A seismic sensor 10 comprises an acceleration acquisition unit 21, an acceleration waveform generation unit 22, a frequency sensing unit 24, and an earthquake determination unit 25. The acceleration acquisition unit 21 detects vibration and measures the acceleration of the vibration. The acceleration waveform generation unit 22 generates an acceleration waveform that indicates the relation between the elapsed time and the acceleration measured by the acceleration acquisition unit 21. The frequency sensing unit 24 senses the frequency of the acceleration waveform generated by the acceleration waveform generation unit 22 using a zero-crossing method. The earthquake determination unit 25 determines whether or not there is an earthquake on the basis of the frequency sensed by the frequency sensing unit 24.

A method of detecting an earthquake is described, comprising receiving a signal representative of measurements of three-dimensional acceleration of the device as a function of time; frequency filtering of the signal; determining, from the filtered signal, data representative of acceleration directions as a function of time; an earthquake being detected if a) the magnitude of the acceleration is greater than a first threshold and the directions of the acceleration are substantially collinear with one another for a first time interval; or b) the directions of acceleration are substantially collinear with one another during a second time interval, and the directions of acceleration are substantially collinear with one another during a third time interval subsequent to the second time interval, and the directions of acceleration of the second interval and the third interval are substantially orthogonal.

A data-driven linear filtering method to recover microseismic signals from noisy data/observations based on statistics of background noise and observation, which are directly extracted from recorded data without prior statistical knowledge of the microseismic source signal. The method does not depend on any specific underlying noise statistics and works for any type of noise, e.g., uncorrelated (random/white Gaussian), temporally correlated and spatially correlated noises. The method is suitable for microquake data sets that are recorded in contrastive noise environments. The method is demonstrated with both field and synthetic data sets and shows a robust performance.

A data-driven linear filtering method to recover microseismic signals from noisy data/observations based on statistics of background noise and observation, which are directly extracted from recorded data without prior statistical knowledge of the microseismic source signal. The method does not depend on any specific underlying noise statistics and works for any type of noise, e.g., uncorrelated (random/white Gaussian), temporally correlated and spatially correlated noises. The method is suitable for microquake data sets that are recorded in contrastive noise environments. The method is demonstrated with both field and synthetic data sets and shows a robust performance.

A method of detecting an earthquake is described, comprising receiving a signal representative of measurements of three-dimensional acceleration of the device as a function of time; frequency filtering of the signal; determining, from the filtered signal, data representative of acceleration directions as a function of time; an earthquake being detected if a) the magnitude of the acceleration is greater than a first threshold and the directions of the acceleration are substantially collinear with one another for a first time interval; or b) the directions of acceleration are substantially collinear with one another during a second time interval, and the directions of acceleration are substantially collinear with one another during a third time interval subsequent to the second time interval, and the directions of acceleration of the second interval and the third interval are substantially orthogonal.