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Detection of volcanic microearthquakes based on homomorphic deconvolution and STA/LTA

Abstract:

Maintaining the seismic monitoring of volcanoes has resulted in a greater understanding of the relationship between the volcano and its environment. This monitoring also provides information on the relationship between the seismic activity of a volcano and possible eruptions. Therefore, automatic detection systems of microearthqueakes are of great importance in this task. In this sense, The aim of this work is to develop a microearthquake detector that search to estimate the signal of the seismic source by reducing the noise present in the registered signal by sensors. For this purpose, it has been proposed the use of homomorphic deconvolution to estimate the signal of the volcanic microearthquake from the signal received by the different seismic sensors that monitor the Cotopaxi volcano. The homomorphic deconvolution technique is accompanied by the calculation of the root mean square energy as a function g(x) for the Short Time Average over Long Time Average (STA/LTA) algorithm. The proposed detector was evaluated with several datasets, including a record of approximately 5 days (7000 min) with 350 seismic events, the data set was provided and labeled by experts from IGEPN, where, a 98.29% of detection probability and an 99.31% of accuracy it was obtained. Additionally, the volcanic microearthquake signals show a gain of 10dB on average after homomorphic deconvolution, when estimating the Signal to Noise Ratio (SNR).