Geology & Geophysics Editors' Highlights

When Will the Next Failure Be?

Unprecedented images of fracture networks in laboratory scale experiments mixed with machine learning algorithms help predict the timing of the next failure.

Source: Geophysical Research Letters


Forecasting impending earthquake rupture is a fundamental goal in the Earth Sciences. Detecting and understanding precursory activity, be that foreshocks, changes in b-value, aseismic slip or a nucleation phase, is fundamental to achieve this goal. Although some precursory activity has been documented, it has not yet been systematically observed.

McBeck et al. [2020] use triaxial compression experiments on different rock samples with multiple high resolution X-ray tomography images to map the location and the evolution of cracks and pores within each sample. They then take advantage of machine learning algorithms to identify the key parameters that can inform the timing of macroscopic failure.

These experiments open a window into the evolution of precursors of rock failure and its timing. The question remains as to how the laboratory conditions are to be extrapolated to crustal conditions, including for example the need to forecast the eventual magnitude of an impending earthquake. Nevertheless, understanding which parameters are key should help inform our goals, such as mapping fracture networks in this work, and ultimately increase our forecasting power for large earthquakes.

Citation: McBeck, J. A., Aiken, J. M., Mathiesen, J., Ben‐Zion, Y., & Renard, F. [2020]. Deformation precursors to catastrophic failure in rocks. Geophysical Research Letters, 47, e2020GL090255.

―Germán A. Prieto, Editor, Geophysical Research Letters

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