A Paradigm Shift Towards Technical and Operational Excellence

Ajimoko

2024

SPE Nigeria Annual International Conference and Exhibition

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This paper explores the transformative potential of digitalization in optimizing operations within marginal oil and gas fields. It delves into how advancements in digital technologies are revolutionizing traditional field management approaches, enabling real-time monitoring, predictive maintenance, and data-driven decision-making. By leveraging digital tools such as IoT, AI, and data analytics, the paper aims to enhance technical and operational efficiency while minimizing costs and maximizing productivity in marginal field operations. Through case studies and industry insights, it elucidates the benefits of digitalization in overcoming operational challenges and achieving excellence in resource extraction from marginal fields. The study underscores the importance of embracing digital innovation as a strategic imperative for maximizing the potential of marginal field assets in the energy industry.

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Predictive big data analytics for drilling downhole problems: A review

Cited by 3 publications

References 55 publications

Anomaly detection for drilling tools based on operating mode recognition and interval-augmented Mahalanobis distance

Anomaly detection for drilling tools based on operating mode recognition and interval-augmented Mahalanobis distance

A novel physics-guided spatial-temporal data mining method with external and internal causal attention for drilling risk evaluation

Digitalizing Marginal Field Operations: A Paradigm Shift Towards Technical and Operational Excellence

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