• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2003.03a
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• pp.30-37
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• 2003

Lineaments along the Yangsan and Ulsan fault systems were extracted through aerial photograph interpretation in the southeastern part of Korean Peninsula. Lineaments can be classified into five ranks on the basis of certainty and divided by curvatures. Mean strikes of all lineament by aerial photograph interpretation is dominant in NS ~N05$^{\circ}$E direction along the Ulsan fault system and Nl5-20$^{\circ}$E direction along the Yangsan fault system respectively. The curvature of lineament around Yangsan Fault is different from around the Ulsan Fault system, the former shows that straight lineament is dominant but the latter curved lineaments are dominant. It indicates that the Quaternary faults around Ulsan Fault would be appeared as reverse fault.

• Economic and Environmental Geology
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• v.57 no.1
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• pp.73-81
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• 2024

To estimate the tectonic displacement of the Chugaryeong Fault System (CFS), gravity surveys were conducted along the Dongducheon fault (DF) and the Wangsukcheon fault (WF). A total of 1,100 stations for the DF and WF regions have been added to the current gravity database. The results of the gravity interpretation indicate that (1) the dextral displacement of the DF is about 3,000 m, similar to the tectonic displacement (2,900-3,100 m) shown in the geological map. (2) The dextral displacement of the WF is about 3,200 m. (3) Taken together, the tectonic displacement of the CFS is estimated to be about 3,000 m on average. To investigate more accurate tectonic displacement of the CFS, further gravity surveys is planned for the Pocheon fault, Gyeonggang fault, and Inje fault.

• Economic and Environmental Geology
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• v.53 no.4
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• pp.479-489
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• 2020

A fault is a geological structure that can be a migration path or a cap rock of hydrocarbon such as oil and gas, formed from source rock. The fault is one of the main targets of seismic exploration to find reservoirs in which hydrocarbon have accumulated. However, conventional fault detection methods using lateral discontinuity in seismic data such as semblance, coherence, variance, gradient magnitude and fault likelihood, have problem that professional interpreters have to invest lots of time and computational costs. Therefore, many researchers are conducting various studies to save computational costs and time for fault interpretation, and machine learning technologies attracted attention recently. Among various machine learning technologies, many researchers are conducting fault interpretation studies using the support vector machine, multi-layer perceptron, deep neural networks and convolutional neural networks algorithms. Especially, researchers use not only their own convolution networks but also proven networks in image processing to predict fault locations and fault information such as strike and dip. In this paper, by investigating and analyzing these studies, we found that the convolutional neural networks based on the U-Net from image processing is the most effective one for fault detection and interpretation. Further studies can expect better results from fault detection and interpretation using the convolutional neural networks along with transfer learning and data augmentation.

• Economic and Environmental Geology
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• v.54 no.6
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• pp.743-752
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• 2021

The three-dimensional distribution of the fault was evaluated using gravity field interpretation such as curvature analysis and Euler deconvolution in the Seoul-Gyeonggi region where the Chugaryeong fault zone was developed. In addition, earthquakes that occurred after 2000 and the location of faults were compared. In Bouguer anomaly of Chugaryeong faults, the Pocheon Fault is an approximately 100 km fault that is extended from the northern part of Gyeonggi Province to the west coast through the central part of Seoul. Considering the frequency of epicenters is high, there is a possibility of an active fault. The Wangsukcheon Fault is divided into the northeast and southwest parts of Seoul, but it shows that the fault is connected underground in the bouguer anomaly. The magnitude 3.0 earthquake that occurred in Siheung city in 2010 occurred in an anticipated fault (aF) that developed in the north-south direction. In the western region of the Dongducheon Fault (≒5,500 m), the density boundary of the rock mass is deeper than that in the eastern region (≒4,000 m), suggesting that the tectonic movements of the western and eastern regions of the Dongducheon Fault is different. The maximum depth of the fracture zone developed in the Dongducheon Fault is about 6,500 m, and it is the deepest in the research area. It is estimated that the fracture zone extends to a depth of about 6,000 m for the Pocheon Fault, about 5,000 m for the Wangsukcheon Fault, and about 6,000 m for the Gyeonggang Fault.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.864-866
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• 1997

This paper presents fault recognition and interpretation in power transformers using dissolved gas analysis embedded Kohonen feature mapping. The imprecision of gas ratio analysis in dissolved gas analysis are managed by mapping in accordance with learning of Kohonen neural network. To verify the effectiveness of the proposed system, it has been tested by the historical gas records to power transformers of Korea Electric Power Corporation. More appropriate fault types can support the maintenance personnels to increase the disgnostic performance for fault of power transformers.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.196-199
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• 2008

Lineament is defined generally as a linear feature or pattern on interpretation of a satellite image and indicates the geological structures such as faults and fractures. For this reason, a lineament extraction and analysis using remote sensing images have been widely used for mapping large areas. The Gyeong-gang Fault is a NNE trending structure located in Gangwon-do and Kyeonggi-do district. However, a few geological researches on that fault have been carried out and its trace or continuity is ambiguous. In this study, we investigate the geologic features at Gyeong-gang Fault Zone using LANDSAT ETM+ satellite image and SRTM digital elevation model. In order to extract the characteristics of geologic features effectively, we transform the LANDSAT ETM+ image using Principal Component Analysis (PCA) and create a shade relief from SRTM data with various illumination angles. The results show that it is possible to identify the dimensions and orientations of the geologic features at Gyeong-gang Fault Zone using remote sensing data. An aerial photograph interpretation and a field work will be future tasks for more accurate analysis in this area.

• Transactions on Electrical and Electronic Materials
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• v.13 no.5
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• pp.229-232
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• 2012

DGA is one of the most recent techniques developed to diagnose the fault condition on oil filled insulation transformers. There are more than 6 known different methods of DGA fault interpretation technique and so there is the likelihood that they may vary in their interpretations. A series of combined interpretation methods that can determine the power transformer condition faults in one assessment is therefore needed. This paper presents a computer program- based system developed to combine four DGA assessment techniques; Rogers Ratio Method, IEC Basic Ratio Method, Duval Triangle method and Key Gas Method. An easy to use Graphic User Interface was designed to give a visual display of the four techniques. The result shows that this assessment method can increase the accuracy of DGA methods by up to 20% and the no prediction result had been reduced down to 0%.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.91-103
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• 2021

In order to estimate the vertical and horizontal structural in the Yangsan fault core line (Naengsuri area, Pohang), we carried out gravity field measurements and interpretation procedures such as Euler deconvolution method and curvature analysis in addition to the forward modelling technique (i.e. IGMAS+). We found a prominent gravity difference of more than 1.5 mGal across the fault core. This indicates a distinct density difference between the western and eastern crustal area across the Yangsan fault line. Comparing this gravity field interpretation with other existent geologic and geophysical survey data (e.g. LiDAR, trenching, electric resistivity measurements), It is concluded that (1) the prominent gravity difference is caused by the density difference of about 0.1 g/㎤ between the Bulguksa Granite in the west and the Cretaceous Sandstone in the east side, (2) the fault core is elongated vertically into a depth of about 2,000 meters and extended horizontally 3,000 meters to the NNE direction from Naengsuri area. Our results present that the gravity field method is a very effective tool to estimate a three -dimensional image of the active fault core.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.78-85
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• 2006

The Ulsan Fault System continues from north of Gyeongju to Ulsan city, trending NNW-SSE and is about 50 km. Many Quaternary faults have been reported and investigated with outcrop observation. Lineaments have been extracted with aerial photograph interpretation and classified by their ranks. Trench excavations on the lineaments along Ulsan Fault System have been carried out to clarify the neotectonic movements and fault parameters such as the latest movement age, fault displacement, slip rate and recurrence interval. We have compiled data from previous studies on criteria of segment type such as lineament rank, seismicity, slip rate, and the latest fault movement. Based on these data, we tried to devide the Ulsan Fault System into several segments. The results of segmentation with each types of segment along the Ulsan Fault System did not show singular division point but overlapped or different length and location.

• Geophysics and Geophysical Exploration
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• v.23 no.2
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• pp.97-114
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• 2020

Recently, many studies have been actively conducted on the application of machine learning in all branches of science and engineering. Studies applying machine learning are also rapidly increasing in all sectors of seismic exploration, including interpretation, processing, and acquisition. Among them, fault detection is a critical technology in seismic interpretation and also the most suitable area for applying machine learning. In this study, we introduced various machine learning techniques, described techniques suitable for fault detection, and discussed the reasons for their suitability. We collected papers published in renowned international journals and abstracts presented at international conferences, summarized the current status of the research by year and field, and intensively analyzed studies on fault detection using machine learning. Based on the type of input data and machine learning model, fault detection techniques were divided into seismic attribute-, image-, and raw data-based technologies; their pros and cons were also discussed.