• Title/Summary/Keyword: Korean Geophysical Society

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Application of Depth Resolution and Sensitivity Distribution of Electrical Resistivity Tomography to Modeling Weathered Zones and Land Creeping (전기비저항 깊이분해능 및 감도분포: 풍화층 및 땅밀림 모델에 대한 적용)

  • Kim, Jeong-In;Kim, Ji-Soo;Ahn, Young-Don;Kim, Won-Ki
    • The Journal of Engineering Geology
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    • v.32 no.1
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    • pp.157-171
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    • 2022
  • Electrical resistivity tomography (ERT) is a traditional and representative geophysical method for determining the resistivity distributions of surrounding soil and rock volumes. Depth resolution profiles and sensitivity distribution sections of the resistivities with respect to various electrode configurations are calculated and investigated using numerical model data. Shallow vertical resolution decreases in the order of Wenner, Schlumberger, and dipole-dipole arrays. A high investigable depth in homogeneous medium is calculated to be 0.11-0.19 times the active electrode spacing, but is counterbalanced by a low vertical resolution. For the application of ERT depth resolution profiles and sensitivity distributions, we provide subsurface structure models for two types of land-creping failure (planar and curved), subvertical fracture, and weathered layer over felsic and mafic igneous rocks. The dipole-dipole configuration appears to be most effective for mapping land-creeping failure planes (especially for curved planes), whereas the Wenner array gives the best resolution of soil horizons and shallow structures in the weathered zone.

Spatio-Temporal Variability Analysis of Precipitation Data Through Circular Statistics (순환통계 분석을 통한 강수량 시계열의 시공간적 변동성 분석)

  • Kwon, Hyun-Han;Lee, Jeong-Ju
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.2B
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    • pp.191-198
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    • 2010
  • Assessing seasonality of precipitation is necessarily required to establish future plans and policies for water resources management. In this regard, a main objective of the study is to introduce an effective approach for assessing the seasonality of the precipitation and evaluate the seasonality through the proposed one. We have used circular statistics to characterize the seasonality on the precipitation in Korea. The circular statistics allow us to effectively assess changes in timing of the seasonality in detail. It was found that peak time on monthly rainfall occurred between end of June and early July in southern coastal area while the timing was delayed in northern part of Korea because of monsoon moving in from south to north. In case of annual daily peak precipitation, spatio-temporal variation of the peak time was increased. It is mainly because of geophysical effects, frequency and paths of typhoons. Finally, temporal variations on the timing of the peak seasons were evaluated through circular statistics by 30-year moving average data. The peak season in the Northen part of Korea (e.g. Seoul and Gangrung) has been moved back from early July to end of July while the peak season has been moved up from middle of July to early July in the Southern part of Korea (e.g. Busan and Mokpo). It seems that changes in seasonality are mostly modulated by variability in the east-asia monsoon system.

Improvement of Underground Cavity and Structure Detection Performance Through Machine Learning-based Diffraction Separation of GPR Data (기계학습 기반 회절파 분리 적용을 통한 GPR 탐사 자료의 도로 하부 공동 및 구조물 탐지 성능 향상)

  • Sooyoon Kim;Joongmoo Byun
    • Geophysics and Geophysical Exploration
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    • v.26 no.4
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    • pp.171-184
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    • 2023
  • Machine learning (ML)-based cavity detection using a large amount of survey data obtained from vehicle-mounted ground penetrating radar (GPR) has been actively studied to identify underground cavities. However, only simple image processing techniques have been used for preprocessing the ML input, and many conventional seismic and GPR data processing techniques, which have been used for decades, have not been fully exploited. In this study, based on the idea that a cavity can be identified using diffraction, we applied ML-based diffraction separation to GPR data to increase the accuracy of cavity detection using the YOLO v5 model. The original ML-based seismic diffraction separation technique was modified, and the separated diffraction image was used as the input to train the cavity detection model. The performance of the proposed method was verified using public GPR data released by the Seoul Metropolitan Government. Underground cavities and objects were more accurately detected using separated diffraction images. In the future, the proposed method can be useful in various fields in which GPR surveys are used.

A Study on Generating Virtual Shot-Gathers from Traffic Noise Data (교통차량진동 자료에 대한 최적 가상공통송신원모음 제작 연구)

  • Woohyun Son;Yunsuk Choi;Seonghyung Jang;Donghoon Lee;Snons Cheong;Yonghwan Joo;Byoung-yeop Kim
    • Geophysics and Geophysical Exploration
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    • v.26 no.4
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    • pp.229-237
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    • 2023
  • The use of artificial sources such as explosives and mechanical vibrations for seismic exploration in urban areas poses challenges, as the vibrations and noise generated can lead to complaints. As an alternative to artificial sources, the surface waves generated by traffic noise can be used to investigate the subsurface properties of urban areas. However, traffic noise takes the form of plane waves moving continuously at a constant speed. To apply existing surface wave processing/inversion techniques to traffic noise, the recorded data need to be transformed into a virtual shot gather format using seismic interferometry. In this study, various seismic interferometry methods were applied to traffic noise data, and the optimal method was derived by comparing the results in the Radon and F-K domains. Additionally, the data acquired using various receiver arrays were processed using seismic interferometry, and the results were compared and analyzed to determine the most optimal receiver array direction for exploration.

Development of a CPInterface (COMSOL-PyLith Interface) for Finite Source Inversion using the Physics-based Green's Function Matrix (물리 기반 유한 단층 미끌림 역산을 위한 CPInterface (COMSOL-PyLith Interface) 개발)

  • Minsu Kim;Byung-Dal So
    • Geophysics and Geophysical Exploration
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    • v.26 no.4
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    • pp.268-274
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    • 2023
  • Finite source inversion is performed with a Green's function matrix and geodetic coseismic displacement. Conventionally, the Green's function matrix is constructed using the Okada model (Okada, 1985). However, for more realistic earthquake simulations, recent research has widely adopted the physics-based model, which can consider various material properties such as elasticity, viscoelasticity, and elastoplasticity. We used the physics-based software PyLith, which is suitable for earthquake modeling. However, the PyLith does not provide a mesh generator, which makes it difficult to perform finite source inversions that require numerous subfaults and observation points within the model. Therefore, in this study, we developed CPInterface (COMSOL-PyLith Interface) to improve the convenience of finite source inversion by combining the processes of creating a numerical model including sub-faults and observation points, simulating earthquake modeling, and constructing a Green's function matrix. CPInterface combines the grid generator of COMSOL with PyLith to generate the Green's function matrix automatically. CPInterface controls model and fault information with simple parameters. In addition, elastic subsurface anomalies and GPS observations can be placed flexibly in the model. CPInterface is expected to enhance the accessibility of physics-based finite source inversions by automatically generating the Green's function matrix.

A Review of Deep Learning-based Trace Interpolation and Extrapolation Techniques for Reconstructing Missing Near Offset Data (가까운 벌림 빠짐 해결을 위한 딥러닝 기반의 트레이스 내삽 및 외삽 기술에 대한 고찰)

  • Jiho Park;Soon Jee Seol;Joongmoo Byun
    • Geophysics and Geophysical Exploration
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    • v.26 no.4
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    • pp.185-198
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    • 2023
  • In marine seismic surveys, the inevitable occurrence of trace gaps in the near offset resulting from geometrical differences between sources and receivers adversely affects subsequent seismic data processing and imaging. The absence of data in the near-offset region hinders accurate seismic imaging. Therefore, reconstructing the missing near-offset information is crucial for mitigating the influence of seismic multiples, particularly in the case of offshore surveys where the impact of multiple reflections is relatively more pronounced. Conventionally, various interpolation methods based on the Radon transform have been proposed to address the issue of the nearoffset data gap. However, these methods have several limitations, leading to the recent emergence of deep-learning (DL)-based approaches as alternatives. In this study, we conducted an in-depth analysis of two representative DL-based studies to scrutinize the challenges that future studies on near-offset interpolation must address. Furthermore, through field data experiments, we precisely analyze the limitations encountered when applying previous DL-based trace interpolation techniques to near-offset situations. Consequently, we suggest that near-offset data gaps must be approached by extrapolation rather than interpolation.

Case Studies of Site Investigation Factors and Methods for Site Selection for High-Level Radioactive Waste Disposal (고준위방사성폐기물 처분 부지선정을 위한 조사인자 및 조사기법에 대한 국외사례 분석)

  • Hyo Geon Kim;Si Won Yoo;Dae Seok Bae;Soo Hwan Jung;Ki Su Kim;Jun Kyum Kim;Man Ho Han;Junghae Choi
    • The Journal of Engineering Geology
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    • v.33 no.4
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    • pp.611-626
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    • 2023
  • Overseas examples of the characterization stage of site selection proposed by the International Atomic Energy Agency were reviewed to highlight the factors necessary for consideration in the deep disposal of high-level radioactive waste. Studies in Sweden, Finland, the USA, and Canada were considered. Site investigations in Sweden and Finland commonly covered the fields of geology, hydrogeology, and hydrogeochemistry using similar field investigation techniques. The USA considered survey groups and factors under pre- and post-lockdown guidelines, as well as those for desaturated and saturated surveys. involving geophysical, hydrological, hydrogeological, hydrogeochemical, mechanical/physical, and thermal-characterization investigations. Canada provided a list of investigative methods for both preliminary and detailed site assessments including geological, physical, boring, hydrological, laboratory testing, and chemical analysis studies. Results of this study should elucidate site-selection investigation factors and survey methods applicable to Korea.

Study on the Seismic Random Noise Attenuation for the Seismic Attribute Analysis (탄성파 속성 분석을 위한 탄성파 자료 무작위 잡음 제거 연구)

  • Jongpil Won;Jungkyun Shin;Jiho Ha;Hyunggu Jun
    • Economic and Environmental Geology
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    • v.57 no.1
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    • pp.51-71
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    • 2024
  • Seismic exploration is one of the widely used geophysical exploration methods with various applications such as resource development, geotechnical investigation, and subsurface monitoring. It is essential for interpreting the geological characteristics of subsurface by providing accurate images of stratum structures. Typically, geological features are interpreted by visually analyzing seismic sections. However, recently, quantitative analysis of seismic data has been extensively researched to accurately extract and interpret target geological features. Seismic attribute analysis can provide quantitative information for geological interpretation based on seismic data. Therefore, it is widely used in various fields, including the analysis of oil and gas reservoirs, investigation of fault and fracture, and assessment of shallow gas distributions. However, seismic attribute analysis is sensitive to noise within the seismic data, thus additional noise attenuation is required to enhance the accuracy of the seismic attribute analysis. In this study, four kinds of seismic noise attenuation methods are applied and compared to mitigate random noise of poststack seismic data and enhance the attribute analysis results. FX deconvolution, DSMF, Noise2Noise, and DnCNN are applied to the Youngil Bay high-resolution seismic data to remove seismic random noise. Energy, sweetness, and similarity attributes are calculated from noise-removed seismic data. Subsequently, the characteristics of each noise attenuation method, noise removal results, and seismic attribute analysis results are qualitatively and quantitatively analyzed. Based on the advantages and disadvantages of each noise attenuation method and the characteristics of each seismic attribute analysis, we propose a suitable noise attenuation method to improve the result of seismic attribute analysis.

Analysis on Seismic Interpretation for Overseas Large-scale CO2 Storage Considering Geological History Related to Plate Tectonics (판구조론적 역사를 고려한 해외 대규모 이산화탄소 지중저장소 탄성파 해석 결과 분석)

  • Young-Ju Lee;Ha-Yeon Kang;Yun-Gon Park;Ah-Reum Han;Jae-Young Lee;Ju-Won Oh
    • Geophysics and Geophysical Exploration
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    • v.27 no.1
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    • pp.1-22
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    • 2024
  • Carbon dioxide capture utilization and storage (CCUS) techniques have received significant global attention as they are part of efforts to achieve carbon neutrality by 2050. Large-scale carbon dioxide capture and storage (CCS) projects are being actively pursued in North America, the North Sea, the Middle East, and Oceania. Considering the current situation in South Korea, identifying large-scale CCS sites that can secure an annual domestic carbon storage capacity of 30 million tons by 2050 is crucial Therefore, this study analyzed the formation process and geological characteristics of overseas large-scale CCS projects in terms of plate tectonics. We utilized the GPlates program to interpret the formation processes of large-scale CCS projects in North America, the North Sea, Middle East, and Oceania from the perspective of plate tectonics. Additionally, we investigated the geological structure of the CO2 storage layer and interpreted seismic imaging results obtained from each CCS site. This study will help identify a domestic large-scale CCS site.

MT Response of a Small Island Model with Deep Sea and Topography (깊은 바다와 지형을 고려한 소규모 섬 모델의 MT 반응 연구)

  • Kiyeon Kim;Seong Kon Lee;Seokhoon Oh;Chang Woo Kwon
    • Geophysics and Geophysical Exploration
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    • v.27 no.1
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    • pp.37-50
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    • 2024
  • The magnetotelluric (MT) survey can be affected by external environmental factors. In particular, when acquiring MT data in islands, it is essential to consider the combined effect of topography and sea to understand the results and make accurate interpretations. To analyze the MT response (apparent resistivity, phase) with consideration of the effect of topography and sea, a small cone-shaped island model surrounded by deep sea was created. Two-dimensional (2-D) and three-dimensional (3-D) forward modeling were performed on the terrain model considering topography and the island model considering both topography and sea. The 2-D MT response did not reflect the topographic and sea effect of the direction orthogonal to the 2-D profile. The 3-D MT response included topographic and sea effects in all directions. The XY and YX components of the apparent resistivity were separated on undulating topography, such as a hill. A conductor at 1 km below sea level could be distinguished from topographic and sea effects in the MT response, and low resistivity anomaly was attenuated at greater depths. This study will facilitate understanding of field data measured on small islands.