Real-time earthquake monitoring using a search engine method

Area of Science:

• Geophysics
• Seismology
• Computational Science

Background:

• Rapid earthquake characterization is crucial for effective disaster response.
• Current methods for determining earthquake source-focal mechanisms are time-consuming, often taking minutes to hours.
• Faster analysis can enable timely evacuations and mitigate damage.

Purpose of the Study:

• To develop a significantly faster method for inferring earthquake parameters, including source-focal mechanisms.
• To create an earthquake search engine analogous to web search engines for seismogram analysis.
• To reduce the time required for critical earthquake information dissemination.

Main Methods:

• Developed a novel earthquake search engine utilizing a fast computer search algorithm.
• Applied the method to a large seismogram database to find matching waveforms.
• The engine efficiently searches for waveforms that best fit input seismic data.

Main Results:

• The developed earthquake search engine is thousands of times faster than exact search methods.
• Successfully inferred earthquake parameters, including source-focal mechanism, in under 1 second for a real-world event.
• Demonstrated rapid analysis using long-period surface wave data for an Mw 5.9 earthquake in Xinjiang, China.

Conclusions:

• The novel earthquake search engine dramatically accelerates the determination of earthquake source-focal mechanisms.
• This advancement has the potential to significantly improve real-time earthquake hazard assessment and response.
• The method offers a scalable and efficient solution for rapid seismic data analysis.