IDENTIFICATION OF FAULTS IN THE SUBSURFACE OF JAVA ISLAND USING THE AMBIENT NOISE TOMOGRAPHY METHOD
This study uses the Ambient Noise Tomography (ANT) method to describe the Rayleigh wave velocity model on the subsurface seismic structure of Java Island which has complex tectonic conditions. The data used in this study is waveform data on the vertical component of 99 BMKG stationary seismic sensor networks spread across Java Island in 2021. Waveform data processing is carried out starting from single data preparation, cross correlation and stacking, cross correlation analysis, curve dispersion measurement, group velocity tomography and the last is the interpretation of the results of the study. The inversion results produce tomographic images of the Rayleigh wave group velocity on subsurface seismic structures ranging from 1.88 km/s to 2.60 km/s and experiencing an increase in the Rayleigh wave group velocity in each measurement period in the Java Island region. This study succeeded in clearly identifying faults and volcanic zones in Java Island which are in the contrast boundary areas of low velocity anomaly zones and high velocity anomaly zones.