Visualising the Ridgcrest Earthquakes using Wavefield Reconstruction

Jack B. Muir, & Zhongwen Zhan

Published August 9, 2019, SCEC Contribution #9403, 2019 SCEC Annual Meeting Poster #265

The high station density of the Southern California Seismic Networks gives us the opportunity to treat earthquake wavefields as unified objects rather than as a collection of individual seismograms, allowing robust computation of useful higher order representations of seimsic data such as spatial derivatives. Straightforward interpolation of the wavefield, however, leads to unphysical wavefields that are dominated by station noise. We use compressive sensing techniques to perform an optimal smoothed interpolation of the wavefield from Ridgecrest sequence earthquakes by first converting the seismograms to the wavelet domain in time, and then applying a L1 regularized and scale penalized curvelet decomposition in space --- we call this technique wavefield reconstruction. This technique produces smooth wavefronts at periods as low as 8s, allowing a detailed view of the wave propagation in space.

Muir, J. B., & Zhan, Z. (2019, 08). Visualising the Ridgcrest Earthquakes using Wavefield Reconstruction. Poster Presentation at 2019 SCEC Annual Meeting.

Related Projects & Working Groups
Ridgecrest Earthquakes