The importance of the development and utilization of deep underground spaces is increasingly recognized, as promoted by advances in geothermal energy, geological nuclear waste disposal, underground energy storage and even underground research laboratories. The deep underground environment is characterized by extreme conditions, including high stress and high water pressure levels and high temperatures with limited accessibility, all of which cause many uncertainties in estimations and assessments of rock mass behaviors at deep depths. Thus, we have focused on the development of InDEPTH technology for the characterization of deep subsurfaces based on boreholes (1-5 km, high temperature and high stress conditions).
We established and improved a new winch system capable of operating at depths as low as 5 km as well as a data acquisition system and a PTS (pressure, temperature and spinner) and borehole image logging system for high-pressure and high-temperature (HPHT) environments. The winch system was successfully tested up to a depth of 4 km at the Pohang borehole (Fig. 1). We have also improved the performance of the equipment for measuring 3D in-situ rock stress levels and undertook related laboratory verification measures (Fig. 2). Subsequently, we developed and verified the analysis technology of coupled T-H-M simulations for the characterization of deep subsurfaces (Fig. 3).
Another main research topic is the establishment of a deep borehole monitoring network via the installation of an integrated geophysical monitoring system at a depth of 1 km to assess earthquake and fault activities in southeastern Korea. The designed system is composed of a borehole seismometer, a FBG strain gage, a distributed temperature sensor, a PT sensor in the boreholes and a broadband seismometer and GNSS station on the ground surface (Figs. 4 & 5). We have also determined ten candidate sites suitable for the installation of the integrated geophysical monitoring system through a weight analysis of five factors with ten parameters related to monitoring performance (Fig. 6).
