• Geophysics and Geophysical Exploration
• /
• v.9 no.1
• /
• pp.93-101
• /
• 2006

In this study, we propose a joint inversion method, using genetic algorithms, to determine the shear-wave velocity structure of deep sedimentary layers from receiver functions and surface-wave phase velocity. Numerical experiments with synthetic data indicate that the proposed method can avoid the trade-off between shear-wave velocity and thickness that arises when inverting the receiver function only, and the uncertainty in deep structure from surface-wave phase velocity inversion alone. We apply the method to receiver functions obtained from earthquake records with epicentral distances of about 100 km, and Rayleigh-wave phase velocities obtained from a microtremor array survey in the Kanto Plain, Japan. The estimated subsurface structure is in good agreement with the previous results of seismic refraction surveys and deep borehole data.

• Geophysics and Geophysical Exploration
• /
• v.10 no.1
• /
• pp.1-18
• /
• 2007

Non-linear elastic wavefield inversion is a powerful method for estimating elastic parameters for physical constraints that determine subsurface rock and properties. Here, I introduce six elastic-wave velocity models by reconstructing elastic-wave velocity variations from real data and a 2D elastic-wave velocity model. Reflection seismic data information is often decoupled into short and long wavelength components. The local search method has difficulty in estimating the longer wavelength velocity if the starting model is far from the true model, and source frequencies are then changed from lower to higher bands (as in the 'frequency-cascade scheme') to estimate model elastic parameters. Elastic parameters are inverted at each inversion step ('simultaneous mode') with a starting model of linear P- and S-wave velocity trends with depth. Elastic parameters are also derived by inversion in three other modes - using a P- and S-wave velocity basis $('V_P\;V_S\;mode')$; P-impedance and Poisson's ratio basis $('I_P\;Poisson\;mode')$; and P- and S-impedance $('I_P\;I_S\;mode')$. Density values are updated at each elastic inversion step under three assumptions in each mode. By evaluating the accuracy of the inversion for each parameter set for elastic models, it can be concluded that there is no specific difference between the inversion results for the $V_P\;V_S$ mode and the $I_P$ Poisson mode. The same conclusion is expected for the $I_P\;I_S$ mode, too. This gives us a sound basis for full wavelength elastic wavefield inversion.

• Geophysics and Geophysical Exploration
• /
• v.6 no.2
• /
• pp.95-100
• /
• 2003

In this study, we developed reflection tomography inversion algorithm using Straight Ray Technique (SRT) which can calculate travel time easily and fast for complex geological structure. The inversion process begins by setting the initial velocity model as a constant velocity model that hat only impedance boundaries. The inversion process searches a layer-interface structure model that is able to explain the given data satisfactorily by inverting to minimize data misfit. For getting optimal solution, we used Gauss-Newton method that needed constructing the approximate Hessian matrix. We also applied the Marquart-Levenberg regularization method to this inversion process to prevent solution diverging. The ability of the method to resolve typical target structures was tested in a synthetic salt dome inversion. Using the inverted velocity model, we obtained the migration image close to that of the true velocity model.

• Geophysics and Geophysical Exploration
• /
• v.10 no.1
• /
• pp.19-28
• /
• 2007

In this study, we propose a joint inversion method, using genetic algorithms, to estimate an S-wave velocity structure for deep sedimentary layers from receiver functions and surface-wave phase velocity observed at several sites. The method takes layer continuity over a target area into consideration by assuming that each layer has uniform physical properties, especially an S-wave velocity, at all the sites in a target area in order to invert datasets acquired at different sites simultaneously. Numerical experiments with synthetic data indicate that the proposed method is effective in reducing uncertainty in deep structure parameters when modelling only surface-wave dispersion data over a limited period range. We then apply the method to receiver functions derived from earthquake records at one site and two datasets of Rayleigh-wave phase velocity obtained from microtremor array surveys performed in central Tokyo, Japan. The estimated subsurface structure is in good agreement with the results of previous seismic refraction surveys and deep borehole data. We also conclude that the proposed method can provide a more accurate and reliable model than individual inversions of either receiver function data only or surface-wave dispersion data only.

• Journal of the Korean Geophysical Society
• /
• v.4 no.1
• /
• pp.35-46
• /
• 2001

한반도 중부에 위치한 대전 지진관측소(TJN) 하부의 세부 지각구조를 밝혀내기 위하여 수신함수를 이용한 선형화된 역산(linearized inversion) 방법을 적용하였다. 본 방법의 비단일해(nonuniqueness)와 초기 모델 의존성의 문제를 해결하기 위해 근사 초기 속도 모델로부터 72개의 서로 다른 초기 모델을 구하여 역산을 수행한 후 결과모델들의 평균 속도 모델을 제시하는 방법을 사용하였다. 역산 결과 총 72개의 모델 중 뚜렷한 지각-맨틀 경계를 보이는 43개의 모델만이 조건에 만족하는 결과를 나타내었다. 모든 모델에서 속도 구조는 전체적으로 깊이에 따라 속도의 불연속면이나 급격한 증가없이 연속적인 변화를 하며, 모호면의 깊이는 30～32.5 km의 범위로 나타났다. 평균적인 하부 지각의 속도는 6.5 km/s, 상부 맨틀의 속도는 7.8 km/s로 뚜렷한 속도 변화를 보였다. 결과 모델 군은 중부지각(mid-crust)에서의 속도를 기준으로 약한 저속도층을 나타내는 군과 상대적으로 일정한 속도를 가지는 군으로 구분되었다. 단지 지진파형의 비교만으로 두 모델군 중 합당한 모델군의 선택은 불가능하였다. 따라서 수신 함수를 이용하여 연구 지역의 신뢰할 만한 지각 구조를 구하기 위해서는 그 지역에 대한 지질학적, 지구물리학적 추가정보와의 동반 해석이 요구된다.

• Geophysics and Geophysical Exploration
• /
• v.8 no.1
• /
• pp.26-33
• /
• 2005

Inversion of multi-mode surface-wave phase velocity for shallow engineering site investigation has received much attention in recent years. A sensitivity analysis and inversion of both synthetic and field data demonstrates the greater effectiveness of this method over employing the fundamental mode alone. Perturbation of thickness and shear-wave velocity parameters in multi-modal Rayleigh wave phase velocities revealed that the sensitivities of higher modes: (a) concentrate in different frequency bands, and (b) are greater than the fundamental mode for deeper parameters. These observations suggest that multi-mode phase velocity inversion can provide better parameter discrimination and imaging of deep structure, especially with a velocity reversal, than can inversion of fundamental mode data alone. An inversion of the theoretical phase velocities in a model with a low velocity layer at 20 m depth can only image the soft layer when the first higher mode is incorporated. This is especially important when the lowest measurable frequency is only 6 Hz. Field tests were conducted at sites surveyed by borehole and PS logging. At the first site, an array microtremor survey, often used for deep geological surveying in Japan, was used to survey the soil down to 35 m depth. At the second site, linear multichannel spreads with a sledgehammer source were recorded, for an investigation down to 12 m depth. The f-k power spectrum method was applied for dispersion analysis, and velocities up to the second higher mode were observed in each test. The multi-mode inversion results agree well with PS logs, but models estimated from the fundamental mode alone show f large underestimation of the depth to shallow soft layers below artificial fill.

• Geophysics and Geophysical Exploration
• /
• v.26 no.2
• /
• pp.84-93
• /
• 2023

The supervised learning-based deep-learning seismic inversion techniques have demonstrated successful performance in synthetic data examples targeting small-scale areas. The supervised learning-based deep-learning seismic inversion uses time-domain wavefields as input and subsurface velocity models as output. Because the time-domain wavefields contain various types of wave information, the data size is considerably large. Therefore, research applying supervised learning-based deep-learning seismic inversion trained with a significant amount of field-scale data has not yet been conducted. In this study, we predict subsurface velocity models using Laplace-domain wavefields as input instead of time-domain wavefields to apply a supervised learning-based deep-learning seismic inversion technique to field-scale data. Using Laplace-domain wavefields instead of time-domain wavefields significantly reduces the size of the input data, thereby accelerating the neural network training, although the resolution of the results is reduced. Additionally, a large grid interval can be used to efficiently predict the velocity model of the field data size, and the results obtained can be used as the initial model for subsequent inversions. The neural network is trained using only synthetic data by generating a massive synthetic velocity model and Laplace-domain wavefields of the same size as the field-scale data. In addition, we adopt a towed-streamer acquisition geometry to simulate a marine seismic survey. Testing the trained network on numerical examples using the test data and a benchmark model yielded appropriate background velocity models.

• Geophysics and Geophysical Exploration
• /
• v.25 no.4
• /
• pp.214-216
• /
• 2022

Distributed acoustic sensing (DAS), an increasingly growing acquisition technique in the oil and gas exploration and seismology fields, has been used to record seismic signals using optical cables as receivers. With the development of imaging methods for DAS data, full waveform inversion (FWI) is been applied to DAS data to obtain high-resolution property models such as P- and S-velocity. However, because the DAS systems measure strain from the phase distortion between two points along optical cables, DAS data must be transformed from strain to particle velocity for FWI algorithms. In this study, a plane-wave FWI algorithm based on the relationship between strain and horizontal particle velocity in the plane-wave assumption is proposed to apply FWI to DAS data. Under the plane-wave assumption, strain equals the horizontal particle velocity, which is scaled by the velocity at the receiver position. This relationship was confirmed using a numerical experiment. Furthermore, 4-layer and modified Marmousi-2 velocity models were used to verify the applicability of the proposed FWI algorithm in various survey environments. The proposed FWI was implemented in land and marine survey environments and provided high-resolution P- and S-velocity models.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2006.06a
• /
• pp.51-59
• /
• 2006

The surface wave data obtained in a tidal flat located in the sw coast of the Korean Peninsula were used to analyse the shear wave velocity structure of the area. First, the phase velocity dispersion curves were obtained by the tau-p stacking method and the group velocity dispersion curves by a wavelet transform method and the Multiple Filtering Technique by Dziewonski. The phase velocity dispersion curves exhibited bigger errors than the group velocity curves. The results showed that the wavelet transform method was more effective in separating the fundamental and the 1st higher mode group velocity curves than the Multiple Filtering Technique. Combined use of the fundamental and the 1st higher mode group velocity dispersion curves in the inversion for the shear wave velocity structure gave better spatial resolution compared when the fundamental mode group velocity was used alone. This study indicates that the group velocity dispersion curves can be used in the inversion of Rayleigh waves for the shear wave velocity structure, especially effectively with the higher mode group velocity curves together.

• Geophysics and Geophysical Exploration
• /
• v.10 no.4
• /
• pp.393-398
• /
• 2007

Seismic traveltime tomography technique was conducted at a site composed of black shale. It is well known that black shale has strong anisotropic property. Therefore, the anisotropic property of black shale has to be considered to obtain the appropriate subsurface velocity model by an inversion process. To estimate the anisotropic constant of the velocity of the black shale in the survey area, the relation between the velocity, which is calculated by the straight ray path and the first arrival time, and the angle of the ray propagation was examined. The elliptically shaped relation was found and it reveals that the black shale contains the anisotropic property of velocity. It was also noticed that the horizontal velocity is faster than the vertical velocity. When the estimated anisotropic constant was applied in the process of the velocity inversion for three sets of field data, we could obtain the appropriate velocity structures of the site that is consistent with the result of the geological survey.