Spatiotemporal Clustering of Induced Seismicity in Enhanced Geothermal Systems
Malla, Birasa
Malla, Birasa
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Abstract
Microseismic events induced by fluid injection and production provide valuable insight into the behaviour of enhanced geothermal systems. At The Geysers geothermal field, the spatial and temporal distribution of seismicity is closely linked to reservoir operations. This work aims to improve understanding of the relationship between fluid flow and induced seismicity, providing insights that may inform adaptive reservoir management strategies. In this study, we apply the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to a microseismic catalog from The Geysers to identify clusters that may correspond to activated fracture networks. Unlike centroid-based methods, DBSCAN is well-suited for this application because it can detect arbitrarily shaped clusters and effectively distinguish noise from meaningful events. The resulting clusters are compared both spatially and temporally with injection and production data to investigate how fluid flow influences the distribution and evolution of seismicity. Preliminary results indicate that clustering patterns exhibit strong spatiotemporal correlations with reservoir operations.
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Date
1/1/2026
Student Status
Graduate Student
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Poster
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Civil Engineering
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College of Engineering and Mathematical Sciences
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Engineering