Application of Ensemble Empirical Mode Decomposition for Noise Reduction of Passive Seismic Signals to Identify Hydrothermal Activity Signals Characteristic, Case Study: Mt. Lamongan, East Java - Indonesia

Abstract

Noise reduction process of non-linear and non-stationary signal done with divide the data to obtain linear event called IMF (Intrinsic Mode Function). Noise reduction used Empirical Mode Decomposition (EMD) method. EMD decompose seismic signals into a number of components intrinsic oscillation. Each component of the Intrinsic Mode Function (IMF) has vary frequency according to characteristics of the field. The decompose based on assumption that the data is composed of intrinsic oscillation models. Ensemble empirical mode decomposition (EEMD) method as the development of empirical mode decomposition (EMD) developed by Zhaohua Wu and Norden E. Huang (2009), Jiang and Zhang (2010) to eliminate mode mixing in EMD method. The process of noise reduction applied to microseismic signals in the geothermal field to determine the estimation position of hydrothermal dynamics in the subsurface. Hydrothermal movement in the pore spaces of rocks cause micro oscillations as a secondary source with high pressure and high temperatures. The primary signal was recorded come from nature considered as ambient noise. The movement of hydrothermal has a low frequency between 1 Hz to 5 Hz. The case study this research was conducted in the geothermal potential area of Mt. Lamongan, East Java. The Microseismic portable developed by GFZ, it can recorded a lot of kind signals source, for example : hydrothermal, tectonic earthquake, and local noise around the stations. The results of research used to plan long-period microseismic acquisition (Broadband).