• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.32-41
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• 1999

In this paper, an inversion method using chirp signals and two near field receivers is proposed. Inversion problems can be formulated into the probabilistic models composed of signals, a forward model and noise. Forward model to simulate chirp signals is chosen to be the source-wavelet-convolution planewave modeling method. The solution of the inversion problem is defined by a posteriori pdf. The wavelet matching technique, using weighted least-squares fitting, estimates the sediment sound-speed and thickness on which determination of the ranges for a priori uniform distribution is based. The genetic algorithm can be applied to a global optimization problem to find a maximum a posteriori solution for determined a priori search space. Here the object function is defined by an L₂norm of the difference between measured and modeled signals. The observed signals can be separated into a set of two signals reflected from the upper and lower boundaries of a sediment. The separation of signals and successive applications of the genetic algorithm optimization process reduce the search space, therefore improving the inversion results. Not only the marginal pdf but also the statistics are calculated by numerical evaluation of integrals using the samples selected during importance sampling process of the genetic algorithm. The examples applied here show that, for synthetic data with noise, it is possible to carry out an inversion for sedimentary layers using the proposed inversion method.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.645-651
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• 2003

This paper presents a revised beamforming inversion method for ocean acoustic tomography. In the proposed inversion method, the relation between group velocity and phase velocity that are the characteristics of the waveguide is used for the inversion of perturbed sound speed profile. The group velocity and phase velocity can be expressed as a function of the travel time and arrival angle of the received signals that are analyzed by the beamforming signal processing. This paper illustrates the simulated results of inversion for the fluctuated sound speed profile of the East Korea Sea and we found the applicability of revised beamforming inversion method to range independent ocean.

• Geotechnical Engineering
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• v.14 no.3
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• pp.95-108
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• 1998

Downhole testing and seismic CPT (SCPT) have been widely used to evaluate stiffness profiles of the subgrade. Advantages of downhole testing and SCPT such as low cost, easy operation and a simple seismic source have got these testings more frequently adopted in site investigation. For the automated analysis of downhole testing and SCPT, the concept of interval measurements has been practiced. In this paper. a new inversion procedure to deal tilth the interval measurements for the automated downhole testing and SCPT (including a newlydeveloped continuous SCPT) is proposed. The forward modeling in the new inversion procedure incorporates ray path theory based on Snell's law. The formulation for the inversion analysis is derived from the maximum likelihood approach, which estimates the maximum likelihood of obtaining a particular travel time from a source to a receiver. Verification of the new inversion procedure was performed with numerical simulations of SCPT using synthesized profiles. The results of the inversion analyses performed for the synthetic data show that the new inversion analysis is a valid procedure which enhances Va profiles determined by downhole testing and SCPT.

• Geophysics and Geophysical Exploration
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• v.22 no.4
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• pp.202-209
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• 2019

In this study, an acoustic full-waveform inversion using Adam optimizer was proposed. The steepest descent method, which is commonly used for the optimization of seismic waveform inversion, is fast and easy to apply, but the inverse problem does not converge correctly. Various optimization methods suggested as alternative solutions require large calculation time though they were much more accurate than the steepest descent method. The Adam optimizer is widely used in deep learning for the optimization of learning model. It is considered as one of the most effective optimization method for diverse models. Thus, we proposed seismic full-waveform inversion algorithm using the Adam optimizer for fast and accurate convergence. To prove the performance of the suggested inversion algorithm, we compared the updated P-wave velocity model obtained using the Adam optimizer with the inversion results from the steepest descent method. As a result, we confirmed that the proposed algorithm can provide fast error convergence and precise inversion results.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.8 no.4
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• pp.49-57
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• 1988

A new analytical inversion technique is developed to determine the shear wave velocity profiles of natural soils and pavement systems from the dispersion curves of Rayleigh waves. Haskell's theory on the dispersion of the surface waves in multi-layered elastic solids is utilized. A frequency-unlimited dispersion equation is developed by use of the delta matrix technique. Rigid halfspace is assumed at the depth of the one wavelength of Rayleigh waves. Computer program is coded and validity of the technique is verified through the numerical model tests.

• The Journal of the Acoustical Society of Korea
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• v.17 no.7
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• pp.36-41
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• 1998

본 논문에서는 부분파수적분법과 유전자알고리즘기법의 조합을 통한 광대역 신호로 부터 직접적인 해저지질특성치의 역산기법을 제시하였다. 광대역주파수신호의 시간영역 모 의는 부분파수적분법을 사용하여 계산시간을 단축하였고, 다수의 국부최소점이 존재하는 역 산문제에 유전자알고리즘기법을 적용한 전역되적점에 대한 탐색을 수행하였다. 본 방법을 사용하여 해저퇴적층의 지질특성 요소에 대한 역산을 수행하였다.

• The Journal of the Acoustical Society of Korea
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• v.24 no.6
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• pp.325-333
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• 2005

This paper proposes a geoacoustic inversion method for the experimental data or MAPLE 2004 experiment conducted in the East Sea of Korea in 2004 and shows source tracking test results to validate the Proposed inversion method. An objective function is defined as a correlation function of the measured and the simulated transmission loss data. The measured transmission data were obtained using a multi-tonal towed source and VLA. The VFSA (Very Fast Simulated Annealing) is applied to the inversion Problem which optimizes the objective function. After performing the inversion process for the S frequencies tonal data independently. geoacoustic models are constructed. Finally matched-field source tracking is Performed using the inverted parameters to verify them.

• Geophysics and Geophysical Exploration
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• v.24 no.4
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• pp.180-193
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• 2021

The complex resistivity method is an exploration technique that can obtain various characteristic information of underground media by measuring resistivity and phase in the frequency domain, and its utilization has recently increased. In this paper, a three-dimensional inversion algorithm for the CR data was developed to increase the utilization of this method. The Poisson equation, which can be applied when the electromagnetic coupling effect is ignored, was applied to the modeling, and the inversion algorithm was developed by modifying the existing algorithm by adopting comlex variables. In order to increase the stability of the inversion, a technique was introduced to automatically adjust the Lagrangian multiplier according to the ratio of the error vector and the model update vector. Furthermore, to compensate for the loss of data due to noisy phase data, a two-step inversion method that conducts inversion iterations using only resistivity data in the beginning and both of resistivity and phase data in the second half was developed. As a result of the experiment for the synthetic data, stable inversion results were obtained, and the validity to real data was also confirmed by applying the developed 3D inversion algorithm to the analysis of field data acquired near a hydrothermal mine.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.2
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• pp.121-130
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• 1987

A new analytical method to determine the theoretical dispersion curves of Rayleigh wave in multilayered elastic media is developed. The method developed in this study gives the solutions for unlimited frequency, and is essential part of surface wave techniques to evaluate the layer profiles and dynamic properties of soils and pavement systems. Delta-Matrix technique is utilized to overcome the overflow and loss of precision problem inherent in the original Thomson-Haskell formulation at high frequencies. Conventional inversion methods based on the original Thomson-Haskell formulation lead to erroneous results due to the limitations on the layer profiles and the magnitude of frequency. The method developed in this study establishes the base of the research on more accurate and efficient inversion method, especially for the pavement systems as well as the natural soils.