Risk Assessment of Sudden Coal and Gas Outbursts Based on 3D Modeling of Coal Seams and Integration of Gas-Dynamic and Tectonic Parameters

Sudden coal and gas outbursts pose a significant hazard in deep-seated coal seam extraction, necessitating reliable risk assessment methods. Traditionally, assessments focus on gas-dynamic parameters, but experience shows they must be supplemented with tectonic factors such as fault-related disturba...

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Bibliographic Details
Main Authors: Vassiliy Portnov, Adil Mindubayev, Andrey Golik, Nurlan Suleimenov, Alexandr Zakharov, Rima Madisheva, Konstantin Kolikov, Sveta Imanbaeva
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Fire
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Online Access:https://www.mdpi.com/2571-6255/8/6/234
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Summary:Sudden coal and gas outbursts pose a significant hazard in deep-seated coal seam extraction, necessitating reliable risk assessment methods. Traditionally, assessments focus on gas-dynamic parameters, but experience shows they must be supplemented with tectonic factors such as fault-related disturbances, weak interlayers, and increased fracturing. Even minor faults in the Karaganda Basin can weaken the coal massif and trigger outbursts. The integration of 3D modeling enhances risk evaluation by incorporating both dynamic (gas-related) and static (tectonic) parameters. Based on exploratory drilling and geophysical studies, these models map coal seam geometry, fault positioning, and high-risk structural zones. In weakened coal areas, stress distribution changes can lead to avalanche-like gas releases, even under normal gas-dynamic conditions. An expert scoring system was used to convert geological and gas-dynamic data into a comprehensive risk index guiding preventive measures. An analysis of Karaganda Basin incidents (1959–2021) shows all outbursts occurred in geological disturbance zones, with 43% linked to fault proximity, 30% to minor tectonic shifts, and 21% to sudden coal seam changes. Advancing 3D modeling, geomechanical analysis, and microseismic monitoring will improve predictive accuracy, ensuring safer coal mining operations.
ISSN:2571-6255