• Title/Summary/Keyword: 역산기법

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Resistivity Inversion of Underground Cavity Model Using a Multi-Resolution Wavelet (다중분해능 웨이브렛에 의한 지하공동모형의 전기비저항 역산)

  • Suh Baek-Soo;Lee Jae-Young;Kim Yong-In;Lee Chang-Hwan
    • Geophysics and Geophysical Exploration
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    • v.5 no.2
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    • pp.78-83
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    • 2002
  • The finite element method combined with the sensitivity method is adopted for 2-dimensionl Fourier transform inversion. To improve the efficiency of inversion calculation, multi-resolution wavelet method is proposed., Theoretical data which is obtained from above method is shown to examine the proposed method. Theoretical model assumes that underground cavity is located in limestone area. In theoretical model, 16 current and potential electrodes are located to get theoretical data. It is shown that the about inversion method is very exact and useful calculation method, in case the larger model is very small such as under ground cavity.

지하 파일 탐지를 위한 시추공 자력탐사 자료의 역산

  • 차영호;신창수;서정희
    • Proceedings of the KSEEG Conference
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    • 1999.04a
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    • pp.80-85
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    • 1999
  • 본 연구에서는 토목분야에서 중요한 문제가 되는 기초 파일의 깊이 탐지와 관련하여 시추공 자력탐사의 적용성을 확인하기 위하여 시추공 자력탐사 모형 반응 계산 및 역산 알고리즘을 개발하였다. 모형 반응 계산은 시추공 자력탐사에 적합하고 삼성분 이상을 계산할 수 있도록 기존의 방법을 수정하였으며, 역산 알고리즘은 일반적인 자력탐사 자료 역산의 불안정성을 고려하여 광역적 최적화 기법의 하나임 ASA(Adaptive Simulated Annealing : Ingber, 1993)를 이용하였다. 개발된 모형 반응 및 역산 알고리즘을 간단한 모형 및 합성자료에 대해 적용한 결과 그 타당성을 검증할 수 있었다. 또한 실제 현장에서 부딪힐 수 있는 무작위 잡음을 첨가한 자료, 주변 파일의 영향 및 지표 구조물에 의한 영향을 고려한 복잡한 모형에 대해 기초 파일의 깊이를 탐지해 낼 수 있었으며, 이를 토대로 실제 현장 적용시 고려해야할 현장지침에 대해서도 고찰할 수 있었다. 마지막으로 실제 현장자료에 적용한 결과 실제 파일의 깊이를 역산해 낼 수 있음을 확인함으로써, 기초 파일의 깊이 탐지를 위한 시추공 자력탐사의 적용성 및 본 알고리즘의 현장 적용성을 확인할 수 있었다.

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Application of Inversion Methods to Evaluate the State of Soft Soil using Electrical Resistivity Monitoring Data (전기비저항 모니터링 자료를 이용한 연약지반 평가를 위한 역산기법 적용 연구)

  • Ji, Yoonsoo;Oh, Seokhoon;Im, Eunsang
    • Geophysics and Geophysical Exploration
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    • v.17 no.2
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    • pp.104-113
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    • 2014
  • Electric resistivity monitoring was applied to evaluate the soft ground in reclaimed land in order to figure out the applicability of physical prospecting. For this, electrical resistivity monitoring data were acquired for total three months and analyzed those data with independent inversion, time-lapse inversion, and 4D inversion methods. The result was compared for various inversion methods so as to figure out what showed the soft soil most properly. Moreover, drilling and CPT(Cone Penetration Test) data were also used in order to find out if each of those inversion methods could distinguish either bed rock or the soft soil clearly. And according to the result, time-lapse inversion showed less inversion artifacts than independent inversion, so it could indicate the soft soil better. If data gained for a longer period than three months are used, 4D inversion has been found to be a more efficient analysis method than the time-lapse inversion method. Electrical resistivity monitoring on the soft soil has been found to be a useful method that can analyze the spatio-temporal electric state of the ground serially.

Inversion of spectral analysis of surface waves with analytic Jacobian (해석적 자코비안을 이용한 표면파 기법의 역산)

  • Ha, Hee-Sang
    • Journal of the Korean Geophysical Society
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    • v.5 no.3
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    • pp.233-245
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    • 2002
  • The spectral-analysis-of-surface-waves (SASW) method is a nondestructive testing method based upon generation and detection of elastic stress waves. SASW is widely used as one of the techniques to determine stiffness profile in engineering geophysics. The essential steps involved are construction of an experimental dispersion curve from data collected in situ, and inversion of the dispersion curve to determine the stiffness profile. The main object of this study is to derive an analytical Jacobian for the inversion. If we set the subsurface to N homogeneous layer, it could save 2N times Jacobian calculation compared to numerical jacobian calculation during inversion. To reconstruct a stiffness profile, constrained damped least square method was applied for the inversion. The algorithm was tested for the numerical data and for the real asphalt and tunnel data, which were able to verify the stiffness profile. The stiffness profile reconstructed by the algorithm showed the possibility to appraise the soundness of tunnel with applications SASW.

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Frequency-domain Waveform Inversion using Residual-selection Strategy (잔여 파동장 분리 기법을 이용한 주파수영역 파형역산)

  • Son, Woo-Hyun;Pyun, Suk-Joon;Kwak, Sang-Min
    • Geophysics and Geophysical Exploration
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    • v.14 no.3
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    • pp.214-219
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    • 2011
  • We perform the frequency-domain waveform inversion based on the residual-selection strategy. In the residual-selection strategy, we classify time-domain residual wavefields into several groups according to the order of absolute amplitudes. Because the residual wavefields are normalized after regularization of the gradient directions within each group, the residual-selection strategy plays a role in enhancing the small-amplitude wavefields, which contributes to improving the deep parts of inverted subsurface images. After classifying residuals in the time domain, they are transformed to the frequency domain. Waveform inversion is performed in the frequency domain using the back-propagation technique which has been popularly used in reverse-time migration. The residual-selection strategy is applied to the SEG/EAGE salt and IFP Marmousi models. Numerical results show that the residual-selection strategy yields better results than the conventional frequency-domain waveform inversion.

Joint Diversion Analysis Using the Dispersion Characteristics of Love Wave and Rayleigh Wave (I) - Constitution of Joint Diversion Analysis Technique - (러브파와 레일리파의 분산특성을 이용한 동시역산해석(I) - 동시역산해석기법의 구성 -)

  • Lee Il-Wha;Joh Sung-Ho
    • Journal of the Korean Geotechnical Society
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    • v.21 no.4
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    • pp.145-154
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    • 2005
  • Love wave and Rayleigh wave are the major elastic waves belonging to the category of the surface wave. Those waves are used to determine the ground stiffness profile using their dispersion characteristics. The fact that Love wave is not contaminated by P-wave makes Love wave superior to Rayleigh wave and other body waves. Therefore, the information that Love wave carries is more distinct and clearer than that of others. Based on theoretical research, the joint inversion analysis that uses the dispersion information of both Love and Rayleigh wave was proposed. This analysis consists of the forward modeling using transfer matrix, the sensitivity matrix for evaluating the ground system and DLSS (Damped Least Square Solution) as an inversion technique. The technique of joint inversion uses the dispersion characteristics of Love wave and Rayleigh wave simultaneously making the sensitivity matrix. The sensitivity matrix was used for inversion analysis repeatedly to find the approximate ground stiffness profile. The purpose of the joint inversion analysis is to improve accuracy and convergency of inversion results by utilizing that frequency contribution of each wave is different.

Extraction of Water Area using Artificial Neural Network from Satellite Imagery and DEM (신경망 알고리즘을 이용한 위성영상과 DEM으로부터의 수계지역 추출)

  • Sohn, Hong-Gyoo;Jung, Won-Jo;Yoo, Hwan-Hee;Song, Yeong-Sun
    • 한국지형공간정보학회:학술대회논문집
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    • 2002.11a
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    • pp.51-57
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    • 2002
  • 국내에서 활발하게 연구되고 있는 위성영상을 이용한 원격탐사는 매핑, 환경관리, 시설물 관리 등에 이용되어 왔다. 본 연구에서는 날씨나 태양의 제약을 받지 않는 RADARSAT SAR 영상의 수계지역을 신경망 기법을 이용하여 분류하고자 하였다. RADARSAT은 경사관측을 통하여 영상을 취득하며 지형의 기복에 의한 음영효과(Shadow effect)로 인하여 수계지역 분류시 정확도를 감소시킨다. 이러한 문제를 해결하기 위해서 본 연구에서는 RADARSAT SAR 영상의 역산란계수를 계산하고 음영효과에 의한 분류오류를 감소시키기 위하여 수치고도모형을 사용하였다. 지형의 기복이 작은 평지와 지형의 기복이 심한 산악지로 나누어 연구를 수행하여 각 지역별로 분류 정확도를 평가하였다. 연구결과로 역산란계수를 신경망기법의 단일 입력 자료로 사용한 경우보다 수치고도모형을 같이 사용한 것이 분류 정확도가 높았다. 또한, 수치고도모형을 역산란계수와 함께 입력 자료로 이용할 경우 평지보다 산악지에서 효율적이었다. 산악지역이 많은 국내에서는 SAR영상의 수계지역 추출을 신경망 기법으로 할 경우에는 수치고도모형을 함께 이용함으로써 분류정확도 향상을 시킬 수 있다고 사료된다.

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Geostatistical inversion of geophysical data for estimation of rock quality (물리탐사 자료의 지구통계학적 역산에 의한 암반강도 추정)

  • Oh, Seok-Hoon;Suh, Baek-Soo
    • 한국지구물리탐사학회:학술대회논문집
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    • 2008.10a
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    • pp.63-67
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    • 2008
  • Geostatistical inverse approach using geophysical data was applied to indirectly make the RMR classification at points apart from boreholes. The geostatistical appoach was usually used to find optimized estimation which supports two or more different physical properties at unsampled points. However, in this study, an approach to solve inverse problem was proposed. The primary variable, RMR values obtained at known boreholes, is geostatistically simulated with many realization at pre-defined grid point according to the variogram model. The simulated values are sequentially compared with the physical property resulted from geophysical survey at an arbitrary grid point, and the most similar one is chosen. This process means that the spatial distribution of primary variable, RMR, is conformed well to the original pattern of the borehole observation, and ensure to fit the geophysical survey result to reflect the correlation between different physical properties.

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Estimation of Shear-Wave Velocities of Layered Half-Space Using Full Waveform Inversion with Genetic Algorithm (유전 알고리즘을 활용한 완전파형역산 기법의 층상 반무한 지반 전단파 속도 추정)

  • Lee, Jin Ho;Lee, Se Hyeok
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.4
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    • pp.221-230
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    • 2021
  • This paper proposes full waveform inversion (FWI) for estimating the physical properties of a layered half-space. An FWI solution is obtained using a genetic algorithm (GA), which is a well-known global optimization approach. The dynamic responses of a layered half-space subjected to a harmonic vertical disk load are measured and compared with those calculated using the estimated physical properties. The responses are calculated using the thin-layer method, which is accurate and efficient for layered media. Subsequently, a numerical model is constructed for a layered half-space using mid-point integrated finite elements and perfectly matched discrete layers. An objective function of the global optimization problem is defined as the L2-norm of the difference between the observed and estimated responses. A GA is used to minimize the objective function and obtain a solution for the FWI. The accuracy of the proposed approach is applied to various problems involving layered half-spaces. The results verify that the proposed FWI based on a GA is suitable for estimating the material properties of a layered half-space, even when the measured responses include measurement noise.

Application of Effective Regularization to Gradient-based Seismic Full Waveform Inversion using Selective Smoothing Coefficients (선택적 평활화 계수를 이용한 그래디언트기반 탄성파 완전파형역산의 효과적인 정규화 기법 적용)

  • Park, Yunhui;Pyun, Sukjoon
    • Geophysics and Geophysical Exploration
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    • v.16 no.4
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    • pp.211-216
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    • 2013
  • In general, smoothing filters regularize functions by reducing differences between adjacent values. The smoothing filters, therefore, can regularize inverse solutions and produce more accurate subsurface structure when we apply it to full waveform inversion. If we apply a smoothing filter with a constant coefficient to subsurface image or velocity model, it will make layer interfaces and fault structures vague because it does not consider any information of geologic structures and variations of velocity. In this study, we develop a selective smoothing regularization technique, which adapts smoothing coefficients according to inversion iteration, to solve the weakness of smoothing regularization with a constant coefficient. First, we determine appropriate frequencies and analyze the corresponding wavenumber coverage. Then, we define effective maximum wavenumber as 99 percentile of wavenumber spectrum in order to choose smoothing coefficients which can effectively limit the wavenumber coverage. By adapting the chosen smoothing coefficients according to the iteration, we can implement multi-scale full waveform inversion while inverting multi-frequency components simultaneously. Through the successful inversion example on a salt model with high-contrast velocity structures, we can note that our method effectively regularizes the inverse solution. We also verify that our scheme is applicable to field data through the numerical example to the synthetic data containing random noise.