Earthquake Prediction Using CNN Algorithm

The recent evolution of induced seismicity in the world calls for exhaustive catalogues to improve seismic hazard assessment. Over the last decades, the volume of seismic data has increased exponentially, creating a need for efficient algorithms to reliably detect and locate earthquakes. Today's most elaborate methods scan through the plethora of continuous seismic records, searching for repeating seismic signals. We leverage the recent advances in artificial intelligence and present CNN, a highly scalable convolutional neural network for earthquake detection and location from a single waveform. We apply our technique to study the induced seismicity. Our algorithm is orders of magnitude faster than established methods.