IDENTIFYING THE GEOTHERMAL POTENTIAL ZONES BASED ON THE PROBABILITY MODELING OF RADON GAS CONCENTRATION, LINEAMENT DENSITIES, GEOCHEMICAL DATA, AND ALTERATION INTENSITY

• Main Author: Azizah Oetomo, Maisyita
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/58442
• Institution: Institut Teknologi Bandung

The issue of global warming must be immediately responded by reducing the carbon emissions. However, the main energy needs in Indonesia are still met using fossil fuels which produce quite large carbon emissions. The solution to this problem is to use clean alternative energy such as geothermal. One area that shows geothermal potential is Wayang Windu Field at West Java. This study aims to identify the geothermal potential zones based on the distribution of the permeability zones from the probability models of radon gas concentration, lineament densities, geochemical data of springs, and alteration intensity. Determining the presence of permeable zones can be obtained from the lineament structures extracted from DEMNAS. The method used for lineament extraction is mSTA (modified Segment Tracing Algorithm). The determination of permeable zone can also be obtained from the distribution of radon gas concentration, which is a trace element that is sensitive to the measurement of displacement time in geothermal reservoirs. Alteration intensity data that showing hydrothermally altered minerals are also used as a parameter for potency zone modeling. The use of geochemical data of trace elements of alkali metals (Li, Rb, Cs, Cl, and B) is also important in the identification of permeable zones as indicators of high temperature due to hydrothermal fluids. The method used to produce probability maps is Sequential Gaussian Simulation (SGS). The method generates 100 realizations for each data, and from those, the upper quartile (Q3) is used for the threshold to calculate probability, except for pH data uses lower quartile (Q1) as the threshold. Then on the probability data, a fuzzy logic "OR" function is generated which produces a map of the permeable zone distribution with indexes 1 and 0. Index 1 shows that one of the overall probability data is outside its threshold and assuming it shows a permeable zone, while index 0 indicates that from the overall probability data, none of them is outside the threshold. As validation, the potential map of permeable zone is overlaid with the location of production wells and geothermal manifestation, where about 78% of them are in the potency zone with index 1.