The Analysis of Triaxial Passive Seismic Signal Data Using Python Scripting Language - Fazriati, Evi; Bahri, Ayi Syaeful; Rosandi, Yudi (Journal of physics. Conference series, 2022)
The local geological and the physical conditions of earth’s ground defines its vibration characteristics. Such vibrations can be detected using conventional passive seismic methods, i.e., a microtremor recording method, which acquires ground vibration data in a suitable sampling time. The method utilizes natural seismic sources, originating from both natural and artificial sources. In this work we present the algorithm to process passive seismic signals, recorded from a laboratory developed triaxial seismic logging device. We use python scripting language to perform the signal processing work. We analyzed the Horizontal to Vertical Spectral Ratio (HVSR) of the signal to determine the on-site natural frequency. The results were compared to the reference data from a high sensitivity microtremor apparatus, at the exact same location. The results show a fair agreement between the low sensitivity and the high sensitivity seismometer, on the sites with low environmental disturbance. However, the values fluctuate significantly at noisy sites. Either way, our results measure the correct dominant frequencies as expected from the geological condition.