09:50 〜 10:10
[U05-03] 地熱関連情報の3次元モデリングと統合による国スケールでの地熱資源ポテンシャル評価
★招待講演
キーワード：深部温度、機械学習、地球統計学、リモートセンシング、ポテンシャルマッピング
The heat in the shallow crust within several km depth can be used as geothermal energy for electric power generation. The importance of geothermal energy has recently increased in terms of renewable energy-based power generation owing to its high power output, high operation rate, and low CO2 emissions. However, as well as other natural resources, geothermal resources are deeply seated and the successful rate to reach reservoirs is low in general. For this problem, accurate evaluation of geothermal resources and detection/specification of high potential zones are more and more important and required globally by integrating multiple geoscience datasets related to geothermal features. Aiming at this achievement, my Laboratory targeted four wide areas so far: whole Japan Islands, whole Java Islands (Indonesia), surrounding Gulf of Suez (Egypt), and whole China in which large increase in geothermal energy use is required socially in common.
Depending on data availability, the datasets used for the potential evaluation and mapping are different. For Japan, the main dataset is well-temperature logging data at 1422 sites with 93,084 data in total. To supplement the temperature data, crustal properties composed of the Curie point depth, water quality of hot springs, active volcano distribution, and surface geology, are incorporated. Because well-temperature logging data were not obtained for Indonesia, a remote sensing-based approach is adopted for potential mapping in Java Islands using multispectral and hyperspectral satellite images for detecting and locating hydrothermal alteration minerals and vegetation stress related to geothermal activity, thermal infrared images for detecting thermal anomalies in night time, lineament distributions extracted from the SRTM Digital Elevation Model (DEM) for modeling fracture system that act as geothermal fluid pathways, Quaternary volcano distribution data, and geophysical datasets composed of seismic activity and gravity and aeromagnetic anomalies that are related to magmatic activities and deep geologic structures. For the Gulf of Suez, borehole temperate data from 281 offshore oil and gas wells, calculated geothermal gradients, and lineament data extracted from a shaded DEM were used. Collection of the geothermal datasets for China is in progress and limited to heat flow and shallow well-temperature logging data to date.
Three-dimensional modeling of temperature to great depths in Japan, the Gulf of Suez, and China and the detection and integration of geothermal features in Java Island are the main cores for resource-potential evaluation. For the spatial modeling and data integration techniques, machine learning such as deep neural network and clustering, decision tree analysis, geostatistics, neural kriging, maximum entropy, and fuzzy logic are used. As examples of the featured results, promising areas of supercritical geothermal resources and zones with large production power from a relatively shallow depth range were discovered throughout Japan, several unexplored high-potential zones were estimated outside volcanic areas throughout Java Islands, and two high potential zones with high temperature and heat flux due to, probably, large radiogenic heat and permeability and development of fractures were identified in the surrounding Gulf of Suez.
Furthermore, a probabilistic assessment of the power potential for 30 years of utilization was tried for two fields in Japan and Indonesia by a numerical reservoir simulation. These approaches are expected to contribute to increasing power generation by flush and/or binary system and enhanced geothermal system (EGS) and planning the sustainable utilization of geothermal resources.
Depending on data availability, the datasets used for the potential evaluation and mapping are different. For Japan, the main dataset is well-temperature logging data at 1422 sites with 93,084 data in total. To supplement the temperature data, crustal properties composed of the Curie point depth, water quality of hot springs, active volcano distribution, and surface geology, are incorporated. Because well-temperature logging data were not obtained for Indonesia, a remote sensing-based approach is adopted for potential mapping in Java Islands using multispectral and hyperspectral satellite images for detecting and locating hydrothermal alteration minerals and vegetation stress related to geothermal activity, thermal infrared images for detecting thermal anomalies in night time, lineament distributions extracted from the SRTM Digital Elevation Model (DEM) for modeling fracture system that act as geothermal fluid pathways, Quaternary volcano distribution data, and geophysical datasets composed of seismic activity and gravity and aeromagnetic anomalies that are related to magmatic activities and deep geologic structures. For the Gulf of Suez, borehole temperate data from 281 offshore oil and gas wells, calculated geothermal gradients, and lineament data extracted from a shaded DEM were used. Collection of the geothermal datasets for China is in progress and limited to heat flow and shallow well-temperature logging data to date.
Three-dimensional modeling of temperature to great depths in Japan, the Gulf of Suez, and China and the detection and integration of geothermal features in Java Island are the main cores for resource-potential evaluation. For the spatial modeling and data integration techniques, machine learning such as deep neural network and clustering, decision tree analysis, geostatistics, neural kriging, maximum entropy, and fuzzy logic are used. As examples of the featured results, promising areas of supercritical geothermal resources and zones with large production power from a relatively shallow depth range were discovered throughout Japan, several unexplored high-potential zones were estimated outside volcanic areas throughout Java Islands, and two high potential zones with high temperature and heat flux due to, probably, large radiogenic heat and permeability and development of fractures were identified in the surrounding Gulf of Suez.
Furthermore, a probabilistic assessment of the power potential for 30 years of utilization was tried for two fields in Japan and Indonesia by a numerical reservoir simulation. These approaches are expected to contribute to increasing power generation by flush and/or binary system and enhanced geothermal system (EGS) and planning the sustainable utilization of geothermal resources.