• Geophysics and Geophysical Exploration
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• v.19 no.4
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• pp.187-199
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• 2016

In order to delineate the soft ground distribution, an integrated geostatistical analysis was performed using the MASW (Multichannel Analysis of Surface Wave) which has the information of overall region and CPTu (Piezo Cone Penetration Test) which provides the direct information of the measuring point of the ground. MASW results were known to have close relationship with the ground stiffness. This correlation was confirmed through the comparison of MASW data obtained from two survey lines to the laboratory test with extracted soil samples. 3D physical property distribution in the study area was acquired by geostatistical integrated analysis with the data of tip resistance ($q_c$) and pore pressure (u) from the CPTu obtained at 6 points within the study area. The integrated analysis was conducted by applying the COSGSIM (Sequential Gaussian Co-Simulation) technology which can carry out the simulation in accordance with the spatial correlation between the MASW results and both tip resistance and pore pressure. Besides the locations of CPTu, borehole investigations were also conducted at two different positions. As a result, the N value of SPT and borehole log could be secured, so these data were used for the analysis of the geotechnical engineering accuracy of the integrated analysis result. For the verification of reliability of the 3D distribution of tip resistance and pore pressure secured through integrated analysis, the geotechnical information gained from the two drilling areas was compared, and the result showed extremely high correlation.

• Tunnel and Underground Space
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• v.31 no.4
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• pp.243-269
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• 2021

Since the early 2010s, the social importance of research and practical projects targeting deep geological disposal of high-level nuclear waste, underground CO₂ storage and characterization of deep subsurface by borehole investigation has been increasing. In this regard, there is also a significant increase in the need for in situ test technology to obtain quantitative and reliable information on the hydraulic characteristics of deep rock mass. Through years of research and development, we have independently set up Deep borehole Hydraulic Test System (DHTS) based on the key apparatuses designed and made with our own technology. Using this system, high precision constant pressure injection tests were successfully completed at the two 1 km boreholes located in Mesozoic granite and sedimentary rock regions, Gyeongju. During the field tests, it was possible to measure very low flow rate below 0.01 l/min with micro flow rate injection/control module. In this paper, the major characteristics of DHTS are introduced and also some results obtained from the high precision field tests under the deep and low permeable rock mass environment are briefly discussed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.1
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• pp.135-144
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• 2020

Since the depth of tunneling with tunnel boring machine (TBM) becomes deeper and deeper, the expense for site investigation for coring and geophysical survey increases to obtain the sufficient accuracy. The tunnel ahead prediction methods have been introduced to overcome this limitation in the stage of site investigation. Probe drilling can obtain the core and borehole images from a borehole. However, the space in TBM for the probe drilling equipment is restricted and the core from probe drilling cannot reflect the whole tunnel face. Seismic methods such as tunnel seismic prediction (TSP) can forecast over 100 m ahead from the tunnel face though the signal is usually generated using the explosive which can affect the stability of segments and backfill grout. Electromagnetic methods such as tunnel electrical resistivity prospecting system (TEPS) offer the exact prediction for a conductive zone such as water-bearing zone. However, the number of electrodes installed for exploration is limited in small diameter TBM and finally the reduction of prediction ranges. In this study, the theoretical equations for the electrical resistivity survey whose electrodes are installed in the face and side of TBM to minimize the installed electrodes on face. The experimental tests were conducted to verify the derived equations.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.5
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• pp.139-150
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• 2007

As computer technology has been rapidly advanced, geographic information system (GIS) is recently used in many disciplines. In this study, for a model area in Seoul, seismic hazard potential relating to site effects, which are influenced by the subsurface geotechnical conditions, was estimated using the GIS tool. The distribution of pre-existing borehole drilling data in Seoul metropolitan area was examined for the regional estimation of site-specific seismic responses at the model area. Spatial geo-layers across the entire model area were predicted by constructing a GIS-based geotechnical information system (GTIS). A microzonation of site period $(T_G)$ for estimating site-specific seismic responses at the model area was performed within the GTIS. The spatial microzoning map of $T_G$ indicated seismic vulnerability of two- to four-storied buildings in the model area. Furthermore, a site classification map for determining the design ground motion was established based on the $T_G$ within the GTIS. This informed that most of location in the model area was categorized into current site classes C and D. This seismic microzonation framework for the model area could be applicable particularly in the entire Seoul metropolitan area based on the pre-existing borehole data.

• Geophysics and Geophysical Exploration
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• v.2 no.2
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• pp.86-95
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• 1999

This paper presents an efficient three-dimensional (3-D) modeling algorithm using the extended approximation to an electric field integral equation. Numerical evaluations of Green's tensor integral are performed in the spatial wavenumber domain. This approach makes it possible to reduce computing time, to handle smoothly varying conductivity model and to remove singularity problems encountered in the integration of Green's tensor at a source point. The responses obtained by 3-D modeling algorithm developed in this study are compared with those by the full integral equation for a thin-sheet EM scattering. The extensive analyses on the performance of modeling algorithm are made with the conductivity contrasts and source frequencies. These results show that the modeling algorithm are accurate up to the conductivity contrast of 1:16 and the frequency range of 100 Hz-100 kHz. The extended Born approximation, however, may produce inaccurate results for some source and model configurations in which the electric field is discontinuous across the conductivity boundary. We performed the modeling of a composite model of which conductivity varies continuously and this shows the modeling algorithm developed in this study is efficient for 3-D EM modeling. For a cross-hole source-receiver configuration a composite model of which conductivity varies continuously can be successfully simulated using this algorithm.

• Geophysics and Geophysical Exploration
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• v.7 no.2
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• pp.109-116
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• 2004

Petroleum reservoir characterization is a process for quantitatively describing various reservoir properties in spatial variability using all the available field data. Porosity and permeability are the two fundamental reservoir properties which relate to the amount of fluid contained in a reservoir and its ability to flow. These properties have a significant impact on petroleum fields operations and reservoir management. In un-cored intervals and well of heterogeneous formation, porosity and permeability estimation from conventional well logs has a difficult and complex problem to solve by conventional statistical methods. This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best related well logs with core porosity and permeability data. Neural network is used as a nonlinear regression method to develop transformation between the selected well logs and core analysis data. The intelligent technique is demonstrated with an application to the well data in offshore Korea. The results show that this technique can make more accurate and reliable properties estimation compared with previously used methods. The intelligent technique can be utilized a powerful tool for reservoir characterization from well logs in oil and natural gas development projects.

• Journal of Korean Tunnelling and Underground Space Association
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• v.14 no.5
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• pp.503-516
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• 2012

Rock mass rating (RMR) is the key factor when designing the appropriate support pattern of tunnel projects. Borehole drilling is usually performed along the tunnel route in order to determine the rock mass rating to be used for tunnel design. The rock mass rating at the non-boring region between boreholes is usually assessed through geophysical surveys such as electrical prospecting, seismic prospecting, etc. Many studies were carried out to find out the correlation between electrical resistivity and rock mass rating. However, most researches were aimed at obtaining the relationship between the two parameters utilizing experimental results obtained from laboratory tests or electrical prospectings. In this paper, efforts were made to analyze and obtain relationships between the electrical resistivity obtained from in-situ electrical resistivity logging data and the rock mass rating. Correlation studies using field data showed that the electrical resistivity is highly correlated with the rock mass rating with the determination coefficient more than 90%. The correlation analysis was also carried out between RMR classification parameters and the electrical resistivity. It was shown that the correlation between the condition of discontinuities and the electrical resistivity was very high with the determination coefficient more than 80%; that between the groundwater condition and the electrical resistivity was very low with the determination coefficient less than 57%.

• Geophysics and Geophysical Exploration
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• v.15 no.1
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• pp.1-7
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• 2012

To evaluate methods of determining near-surface shear-wave velocities (${\nu}_s$), we derived dispersion curves of Rayleigh waves generated by both passive and active sources in Chuncheon, Korea. Microtremors were recorded for 5 minutes in each of four triangular arrays with radii of 5 ~ 40 m. Those data were analyzed using the Spatial Autocorrelation method. Rayleigh waves were also generated by a hammer source and recorded in the same area for 2 s using 24 4.5-Hz geophones. Multichannel Analysis of Surface Waves was applied to those data. Velocity spectra were derived with relatively high signal-to-noise ratios in the frequency ranges of 7 ~ 19 and 11 ~ 50 Hz for the microtremors and synthetically generated Rayleigh waves, respectively. The resultant dispersion curves were combined as one and then input to inversion to derive shear wave velocities that were compared with a lithology log from a nearby well. Shearwave velocities in the top soil and soft-rock layers are almost constant with values of 221 and 846 m/s, respectively; while the inverse-modeled ${\nu}_s$ increases linearly in the gravelly sand, cobbles, and weathered-rock layers. If rock type is classified based on shear-wave velocity, the inversion-derived boundary between weathered-rock and soft rock may be about 5 m deeper than in the well log.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.13-24
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• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.4
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• pp.17-35
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• 2016

Earthquake-induced disasters are often more severe in locations with soft soils than firm soils or rocks due to differences in ground motion amplification. On a regional scale, such differences can be estimated by spatially predicting subsurface soil thickness over the entire target area. In general, soil deposits are generally deeper in coastal or riverside areas than in inland regions. In this study, a coastal metropolitan area, Incheon, was selected to assess site effects and provide information on seismic hazards. Spatial prediction of geotechnical layers was performed for the entire study area within the GIS framework. Approximately 7,000 existing borehole drilling data in the Incheon area were gathered and archived into the GIS Database (DB). In addition, surface geotechnical data were acquired from a walkover survey. Based on the built geotechnical DB, spatial zoning maps of site-specific seismic response parameters were created and presented for use in a regional seismic strategy. Site response parameters were performed to determine site coefficients for seismic design over the entire target area and compared with each other. Site classifications and subsequent seismic zoning were assigned based on site coefficients. From this seismic zonation case study in Incheon, we verified that geotechnical GIS-DB can create spatial zoning maps of site-specific seismic response parameters that are useful for seismic hazard mitigation particularly in coastal metropolitan areas.