• Title/Summary/Keyword: 지구물리탐사기법

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A study on the estimation of rock mass classes using the information off a tunnel center line (터널 중심선으로부터 이격된 자료를 활용한 미시추구간의 암반등급 산정에 관한 연구)

  • You, Kwang-Ho;Lee, Sang-Ho;Choo, Suk-Yeon;Jue, Kwang-Sue
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.6 no.2
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    • pp.101-111
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    • 2004
  • In order to guarantee the stability of a tunnel and its optimum design, it is very important to obtain enough ground investigation data. In realty, however, it is not the case due to the limitation of measuring spatially distributed data and economical reasons. Especially, there are regions where drilling is impossible due to civil appeal and mountainous topology, and it is also difficult to estimate rock mass classes quantitatively with only geophysical exploration data. In this study, therefore, 3 dimensional multiple indicator kriging (3D-MI kriging), which can incorporate geophysical exploration data and drill core data off a tunnel center line, is proposed to cope with such problems. To this end, two dimensional mutiple indicator kriging, which is one of the geostatistical techniques, is extended for three dimensional analysis. Also, the proposed 3D-MI kriging was applied to determine the rock mass classes by RMR system for the design of a Kyungbu express rail way tunnel.

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Detection of unexploded ordnance (UXO) using marine magnetic gradiometer data (해양 자력구배 탐사자료를 이용한 UXO 탐지)

  • Salem Ahmed;Hamada Toshio;Asahina Joseph Kiyoshi;Ushijima Keisuke
    • Geophysics and Geophysical Exploration
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    • v.8 no.1
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    • pp.97-103
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    • 2005
  • Recent development of marine magnetic gradient systems, using arrays of sensors, has made it possible to survey large contaminated areas very quickly. However, underwater Unexploded Ordnances (UXO) can be moved by water currents. Because of this mobility, the cleanup process in such situations becomes dynamic rather than static. This implies that detection should occur in near real-time for successful remediation. Therefore, there is a need for a fast interpretation method to rapidly detect signatures of underwater objects in marine magnetic data. In this paper, we present a fast method for location and characterization of underwater UXOs. The approach utilises gradient interpretation techniques (analytic signal and Euler methods) to locate the objects precisely. Then, using an iterative linear least-squares technique, we obtain the magnetization characteristics of the sources. The approach was applied to a theoretical marine magnetic anomaly, with random errors, over a known source. We demonstrate the practical utility of the method using marine magnetic gradient data from Japan.

Improvement of Migration Image for Ocean-bottom Seismic Data using Wavefield Separation and Mirror Imaging (파동장 분리와 미러 이미징을 이용한 해저면 탄성파 탐사 자료의 참반사 보정 영상 개선)

  • Lee, Ganghoon;Pyun, Sukjoon
    • Geophysics and Geophysical Exploration
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    • v.21 no.2
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    • pp.112-124
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    • 2018
  • Ocean-bottom seismic survey is a seismic acquisition technique which measures data by installing 4-component receiver on the sea floor. It can produce more improved data in quality than any other acquisition techniques. In the ocean-bottom seismic survey, however, the number of receivers is limited due to high cost. Since only a small number of receivers are used for acquisition, ocean-bottom seismic data may suffer from discontinuities of events over traces, which can result in spatial aliasing. In this paper, we implemented Kirchhoff migration using mirror-imaging algorithm to improve the quality of ocean-bottom seismic image. In order to implement the mirror imaging algorithm, the seismograms should be separated into up-going and down-going wavefields and the down-going wavefield should be used for migration. In this paper, we use the P-Z summation method to separate the wavefield. Numerical examples show that the migration results using mirror imaging algorithm have wider illumination than the conventional migration, especially in the shallow layers.

Iterative Series Methods in 3-D EM Modeling (급수 전개법에 의한 3차원 전자탐사 모델링)

  • Cho In-Ky;Yong Hwan-Ho;Ahn Hee-Yoon
    • Geophysics and Geophysical Exploration
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    • v.4 no.3
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    • pp.70-79
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    • 2001
  • The integral equation method is a powerful tool for numerical electromagnetic modeling. But the difficulty of this technique is the size of the linear equations, which demands excessive memory and calculation time to invert. This limitation of the integral equation method becomes critical in inverse problem. The conventional Born approximation, where the electric field in the anomalous body is approximated by the background field, is very rapid and easy to compute. However, the technique is inaccurate when the conductivity contrast between the body and the background medium is large. Quasi-linear, quasi-analytical and extended Born approximations are novel approaches to 3-D EM modeling based on the linearization of the integral equations for scattered EM field. These approximation methods are much less time consuming than full integral equation method and more accurate than conventional Born approximation. They we, however, still approximate methods for 3-D EM modeling. Iterative series methods such as modified Born, quasi-linear and quasi-analytical can be used to increase the accuracy of various approximation methods. Comparisons of numerical performance against a full integral equation and various approximation codes show that the iterative series methods are very accurate and almost always converge. Furthermore, they are very fast and easy to implement on a computer. In this study, extended Born series method is developed and it shows more accurate result than that of other series methods. Therefore, Iterative series methods, including extended Born series, open principally new possibilities for fast and accurate 3-D EM modeling and inversion.

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Reverse-time Migration using Surface-related Multiples (자유면 기인 겹반사파를 이용한 거꿀시간 참반사 보정)

  • Lee, Ganghoon;Pyun, Sukjoon
    • Geophysics and Geophysical Exploration
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    • v.21 no.1
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    • pp.41-53
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    • 2018
  • In the traditional seismic processing, multiple reflections are treated as noise and therefore they are eliminated during data processing. Recently, however, many studies have begun to consider multiples as signals rather than noise for seismic imaging. Multiple reflections can illuminate an area where primary reflections are not able to cover, thus it is allowed that a smaller number of shots and receivers are used for imaging large areas. In order to verify this, surface-related multiples were used for reverse-time migration (RTM), and then we compared the results with conventional RTM images which are generated from primary reflections. To utilize multiples, we separated multiples from whole seismic data using surface-related multiple elimination (SRME) method. Numerical examples confirmed that the migration using multiples can image wider area than the conventional migration, particularly in the shallow subsurface layers. In addition, the migration of multiples could eliminate the acquisition footprints.

A Comparative Study of 3D MT Modeling Methods (3차원 MT 모델링 기법의 비교 분석)

  • Han, Nu-Ree;Nam, Myung-Jin;Kim, Hee-Joon;Song, Yoon-Ho;Suh, Jung-Hee
    • Geophysics and Geophysical Exploration
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    • v.10 no.2
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    • pp.154-160
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    • 2007
  • This paper compares the characteristics of three different algorithms for three-dimensional (3D) magnetotelluric (MT) modeling. These methods are developed by Mackie et al. (1994), Sasaki (1999) and Nam et al. (2007). The first and second methods are based on the finite difference method (FDM), while the last one the finite-element method (FEM). MT responses, apparent resistivities and phases, for a COMMEMI 3D-2 model show a good agreement with integral equation solutions and only minor discrepancies are found over the anomalous bodies in the 3D model. The computation time of the two methods based on FDM is short and the static divergence correction contributes to speed up. The FEM modeling scheme is accurate but slow.

Resolution Limits of Cross-Well Seismic Imaging Using Full Waveform Inversion (전파형 역산을 이용한 시추공 영상의 분해능)

  • Cho, Chang-Soo;Lee, Hee-Il;Suh, Jung-Hee
    • Geophysics and Geophysical Exploration
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    • v.5 no.1
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    • pp.33-45
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    • 2002
  • It was necessary to devise new techniques to overcome and enhance the resolution limits of traveltime tomography. Waveform inversion has been one of the methods for giving very high resolution result. High resolution image could be acquired because waveform inversion used not only phase but amplitude. But waveform inversion was much time consuming Job because forward and backward modeling was needed at each iteration step. Velocity-stress method was used for effective modeling. Resolution limits of imaging methods such as travel time inversion, acoustic and elastic waveform inversion were investigated with numerical models. it was investigated that Resolution limit of waveform inversion was similar tn resolution limit of migration derived by Schuster. Horizontal resolution limit could be improved with increased coverage by adding VSP data in cross hole that had insufficient coverage. Also, waveform inversion was applied to realistic models to evaluate applicability and using initial guess of travel time tomograms to reduce non-linearity of waveform inversion showed that the better reconstructed image could be acquired.

A Study on Slowness Time Coherence Application and its Characteristics from Sonic Log Experiment in Model Holes (모형공에서의 음파실험을 통한 STC 기법의 적용과 특성 비교)

  • Kim, Yeong-Hwa;Zhao, Weijun
    • Geophysics and Geophysical Exploration
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    • v.10 no.4
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    • pp.299-307
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    • 2007
  • Slowness time coherence (STC) technique has been applied to 3-receiver slim hole sonic log using 3 NX sized concrete model holes of different physical properties. We analyzed the effects of different source center frequencies on the wave forms, their amplitude spectra, and their STC results. We could determine the sonic velocity of each mode accurately by the application of STC method with the semblance projection and efficient selection of center frequency. Theoretical model and experimental model hole studies indicate that 4-receiver condition is the most ideal for STC in near surface slim hole sonic log. The result also indicates that favorable STC result can be obtained from three-receiver sonic log provided with the help of the first arrival picking method.

Automatic Electrofacies Classification from Well Logs Using Multivariate Statistical Techniques (다변량 통계 기법을 이용한 물리검층 자료로부터의 암석물리학상 결정)

  • Lim Jong-Se;Kim Jungwhan;Kang Joo-Myung
    • Geophysics and Geophysical Exploration
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    • v.1 no.3
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    • pp.170-175
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    • 1998
  • A systematic methodology is developed for the prediction of the lithology using electrofacies classification from wireline log data. Multivariate statistical techniques are adopted to segment well log measurements and group the segments into electrofacies types. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the quality and efficiency of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification works well with reliability to the core and cutting data. This methodology for electrofacies determination can be used to define reservoir characterization which is helpful to the reservoir management.

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A Review of Seismic Full Waveform Inversion Based on Deep Learning (딥러닝 기반 탄성파 전파형 역산 연구 개관)

  • Sukjoon, Pyun;Yunhui, Park
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.227-241
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    • 2022
  • Full waveform inversion (FWI) in the field of seismic data processing is an inversion technique that is used to estimate the velocity model of the subsurface for oil and gas exploration. Recently, deep learning (DL) technology has been increasingly used for seismic data processing, and its combination with FWI has attracted remarkable research efforts. For example, DL-based data processing techniques have been utilized for preprocessing input data for FWI, enabling the direct implementation of FWI through DL technology. DL-based FWI can be divided into the following methods: pure data-based, physics-based neural network, encoder-decoder, reparameterized FWI, and physics-informed neural network. In this review, we describe the theory and characteristics of the methods by systematizing them in the order of advancements. In the early days of DL-based FWI, the DL model predicted the velocity model by preparing a large training data set to adopt faithfully the basic principles of data science and apply a pure data-based prediction model. The current research trend is to supplement the shortcomings of the pure data-based approach using the loss function consisting of seismic data or physical information from the wave equation itself in deep neural networks. Based on these developments, DL-based FWI has evolved to not require a large amount of learning data, alleviating the cycle-skipping problem, which is an intrinsic limitation of FWI, and reducing computation times dramatically. The value of DL-based FWI is expected to increase continually in the processing of seismic data.