Geohazard impact and gas reservoir pressure dynamics in the Zagros Fold-Thrust Belt: An environmental perspective

• Hybrid GIS-DSS model enhances earthquake risk assessment in the ZFTB. • Machine learning predicts landslide risk with 92% accuracy using random forest. • Strong correlation found between seismic activity and gas reservoir pressure changes. • Landslide susceptibility map identifies critical zones for proactive management. • Real-time data integration enables dynamic risk assessments for gas reservoirs. The Zagros Fold-Thrust Belt (ZFTB) presents a unique intersection of geohazards and gas reservoir dynamics, shaped by the ongoing tectonic activity resulting from the collision of the Arabian and Eurasian plates. This study aims to assess the risk of earthquake-induced landslides and their impact on gas reservoir pressure dynamics – with a particular focus on the Kabir Kuh gas field – identified as a critical area for monitoring due to its vulnerability to seismic events. A novel hybrid model is introduced that integrates geographic information system (GIS) mapping, decision support system (DSS) modeling, and machine learning algorithms. By analyzing a century's worth of seismic data alongside real-time environmental parameters, the model demonstrates a predictive accuracy of 92% using Random Forest algorithms, significantly outperforming traditional methods. The findings reveal a strong correlation between seismic activity and fluctuations in gas reservoir pressure, with an average pressure change of ±150 psi observed during significant seismic events. A landslide susceptibility map was generated, pinpointing regions that require proactive management strategies, particularly where significant landslide potential threatens gas field stability. Identifying the Seymareh landslide as a monumental geological event underscores the impact of landslide hazards on gas field integrity. This research emphasizes the integration of advanced predictive techniques into seismic risk assessments, providing actionable insights for the sustainable gas reservoir management in seismically active regions. The necessity for continuous monitoring and the implementation of advanced geotechnical measures are highlighted as essential components of effective geohazard management. This study contributes to understanding the interplay between seismic hazards and gas reservoir dynamics, offering a comprehensive framework for future research and practical applications in risk management and environmental sustainability.

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Publication Details

Journal
Geosystems and Geoenvironment
Published
2025-03-07
DOI
https://doi.org/10.1016/j.geogeo.2025.100362
Citations
20
Primary Topic
earthquake and tectonic studies
Type
article
Field-Weighted Citation Impact
37.33
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article

Geohazard impact and gas reservoir pressure dynamics in the Zagros Fold-Thrust Belt: An environmental perspective

Pooria Kianoush, Mohammad Ali Ganjavian, Ali Solgi, Mahsa Asghari et al.
20 citations
Geosystems and Geoenvironment
earthquake and tectonic studies
37.33
article

Geohazard impact and gas reservoir pressure dynamics in the Zagros Fold-Thrust Belt: An environmental perspective

Pooria Kianoush, Mohammad Ali Ganjavian, Ali Solgi, Mahsa Asghari, Zahra Maleki
article en
20 citations

Abstract

• Hybrid GIS-DSS model enhances earthquake risk assessment in the ZFTB. • Machine learning predicts landslide risk with 92% accuracy using random forest. • Strong correlation found between seismic activity and gas reservoir pressure changes. • Landslide susceptibility map identifies critical zones for proactive management. • Real-time data integration enables dynamic risk assessments for gas reservoirs. The Zagros Fold-Thrust Belt (ZFTB) presents a unique intersection of geohazards and gas reservoir dynamics, shaped by the ongoing tectonic activity resulting from the collision of the Arabian and Eurasian plates. This study aims to assess the risk of earthquake-induced landslides and their impact on gas reservoir pressure dynamics – with a particular focus on the Kabir Kuh gas field – identified as a critical area for monitoring due to its vulnerability to seismic events. A novel hybrid model is introduced that integrates geographic information system (GIS) mapping, decision support system (DSS) modeling, and machine learning algorithms. By analyzing a century's worth of seismic data alongside real-time environmental parameters, the model demonstrates a predictive accuracy of 92% using Random Forest algorithms, significantly outperforming traditional methods. The findings reveal a strong correlation between seismic activity and fluctuations in gas reservoir pressure, with an average pressure change of ±150 psi observed during significant seismic events. A landslide susceptibility map was generated, pinpointing regions that require proactive management strategies, particularly where significant landslide potential threatens gas field stability. Identifying the Seymareh landslide as a monumental geological event underscores the impact of landslide hazards on gas field integrity. This research emphasizes the integration of advanced predictive techniques into seismic risk assessments, providing actionable insights for the sustainable gas reservoir management in seismically active regions. The necessity for continuous monitoring and the implementation of advanced geotechnical measures are highlighted as essential components of effective geohazard management. This study contributes to understanding the interplay between seismic hazards and gas reservoir dynamics, offering a comprehensive framework for future research and practical applications in risk management and environmental sustainability.

Geosystems and GeoenvironmentVol. 4(2)
National Iranian Oil Company (Iran) (IR), Islamic Azad University South Tehran Branch (IR), Islamic Azad University, Science and Research Branch (IR), Islamic Azad University, Shahrood (IR)
Climate action
Openalex Percentile: Top 0%
earthquake and tectonic studies
37.33
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