【企画講演】資源探査における大規模データと掘削情報プロセッシングの動向　 ［3/14(金) AM 　第1会場］

[3K0101-06-03] GIS-based delineation of geothermal potential zones over Java Island, Indonesia using combination of Fuzzy logic and Geostatistics

○Tedi Atmapradhana^{1[博士課程]}, Asep Saepuloh², Katsuaki Koike¹ (1. Kyoto University, 2. Institut Teknologi Bandung)

司会：桑谷　立（海洋研究開発機構）

キーワード：Geothermal, Remote Sensing, Fuzzy Ordinary Kriging, Geostatistics, Weighted Fuzzy Logic

Indonesia, positioned within the tectonically active Ring of Fire, possesses abundant geothermal resources, making it a significant locus for renewable energy exploration. This geothermal potential is amplified by the cost-efficiency of exploration within these volcanically active regions. To enhance the understanding and spatial delineation of these geothermal prospects, this study integrates a novel methodological framework that synergizes Weighted Fuzzy Logic (WFL) and geostatistics, forming an innovative approach termed Fuzzy Ordinary Kriging (FOK). Specifically, Landsat 8 Operational Land Imager (OLI) data including bands 3,4,5,6,and7 are utilized to assess vegetation health using the Vegetation Index Considering Greenness and Shortwave Infrared (VIGS) algorithm, which aids in identifying stress signatures potentially indicative of subsurface geothermal activity. Concurrently, thermal infrared data from the ASTER Thermal Infrared Sensor (TIRS) provide critical insights into surface temperature anomalies, a key indicator of underlying geothermal processes. Complementing these datasets, aeromagnetic data are employed to elucidate the magnetic characteristics of subsurface lithologies, particularly around volcanic structures, while gravity data facilitate the detection of Bouguer anomalies, indicative of density variations associated with geothermal reservoirs. The integration of these diverse datasets through the FOK methodology has successfully delineated high-potential geothermal zones across Java Island. Notably, this approach has identified previously unrecognized geothermal anomalies, particularly around Mt. Sindoro and the eastern flanks of Mt. Semeru. Intriguingly, the analysis also reveals significant anomalies in the northern sector near Mt. Ijen, underscoring the method's capability to uncover hidden geothermal prospects that conventional reconnaissance techniques might overlook. This integrated approach thus represents a significant advancement in geothermal exploration, offering a more precise and comprehensive tool for identifying and characterizing Indonesia's rich geothermal potential.