• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.233-236
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• 2005

Polarization filtering based on the multicomponent complex trace analysis method is performed to reject Rayleigh waves and to enhance S waves. To test the polarization filter, synthetic seismic data were constructed for a simple two-layer model based on the finite difference method. Rayleigh waves with elliptic motion are eliminated effectively and P and S waves with linear motions are well separated each other.

• Journal of Korean Society of Steel Construction
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• v.8 no.3 s.28
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• pp.97-105
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• 1996

A Stochastic line source model is developed to simulate the seismic wave field generated during the rupture propagation process along a fault plane of which length is much larger than its width. The fault plane is assumed to consist of randomly distributed slip zones and barriers and each slip zone is modeled as a point source. By combining the newly developed source model with wave propagation analysis method in a layered 3-D visco-elastic half space, synthetic seismograms are obtained. The calculated accelerograms due to vertical dip slip and strike slip line sources are presented.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.197-202
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• 2007

Most of seismic reflection prospecting assumes subsurface formation to be homogeneous media. These models are not capable of estimating small scale heterogeneity which is verified by well log data or drilling core. And those synthetic seismograms by homogeneous media are limited to explain various changes at field data. So we developed a inhomogeneous velocity model which can estimate inhomogeneity of background medium to implement numerical modeling from homogeneous medium and inhomogeneous medium on the model. Background medium using three autocorrelation functions in order to generate inhomogeneous velocity media was according to dominant wavelength of background medium and correlation length of random medium. And then we compared shot gathers. The results show that numerical modeling implemented at inhomogeneous medium depicts complex wave propagation of field data.

• Journal of the Korean Geophysical Society
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• v.8 no.1
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• pp.35-38
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• 2005

Polarization filtering based on the multicomponent complex trace analysis method is performed to reject Rayleigh waves and to enhance S waves. To test the polarization filter, synthetic seismic data were constructed for a simple two-layer model based on the finite difference method. Rayleigh waves with elliptic motion are eliminated effectively and P and S waves with linear motions are well separated each other.

• Geophysics and Geophysical Exploration
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• v.11 no.4
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• pp.361-367
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• 2008

When constructing a synthetic seismogram in the earthquake study or in seismic data interpretation by using a ray-tracing technique, the most troublesome and error-prone task is to define a suite of ray codes for the corresponding rays to trace in advance. An infinite number of rays exist for any arbitrarily located source and receiver in a medium. Missing certain important rays or an inappropriate selection of ray codes in tracing rays may result in wrong interpretation of the earthquake record or seismogram. Automatic ray code generation could be able to eliminate those problems. In this study we have developed an efficient algorithm with which one can generate systematically all the ray codes for the source(s) and receiver(s) arbitrarily located in a model. The result of this work could be used not only in analysing multiples in seismic data processing and interpretation, but also in coda wave study, study on the amplification effects in a basin and phase identification of the waves multiply reflected/refracted in earthquake study.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.37-51
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• 2023

The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.41-49
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• 2005

We have developed a random heterogeneous velocity model with bimodal distribution in methane hydrate-bearing Bones. The P-wave well-log data have a von Karman type autocorrelation function and non-Gaussian distribution. The velocity histogram has two peaks separated by several hundred metres per second. A random heterogeneous medium with bimodal distribution is generated by mapping of a medium with a Gaussian probability distribution, yielded by the normal spectral-based generation method. By using an ellipsoidal autocorrelation function, the random medium also incorporates anisotropy of autocorrelation lengths. A simulated P-wave velocity log reproduces well the features of the field data. This model is applied to two simulations of elastic wane propagation. Synthetic reflection sections with source signals in two different frequency bands imply that the velocity fluctuation of the random model with bimodal distribution causes the frequency dependence of the Bottom Simulating Reflector (BSR) by affecting wave field scattering. A synthetic cross-well section suggests that the strong attenuation observed in field data might be caused by the extrinsic attenuation in scattering. We conclude that random heterogeneity with bimodal distribution is a key issue in modelling hydrate-bearing Bones, and that it can explain the frequency dependence and scattering observed in seismic sections in such areas.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.89-94
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• 2006

In order to increase the signal-to-noise ratio in multi-component seismic data, we developed new polarization filters based on the method of multicomponent complex trace analysis. Unlike the previous polarization filters, the present filters separately compute linear and elliptic components at each time sample using amplitude ratio of horizontal and vertical components of body waves and ellipticity of Rayleigh waves. The polarization filters work ideally even with low S/N data. Application of the filters to both synthetic and real seismic data shows that Rayleigh waves of elliptic motions are effectively eliminated and both P and S waves of linear motions are well separated each other.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.54-63
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• 2015

Petrophysical parameters such as porosity and fluid saturation which provide useful information for reservoir characterization could be estimated by rock physics model (RPM) using seismic velocity and resistivity. Therefore, accurate P-wave velocity and resistivity information have to be obtained for successful estimation of the petrophysical parameters. Compared with the individual inversion of electromagnetic (EM) or seismic data, the joint inversion using both EM and seismic data together can reduce the uncertainty and gives the opportunity to use the advantages of each data. Thus, more reliable petrophysical properties could be estimated through the joint inversion. In this paper, for the successful estimation of petrophysical parameters, we proposed an effective method which applies a grid-search method to find the porosity and fluid saturation. The relations of porosity and fluid saturation with P-wave velocity and resistivity were expressed by using RPM and the improved resistivity distribution used to this study was obtained by joint inversion of seismic and EM data. When the proposed method was applied to the synthetic data which were simulated for subsea reservoir exploration, reliable petrophysical parameters were obtained. The results indicate that the proposed method can be applied for detecting a reservoir and calculating the accurate oil and gas reserves.

• Geophysics and Geophysical Exploration
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• v.10 no.1
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• pp.77-88
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• 2007

Following a successful bathymetric mapping demonstration in a previous study, the potential of airborne EM for seafloor characterisation has been investigated. The sediment thickness inferred from 1D inversion of helicopter-borne time-domain electromagnetic (TEM) data has been compared with estimates based on marine seismic studies. Generally, the two estimates of sediment thickness, and hence depth to resistive bedrock, were in reasonable agreement when the seawater was ${\sim}20\;m$ deep and the sediment was less than ${\sim}40\;m$ thick. Inversion of noisy synthetic data showed that recovered models closely resemble the true models, even when the starting model is dissimilar to the true model, in keeping with the uniqueness theorem for EM soundings. The standard deviations associated with shallow seawater depths inferred from noisy synthetic data are about ${\pm}5\;%$ of depth, comparable with the errors of approximately ${\pm}1\;m$ arising during inversion of real data. The corresponding uncertainty in depth-to-bedrock estimates, based on synthetic data inversion, is of order of ${\pm}10\;%$. The mean inverted depths of both seawater and sediment inferred from noisy synthetic data are accurate to ${\sim}1\;m$, illustrating the improvement in accuracy resulting from stacking. It is concluded that a carefully calibrated airborne TEM system has potential for surveying sediment thickness and bedrock topography, and for characterising seafloor resistivity in shallow coastal waters.