Detecting the Preparatory Phase of Induced Earthquakes at The Geysers (California) Using K‐Means Clustering

• Published in: Journal of geophysical research. Solid earth Vol. 128; no. 10
• Main Authors: Iaccarino, A. G., Picozzi, M.
• Format: Journal Article
• Language: English
• Published: Washington Blackwell Publishing Ltd 01-10-2023
• Subjects: Catalogues; Cluster analysis; Clustering; Earthquake forecasting; Earthquake prediction; Earthquakes; Evolution; Fluids; Fractal geometry; Geophysics; Geothermal fields; Geysers; Hot springs; Injection; Machine learning; Nucleation; Physics; Seismic activity; Seismicity; Seismology; Tectonics; Unsupervised learning; United States > US; California
• ISSN: 2169-9313; 2169-9356
• DOI: 10.1029/2023JB026429

Abstract
The generation of strong earthquakes is a long‐debated problem in seismology, and its importance is increased by the possible implications for earthquake forecasting. It is hypothesized that the earthquake generation processes are anticipated by several phenomena occurring within a nucleation region. These phenomena, also defined as preparatory processes, load stress on the fault leading it to reach a critical state. In this paper, we investigate the seismicity preceding 19 moderate (
M
w
 ≥ 3.5) earthquakes at The Geysers, Northern California, aiming to verify the existence of a preparatory phase before their occurrence. We apply an unsupervised K‐means clustering technique to analyze time series of physics‐related features extracted from catalog information and estimated for events occurred before the mainshocks. Specifically, we study the temporal evolution of the
b
‐value from the Gutenberg‐Richter (
b
), the magnitude of completeness (
Mc
), the fractal dimension (
Dc
), the inter‐event time (
dt
), and the moment rate (
). Our analysis shows that out of 19 moderate magnitude events considered, a common preparatory phase for 11 events is clearly identified, plus other five events for which we can guess a preparatory phase but with different characteristics from the previous ones. The latter result confirms that even within the same tectonic context different possible activation behaviors may exist. The duration of the preparatory process ranges between about 16 hr and 4 days. We observe that also for the retrieved preparatory process a decrease in
b
,
Mc
, and
Dc
, and an increase of
. Finally, we show a clear correlation between events with a preparation phase and the location of injection's wells, suggesting an important role of fluids in the preparatory process.
Plain Language Summary
We investigate the preparatory phase of moderate magnitude‐induced earthquakes at The Geysers geothermal field in California by studying the spatiotemporal evolution and dynamic properties of small magnitude events and using an unsupervised machine learning approach. To this aim, we rely on features extracted from seismic catalog information that are used for a K‐means clustering analysis. Our results highlight changes in the seismicity characteristics before the moderate‐induced earthquakes. We find that most of the analyzed target earthquakes present a preparatory phase, and that most of the cases the latter presents common characteristics in their key features. We show that the seismicity clusters in space and time before moderate events also becoming more energetic. We estimate a duration for the detected preparatory phases that ranges from 16 hr to 4 days. Finally, we show that the presence of a preparatory phase is correlated to the proximity of injection's wells, suggesting a significant role of fluids in the earthquake's nucleation process.
Key Points
Moderate‐induced earthquakes at The Geysers can be preceded by a preparatory phase detectable using K‐means clustering on catalog features
The detected preparatory phase has common characteristics presenting negative trends of
b
‐value,
Mc
, and
Dc
and a positive trend of
The earthquakes with a preparatory phase are located nearer to the injection's wells in the area than the events without it