• Geophysics and Geophysical Exploration
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• v.25 no.4
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• pp.252-265
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• 2022

Subsurface velocity is critical for the accurate resolution geological structures. The estimation of acoustic impedance is also critical, as it provides key information regarding the reservoir properties. Therefore, researchers have developed various inversion approaches for the estimation of reservoir properties. The Markov chain Monte Carlo method, which is a stochastic method, has advantages over the deterministic method, as the stochastic method enables us to attenuate the local minima problem and quantify the uncertainty of inversion results. Therefore, the Markov chain Monte Carlo inversion method has been applied to various kinds of geophysical inversion problems. However, studies on the Markov chain Monte Carlo inversion are still very few compared with deterministic approaches. In this study, we reviewed various types of reversible jump Markov chain Monte Carlo applications and explained the key concept of each application. Furthermore, we discussed future applications of the stochastic method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.10
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• pp.1141-1149
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• 1988

The inverse scattering scheme, which was exploited for the reconstruction of complex permittivity profiles of 2-dimensional dielectric objects by using the moment method in the spatial domain, is modified to be applicable in the spectral domain. The presented scheme is conceptually simple and provides some proper ways to regularize the ill-posed characteristics inherent to the inverse scattering problems.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.117-122
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• 2006

In the geophysical monitoring to understand the change of subsurface material properties with time, the time-invariant static subsurface model is commonly adopted to reconstruct a time-lapse image. This assumption of static model, however, can be invalid particularly when fluid migrates very quickly in highly permeable medium in the brine injection experiment. In such case, the resultant subsurface images may be severely distorted. In order to alleviate this problem, we develop a new least-squares inversion algorithm under the assumption that the subsurface model will change continuously in time. Instead of sampling a time-space model into numerous space models with a regular time interval, a few reference models in space domain at different times pre-selected are used to describe the subsurface structure continuously changing in time; the material property at a certain space coordinate are assumed to change linearly in time. Consequently, finding a space-time model can be simplified into obtaining several reference space models. In order to stabilize iterative inversion and to calculate meaningful subsurface images varying with time, the regularization along time axis is introduced assuming that the subsurface model will not change significantly during the data acquisition. The performance of the proposed algorithm is demonstrated by the numerical experiments using the synthetic data of crosshole dc resistivity tomography.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.314-321
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• 2007

Recently, multi-dimensional joint inversion of geophysical data based on fundamentally different physical properties is being actively studied. Joint inversion can provide a way to obtaining much more accurate image of the subsurface structure. Through the joint inversion, furthermore, it is possible to directly estimate non-geophysical material properties from geophysical measurements. In this study, we developed a new algorithm for jointly inverting dc resistivity and seismic traveltime data based on the multiple constraints: (1) structural similarity based on cross-gradient, (2) correlation between two different material properties, and (3) a priori information on the material property distribution. Through the numerical experiments of surface dc resistivity and seismic refraction surveys, the performance of the proposed algorithm was demonstrated and the effects of different regularizations were analyzed. In particular, we showed that the hidden layer problem in the seismic refraction method due to an inter-bedded low velocity layer can be solved by the joint inversion when appropriate constraints are applied.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2005.11a
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• pp.169-174
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• 2005

In this paper, we proposed a new algorithm of the inverse scattering for the reconstruction of unknown dielectric scatterers using the finite-difference time-domain method and the design sensitivity analysis. We introduced the design sensitivity analysis based on the gradient for the fast convergence of the reconstruction. By introducing the adjoint variable method for the efficient calculation, we derived the adjoint variable equation. As an optimal algorithm we used the steepest descent method and reconstructed the dielectric targets using the iterative estimation. To verify our algorithm we will show the numerical examples for the two-dimensional $TM^2$ cases.

• Geophysics and Geophysical Exploration
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• v.11 no.4
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• pp.326-334
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• 2008

The resistivity method has been used to image the electrical properties of the subsurface. Especially, this method has become suitable for monitoring since data could be rapidly and automatically acquired. In this study, we developed a time-lapse inversion algorithm for the interpretation of resistivity monitoring data. The developed inversion algorithm imposes a big penalty on the model parameter with small change, while a minimal penalty on the model parameter with large change compared to the reference model. Through the numerical experiments, we can ensure that the time-lapse inversion result shows more accurate and focused image where model parameters have changed. Also, applying the timelapse inversion method to the leakage detection of an embankment dam, we can confirm that there are three major leakage zones, but they have not changed over time.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.10
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• pp.653-658
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• 2016

A study on the measurement of critical heat flux using the transient inverse heat conduction method in spray cooling was performed. The inverse heat conduction method estimates the surface heat flux or temperature using a measured interior temperature history. The effects of the measuring time interval and location of temperature measurement on the measurement of critical heat flux were primarily investigated. The following results were obtained. The estimated critical heat flux decreased as the time interval of temperature measurement increased. Meanwhile, the effect of measurement location on critical heat flux was not significant. It was also found, from the experimental results, that the critical superheat increased as the measurement location of thermocouple neared the heat transfer surface.

• Journal of the Korean Geophysical Society
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• v.8 no.2
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• pp.67-74
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• 2005

Two-dimensional S-wave velocity sections from SH-wave refraction tomography and surface wave dispersions were obtained by inverting traveltimes of first arrivals and surface wave dispersions, respectively. For the purpose of comparison, a P-wave velocity tomogram was also obtained from a P-wave refraction profiling. P and Rayleigh waves generated by vertical blows on a plate with a sledgehammer were received by 100- and 4.5-Hz geophones, respectively. SH-waves generated by horizontal blows on both sides of a 50 kg timber were received by 8 Hz horizontal geophones. The shear-wave signals were enhanced subtracting data of left-side blows from ones of the right-side blows. Shear-wave velocities from tomography inversion of first-arrival times were compared with ones from inverting dispersion curves of Rayleigh waves. Although the two velocity sections look similar to each other in general, the one from the surface waves tends to have lower velocities. First arrival picking of SH waves is troublesome since P and PS-converted waves arrive earlier than SH waves. Application of the surface wave method, on the other hand, is limited where lateral variation of subsurface tructures is not mild.

• Geophysics and Geophysical Exploration
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• v.21 no.3
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• pp.139-149
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• 2018

The resistivity monitoring is a practical method to resolve changes in resistivity of underground structures over time. With the advance of sophisticated automatic data acquisition system and rapid data communication technology, resistivity monitoring has been widely applied to understand spatio-temporal changes of subsurface. In this study, a new 4D inversion algorithm is developed, which can effectively emphasize significant changes of underground resistivity with time. To overcome the overly smoothing problem in 4D inversion, the Lagrangian multipliers in the space-domain and time-domain are determined automatically so that the proportion of the model constraints to the misfit roughness remains constant throughout entire inversion process. Furthermore, a focusing model constraint is added to emphasize significant spatio-temporal changes. The performance of the developed algorithm is demonstrated by the numerical experiments using the synthetic data set for a time-lapse model.

• 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.