• Title/Summary/Keyword: full waveform inversion

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Markov Chain Monte Carlo Simulation to Estimate Material Properties of a Layered Half-space (층상 반무한 지반의 물성치 추정을 위한 마르코프 연쇄 몬테카를로 모사 기법)

  • Jin Ho Lee;Hieu Van Nguyen;Se Hyeok Lee
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.36 no.3
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    • pp.203-211
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    • 2023
  • A Markov chain Monte Carlo (MCMC) simulation is proposed for probabilistic full waveform inversion (FWI) in a layered half-space. Dynamic responses on the half-space surface are estimated using the thin-layer method when a harmonic vertical force is applied. Subsequently, a posterior probability distribution function and the corresponding objective function are formulated to minimize the difference between estimations and observed data as well as that of model parameters from prior information. Based on the gradient of the objective function, a proposal distribution and an acceptance probability for MCMC samples are proposed. The proposed MCMC simulation is applied to several layered half-space examples. It is demonstrated that the proposed MCMC simulation for probabilistic FWI can estimate probabilistic material properties such as the shear-wave velocities of a layered half-space.

A Study on Consistency of Numerical Solutions for Wave Equation (파동방정식 수치해의 일관성에 관한 연구)

  • Pyun, Sukjoon;Park, Yunhui
    • Geophysics and Geophysical Exploration
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    • v.19 no.3
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    • pp.136-144
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    • 2016
  • Since seismic inversion is based on the wave equation, it is important to calculate the solution of wave equation exactly. In particular, full waveform inversion would produce reliable results only when the forward modeling is accurately performed because it uses full waveform. When we use finite-difference or finite-element method to solve the wave equation, the convergence of numerical scheme should be guaranteed. Although the general proof of convergence is provided theoretically, the consistency and stability of numerical schemes should be verified for practical applications. The implementation of source function is the most crucial factor for the consistency of modeling schemes. While we have to use the sinc function normalized by grid spacing to correctly describe the Dirac delta function in the finite-difference method, we can simply use the value of basis function, regardless of grid spacing, to implement the Dirac delta function in the finite-element method. If we use frequency-domain wave equation, we need to use a conservative criterion to determine both sampling interval and maximum frequency for the source wavelet generation. In addition, the source wavelet should be attenuated before applying it for modeling in order to make it obey damped wave equation in case of using complex angular frequency. With these conditions satisfied, we can develop reliable inversion algorithms.

Case Analysis of Seismic Velocity Model Building using Deep Neural Networks (심층 신경망을 이용한 탄성파 속도 모델 구축 사례 분석)

  • Jo, Jun Hyeon;Ha, Wansoo
    • Geophysics and Geophysical Exploration
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    • v.24 no.2
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    • pp.53-66
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    • 2021
  • Velocity model building is an essential procedure in seismic data processing. Conventional techniques, such as traveltime tomography or velocity analysis take longer computational time to predict a single velocity model and the quality of the inversion results is highly dependent on human expertise. Full-waveform inversions also depend on an accurate initial model. Recently, deep neural network techniques are gaining widespread acceptance due to an increase in their integration to solving complex and nonlinear problems. This study investigated cases of seismic velocity model building using deep neural network techniques by classifying items according to the neural networks used in each study. We also included cases of generating training synthetic velocity models. Deep neural networks automatically optimize model parameters by training neural networks from large amounts of data. Thus, less human interaction is involved in the quality of the inversion results compared to that of conventional techniques and the computational cost of predicting a single velocity model after training is negligible. Additionally, unlike full-waveform inversions, the initial velocity model is not required. Several studies have demonstrated that deep neural network techniques achieve outstanding performance not only in computational cost but also in inversion results. Based on the research results, we analyzed and discussed the characteristics of deep neural network techniques for building velocity models.

Anewwaveform inversion methodto determine the rupture directivity of moderate earthquakes: numerical tests for rupture models (중간 규모 지진의 단층 파해 방향성 결정을 위한 새로운 주파수 영역 역산방법: 파쇄 전파 모델을 이용한 수치 시험)

  • Yoo, Seung-Hoon;Rhie, Jun-Kee
    • Geophysics and Geophysical Exploration
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    • v.12 no.1
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    • pp.114-120
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    • 2009
  • Rupture directivity is the important parameter in estimating damage due to earthquakes. However, the traditional moment tensor inversion technique cannot resolve the real fault plane or the rupture directivity. To overcome these limitations, we have developed a new inversion algorithm to determine the moment tensor solution and the rupture directivity for moderate earthquakes, using the waveform inversion technique in the frequency domain. Numerical experiments for unilateral and bilateral rupture models with various rupture velocities confirm that the method can resolve the ambiguity of the fault planes and the rupture directivity successfully. To verify the feasibility of the technique, we tested the sensitivity to velocity models, which must be the most critical factor in practice. The results of the sensitivity tests show that the method can be applied even though the velocity model is not perfect. If this method is applied in regions where the velocity model is well verified, we can estimate the rupture directivity of a moderate earthquake. This method makes a significant contribution to understanding the characteristics of earthquakes in those regions.

Time-domain Elastic Full-waveform Inversion Using One-dimensional Mesh Continuation Scheme (1차원 유한요소망 연속기법을 이용한 시간영역 탄성파의 역해석)

  • Kang, Jun Won
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.26 no.4
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    • pp.213-221
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    • 2013
  • This paper introduces a mesh continuation scheme for a one-dimensional inverse medium problem to reconstruct the spatial distribution of elastic wave velocities in heterogeneous semi-infinite solid domains. To formulate the inverse problem, perfectly-matched-layers(PMLs) are introduced as wave-absorbing boundaries that surround the finite computational domain truncated from the originally semi-infinite extent. To tackle the inverse problem in the PML-truncated domain, a partial-differential-equations(PDE)-constrained optimization approach is utilized, where a least-squares misfit between calculated and measured surface responses is minimized under the constraint of PML-endowed wave equations. The optimization problem iteratively solves for the unknown wave velocities with their updates calculated by Fletcher-Reeves conjugate gradient algorithms. The optimization is performed using a mesh continuation scheme through which the wave velocity profile is reconstructed in successively denser mesh conditions. Numerical results showed the robust performance of the mesh continuation scheme in reconstructing target wave velocity profile in a layered heterogeneous solid domain.

Parallelizing 3D Frequency-domain Acoustic Wave Propagation Modeling using a Xeon Phi Coprocessor (제온 파이 보조 프로세서를 이용한 3차원 주파수 영역 음향파 파동 전파 모델링 병렬화)

  • Ryu, Donghyun;Jo, Sang Hoon;Ha, Wansoo
    • Geophysics and Geophysical Exploration
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    • v.20 no.3
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    • pp.129-136
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    • 2017
  • 3D seismic data processing methods such as full waveform inversion or reverse-time migration require 3D wave propagation modeling and heavy calculations. We compared efficiency and accuracy of a Xeon Phi coprocessor to those of a high-end server CPU using 3D frequency-domain wave propagation modeling. We adopted the OpenMP parallel programming to the time-domain finite difference algorithm by considering the characteristics of the Xeon Phi coprocessors. We applied the Fourier transform using a running-integration to obtain the frequency-domain wavefield. A numerical test on frequency-domain wavefield modeling was performed using the 3D SEG/EAGE salt velocity model. Consequently, we could obtain an accurate frequency-domain wavefield and attain a 1.44x speedup using the Xeon Phi coprocessor compared to the CPU.

A Study on Field Seismic Data Processing using Migration Velocity Analysis (MVA) for Depth-domain Velocity Model Building (심도영역 속도모델 구축을 위한 구조보정 속도분석(MVA) 기술의 탄성파 현장자료 적용성 연구)

  • Son, Woohyun;Kim, Byoung-yeop
    • Geophysics and Geophysical Exploration
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    • v.22 no.4
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    • pp.225-238
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    • 2019
  • Migration velocity analysis (MVA) for creating optimum depth-domain velocities in seismic imaging was applied to marine long-offset multi-channel data, and the effectiveness of the MVA approach was demonstrated by the combinations of conventional data processing procedures. The time-domain images generated by conventional time-processing scheme has been considered to be sufficient so far for the seismic stratigraphic interpretation. However, when the purpose of the seismic imaging moves to the hydrocarbon exploration, especially in the geologic modeling of the oil and gas play or lead area, drilling prognosis, in-place hydrocarbon volume estimation, the seismic images should be converted into depth domain or depth processing should be applied in the processing phase. CMP-based velocity analysis, which is mainly based on several approximations in the data domain, inherently contains errors and thus has high uncertainties. On the other hand, the MVA provides efficient and somewhat real-scale (in depth) images even if there are no logging data available. In this study, marine long-offset multi-channel seismic data were optimally processed in time domain to establish the most qualified dataset for the usage of the iterative MVA. Then, the depth-domain velocity profile was updated several times and the final velocity-in-depth was used for generating depth images (CRP gather and stack) and compared with the images obtained from the velocity-in-time. From the results, we were able to confirm the depth-domain results are more reasonable than the time-domain results. The spurious local minima, which can be occurred during the implementation of full waveform inversion, can be reduced when the result of MVA is used as an initial velocity model.

Elastic Wave Propagation in Nuclear Power Plant Containment Building Walls Considering Liner Plate and Concrete Cavity (라이너 플레이트 및 콘크리트 공동을 고려한 원전 격납건물 벽체의 탄성파 전파 해석)

  • Kim, Eunyoung;Kim, Boyoung;Kang, Jun Won;Lee, Hongpyo
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.34 no.3
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    • pp.167-174
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    • 2021
  • Recent investigation into the integrity of nuclear containment buildings has highlighted the importance of developing an elaborate diagnostic method to evaluate the distribution and size of cavities inside concrete walls. As part of developing such a method, this paper presents a finite element approach to modeling elastic waves propagating in the containment building walls of a nuclear power plant. We introduce a perfectly matched layer (PML) wave-absorbing boundary to limit the large-scale nuclear containment wall to the region of interest. The formulation results in a semi-discrete form with symmetric damping and stiffness matrices. The transient elastic wave equations for a mixed unsplit-field PML were solved for displacement and stresses in the time domain. Numerical results show that the sensitivity of displacement, velocity, acceleration, and stresses is large depending on the size and location of the cavity. The dynamic response of the wall slightly differs depending on the existence of the containment liner plate. The results of this study can be applied to a full-waveform inversion approach for characterizing cavities inside a containment wall.