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Enhancing earthquake prediction and infrastructure resilience

Enhancing earthquake prediction and infrastructure resilience


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Understanding the effect of rock permeability

Recent research conducted by the Jackson School of Geosciences has revealed the permeability of rocks as a critical factor in understanding slow-moving earthquakes. Unlike sudden, destructive seismic events, slow-slip events release tectonic forces gradually over weeks or months, allowing researchers to study seismic cycles without catastrophic consequences. This insight is pivotal for earthquake prediction and has important implications for the design and resilience of infrastructure critical for sustainable development and energy security.

Investigation of the Hikurangi Margin

The research team focused on the Hikurangi Zone, a subduction zone in New Zealand known for its annual slow-slip events. During multiple missions in 2019 and 2022, scientists collected rock samples from various outcrops near the margin. These samples underwent rigorous laboratory testing at the University of Texas to determine their permeability and elastic properties. The results revealed a clear relationship between rock permeability levels and the regular occurrence of slow slip events in this subduction zone.

Mechanism of slow slip events

This phenomenon is mainly controlled by an impermeable rock layer that acts as a cover, trapping fluids within the pores of the underlying rock layers. As fluid pressure increases, it reaches a threshold that triggers a slow slip event, temporarily increasing the permeability of the rock and allowing trapped fluids to escape. After the event, the rock gradually heals, and the cycle repeats.

Strengthening resilience and preparedness

Understanding the role of rock permeability in slow-moving earthquakes is crucial to enhancing predictive models. By incorporating this knowledge into seismic models, scientists aim to improve the accuracy of earthquake prediction. This progress is essential for developing resilient infrastructure, especially in areas prone to seismic activity. For businesses and industries, these predictive capabilities can help build and maintain energy infrastructure, ensuring it can withstand and recover from seismic events.

Implications for energy infrastructure and ESG objectives

The implications of this research extend to energy security and sustainability. Energy infrastructure, such as power lines, pipelines, and renewable energy facilities, must be designed to withstand seismic disturbances and recover quickly. Improved earthquake prediction models contribute to improved risk management strategies, in line with ESG objectives by reducing environmental impact and ensuring the safety and reliability of energy supply chains.

Lead author Nicola Tessato and his team believe their research will help improve predictive models, paving the way toward more accurate earthquake prediction. This progress is vital for vulnerable regions, providing a roadmap for safer and more sustainable development. By carefully analyzing rock samples from the Hikurangi Margin, the team is unlocking the geological puzzle of earthquake prediction, contributing to a future where we can better anticipate and mitigate risks associated with seismic activity.




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