The Development of Constructive Methods for Monitoring and Managing Complex Oil and Gas Production Systems under Uncertainty: The Case of Azerbaijan

Azerbaijan’s oil and gas sector is rapidly adopting digital technologies (digital twins, remote control, predictive maintenance), yet constructive methods for monitoring and managing complex production systems under uncertainty lag behind practical needs. This gap reduces the effectiveness of digital investments and exposes operations to operational, economic, and environmental risks. This paper reviews the state of technology and methodology in Azerbaijan, identifies methodological shortfalls (uncertainty modeling, real-time decision algorithms, robust adaptive control), and proposes a research agenda emphasizing probabilistic models, hybrid fuzzy–Bayesian frameworks, and reinforcement learning approaches tailored to Azerbaijani field conditions. Examples from BP’s ACE platform and SOCAR’s digital projects illustrate both progress and remaining methodological challenges. Practical recommendations for industry–academia collaboration, pilot deployments, and capacity building conclude the paper.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-31
DOI
https://doi.org/10.5281/zenodo.17836072
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
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article

The Development of Constructive Methods for Monitoring and Managing Complex Oil and Gas Production Systems under Uncertainty: The Case of Azerbaijan

Zenodo (CERN European Organization for Nuclear Research)
Reservoir Engineering and Simulation Methods
article

The Development of Constructive Methods for Monitoring and Managing Complex Oil and Gas Production Systems under Uncertainty: The Case of Azerbaijan

article en

Abstract

Azerbaijan’s oil and gas sector is rapidly adopting digital technologies (digital twins, remote control, predictive maintenance), yet constructive methods for monitoring and managing complex production systems under uncertainty lag behind practical needs. This gap reduces the effectiveness of digital investments and exposes operations to operational, economic, and environmental risks. This paper reviews the state of technology and methodology in Azerbaijan, identifies methodological shortfalls (uncertainty modeling, real-time decision algorithms, robust adaptive control), and proposes a research agenda emphasizing probabilistic models, hybrid fuzzy–Bayesian frameworks, and reinforcement learning approaches tailored to Azerbaijani field conditions. Examples from BP’s ACE platform and SOCAR’s digital projects illustrate both progress and remaining methodological challenges. Practical recommendations for industry–academia collaboration, pilot deployments, and capacity building conclude the paper.

Zenodo (CERN European Organization for Nuclear Research)
Azerbaijan State Oil and Industry University (AZ)
Industry, innovation and infrastructure
Openalex Percentile: Top 40%
Reservoir Engineering and Simulation Methods
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The Development of Constructive Methods for Monitoring and Managing Complex Oil and Gas Production Systems under Uncertainty: The Case of Azerbaijan · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS