Abstract

The limited nature of subsurface imaging data in geothermal field makes surface data important to infer subsurface geologic conditions. One of the main geologic features that can be extracted from surface data is lineament which can be attributed to rock fractures, including joints and deep-seated faults. Fractures play a dominant role in the creation of porosity and permeability that allows the storage and flow of thermal fluid in geothermal reservoirs. Therefore, it is important to characterize rock fractures and model the flow of thermal fluid through them to better understand the geothermal reservoir. This study evaluates the application of lineaments extracted from dual-orbit Synthetic Aperture Radar (SAR) images acquired by the Phased-L Synthetic Aperture Radar (PALSAR) sensor on the Advanced Land Observing Satellite (ALOS) as input for fracture modeling to reservoir simulation in geothermal field. The SAR images were acquired from the Geureudong area in Aceh. Lineaments were extracted automatically from SAR images using modified Segment Tracing Algorithm (mSTA). Noise filtering and edge enhancement algorithms were applied to the SAR images prior to mSTA to optimize the extraction of geologically significant lineaments. The extracted lineaments were spatially analyzed, including lineament frequency density, lineament length density, lineament intersection density, and lineament direction rose diagram. Representative fracture model with a vertical dip angle was created from the extracted lineaments and was assigned with reservoir properties, including permeability and porosity. Thermal fluid flow was simulated through it to detect flow path and to characterize fluid flow in a geothermal system. Spatial analysis of the extracted lineaments showed a good correlation with the trend of geological structures observed in the field. The simulated fluid flow path showed good agreement with the spatial distribution of geothermal manifestations. Simulation results showed a strong correlation between fluid flow characteristics to the orientation, density, and connectivity of the fracture model.

Full Text
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