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All Journal Jurnal Ilmiah MTG Journal of Petroleum and Geothermal Technology Journal of Applied Sciences, Management and Engineering Technology (JASMET)
Ambara Putra, I Putu Raditya
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Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Earth & Planetary Sciences Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology

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The use of PhaseNet and GaMMA in microseismic monitoring in geothermal fields Ambara Putra, I Putu Raditya
Jurnal Ilmiah MTG Vol 14, No 2 (2023): Jurnal Ilmiah MTG Volume 14 No.2 Tahun 2023
Publisher : Jurusan Teknik Geologi Fakultas Teknologi Mineral UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/jmtg.v14i2.11436

Abstract

Due to its potential to decrease greenhouse gas emissions and decrease dependence on fossil fuels, geothermal energy has recently attracted more attention as a renewable and sustainable form of power generation. For evaluating the reservoir's integrity and understanding the underlying geomechanical processes in geothermal fields, microseismic monitoring is crucial. To accurately analyze and understand these microseismic occurrences, it is necessary to accurately identify their phases. Therefore, in this study, we used the PhaseNet-GaMMA combination to identify the arrival times of P and S and associate them to determine the microseismic events of these phases. PhaseNet-GaMMA succeeded in detecting a greater number of phases and events compared to catalog data, where the identification match rate was 85%. Even so, the time required for automatic detection of PhaseNet-GaMMA is relatively short and simple, so it is very good if used as an initial stage in the process of identifying phases and microevents in geothermal fields.
The use of PhaseNet for Event Identification of Microearthquake Monitoring in Geothermal Field Al Hakim, Muhamad Firdaus; Ambara Putra, I Putu Raditya
Journal of Petroleum and Geothermal Technology Vol. 6 No. 1 (2025): May
Publisher : Universitas Pembangunan Nasional "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/jpgt.v6i1.13437

Abstract

Geothermal energy is a sustainable energy source that requires continuous microseismic monitoring to assess reservoir integrity and geomechanical behavior. Traditional phase identification methods are challenged by noisy environments and complex waveforms, especially in geothermal fields. This study explores the efficacy of PhaseNet, a deep learning neural network model, in detecting P and S wave arrival times for micro-earthquake events. The PhaseNet model was retrained using local seismic data from a geothermal field and tested for its performance in identifying seismic phases. The results were validated against a manual seismic catalog, with additional clustering and association analysis conducted using GaMMA and hypocenter locations determined with NonLinLoc. The findings demonstrate that PhaseNet, combined with GaMMA, provides robust phase detection capabilities, essential for early-stage monitoring in geothermal development.
Determining the Best Zone for Waste Storage Ponds: Integrating DEM analysis and Satellite Gravity data in the Prospect Area of Ungaran Geothermal Mining Working Area, Semarang, Indonesia. Humairoh, Wahyuni Annisa -; Mardiati, Dani; Ambara Putra, I Putu Raditya
Journal of Applied Sciences, Management and Engineering Technology Vol 6, No 2 (2025)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jasmet.2025.v6i2.8194

Abstract

The Ungaran Geothermal Mining Working Area, Mount Ungaran, has geothermal prospects around the Gedongsongo and Nglimut areas, which have the potential to develop as Indonesian geothermal exploration projects. The challenges in developing geothermal exploration projects in Indonesia are the PLTP sector, which generates geothermal waste in the form of brine and geothermal mud. If discharged into the environment, this waste can pose a threat to human health and ecosystems. This study aimed to specify the most suitable zone for waste storage ponds in the Ungaran geothermal prospect area. The method integrates data analysis of Digital Elevation Model (DEM) imagery, Landsat imagery, and air gravity data, which produces integrated maps, such as Maps of Fault and Fractures density and Maps of Land Cover. Second vertical derivative (SVD) analysis from air gravity data is also used to ensure the presence of a structure. There are five parameters for determining the pond-making zone: Not a residential area with a slope of less than 15%, distance from the fault is more than 200 m, distance from the road is more than 100 m, and distance from areas of geothermal manifestations such as hot springs and fumaroles is more than 200 m. Based on the interpretation of the integrated maps resulting from the analysis, several zones are suitable for creating waste storage ponds in the Nglimut and Gedongsongo prospect areas. The Nglimut area has potential zones, in contrast. In the Gedongsongo area, there are no potential zones. The Nglimut prospect has two possible zones; the best zone is N2, where all five parameters are perfectly satisfied. The northern area of N1 has one geothermal manifestation (hot spring). The best-to-fair zones are N2 and N1.
The use of PhaseNet and GaMMA in microseismic monitoring in geothermal fields Ambara Putra, I Putu Raditya
Jurnal Ilmiah MTG Vol 14 No 2 (2023): Jurnal Ilmiah MTG Volume 14 No.2 Tahun 2023
Publisher : Jurusan Teknik Geologi Fakultas Teknologi Mineral UPN "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/jmtg.v14i2.11436

Abstract

Due to its potential to decrease greenhouse gas emissions and decrease dependence on fossil fuels, geothermal energy has recently attracted more attention as a renewable and sustainable form of power generation. For evaluating the reservoir's integrity and understanding the underlying geomechanical processes in geothermal fields, microseismic monitoring is crucial. To accurately analyze and understand these microseismic occurrences, it is necessary to accurately identify their phases. Therefore, in this study, we used the PhaseNet-GaMMA combination to identify the arrival times of P and S and associate them to determine the microseismic events of these phases. PhaseNet-GaMMA succeeded in detecting a greater number of phases and events compared to catalog data, where the identification match rate was 85%. Even so, the time required for automatic detection of PhaseNet-GaMMA is relatively short and simple, so it is very good if used as an initial stage in the process of identifying phases and microevents in geothermal fields.
Co-Authors Dani Mardiati, S.T., M.Eng. Humairoh, Wahyuni Annisa - Muhamad Firdaus Al Hakim