Japan Geoscience Union Meeting 2019

Presentation information

[J] Poster

S (Solid Earth Sciences ) » S-CG Complex & General

[S-CG62] Potentiality of Machine Learning in Solid Earth Sciences

Sun. May 26, 2019 3:30 PM - 5:00 PM Poster Hall (International Exhibition Hall8, Makuhari Messe)

convener:Takahiko Uchide(Research Institute of Earthquake and Volcano Geology, Geological Survey of Japan, National Institute of Advanced Industrial Science and Technology (AIST)), Hirokuni Oda(Institute of Geology and Geoinformation, Geological Survey of Japan, AIST)

[SCG62-P03] Detection of Gas Bubble signals recorded at the OBS Stations by Machine-Learning

*emmy TY CHANG1 (1.Institute of Oceanography, National Taiwan University)

Keywords:gas emission, bubble, machine learning, Ocean bottom seismometer

Along the OBS seismograms, the waveforms of gas emission signals exhibit a high-frequency resonant vibration alike the bubble bursting at the free surface of a non-Newtonian fluid. Every single signal is a short-duration event (hereafter termed as “SDE”, <1.0 second). In this study, we shall develop the computer algorithm to detect the SDE signals along the OBS seismograms. Our work carried out in 2018 has been laid on the mathematical matching of the bubble signals. We conclude that even though the bubbles exhibit a specific waveform, the mathematical equation cannot perfectly describe the bubble with all ambient conditions at the seafloor. Our strategy is to adopt the Machine Learning (ML) to identify bubbles by images. In the following years, two phases of our project are designed as (i) Establishing the method to quantify the SDE signals by means of ML modeling: we shall train a neural network model with varied parameters to gain a complete estimation of the bubble signals within our OBS records. (ii) The experiments with OBS instruments will also be used for tests of generating different waveforms in water tanks of the ifremer as well as a constrained offshore area (e.g. lake), to provide referenced waveforms for the SDE or bubble signals.