Artificial intelligence for predictive maintenance in oil and gas operations

Oil and Gas companies are maximizing capabilities using AI in the area of predictive maintenance to create data-driven insights leading towards higher operational efficiencies and safety. AI-driven predictive maintenance means analyzing data collected from various sensors and equipment to predict when a machinery fault might occur. And this approach helps cut back on unanticipated downtimes and drops maintenance costs to increase the life cycle of key assets. AI driven systems with predictive analytics capabilities analyze equipment behavior for patterns, anomalies using AI techniques like machine learning algorithms, deep learning etc. Those methods enable detecting issues in early stages, so intervention can be done before the failure. The accuracy of learning models is enhanced by AI collaborating with IoT devices to provide real-time data and continuous monitoring.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-30
DOI
https://doi.org/10.5281/zenodo.14942904
Primary Topic
Oil and Gas Production Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Artificial intelligence for predictive maintenance in oil and gas operations

Zenodo (CERN European Organization for Nuclear Research)
Oil and Gas Production Techniques
article

Artificial intelligence for predictive maintenance in oil and gas operations

article en

Abstract

Oil and Gas companies are maximizing capabilities using AI in the area of predictive maintenance to create data-driven insights leading towards higher operational efficiencies and safety. AI-driven predictive maintenance means analyzing data collected from various sensors and equipment to predict when a machinery fault might occur. And this approach helps cut back on unanticipated downtimes and drops maintenance costs to increase the life cycle of key assets. AI driven systems with predictive analytics capabilities analyze equipment behavior for patterns, anomalies using AI techniques like machine learning algorithms, deep learning etc. Those methods enable detecting issues in early stages, so intervention can be done before the failure. The accuracy of learning models is enhanced by AI collaborating with IoT devices to provide real-time data and continuous monitoring.

Zenodo (CERN European Organization for Nuclear Research)
Oil and Natural Gas Corporation (India) (IN), Life Cycle Engineering (United States) (US), University of Petroleum and Energy Studies (IN)
Responsible consumption and production
Openalex Percentile: Top 59%
Oil and Gas Production Techniques
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Artificial intelligence for predictive maintenance in oil and gas operations · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS