• Geophysics and Geophysical Exploration
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• v.14 no.3
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• pp.234-241
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• 2011

Recently, exploration and development of oil sands are thriving due to high oil price. Because oil sands reservoir usually exists as a thin layer, multicomponent VSP, which has the advantage of the high-resolution around the borehole, is more effective than surface seismic survey in exploring oil sand reservoir. In addition, prestack phase-screen migration is effective for multicomponent seismic data because it is based on an one-way wave equation. In this study, we examined the applicability of the prestack phase-screen migration for multicomponent RVSP data to image the thin oil sand reservoir. As a preprocessing tool, we presented a method for separating P-wave and PS-wave from multicomponent RVSP data by using incidence angle and rotation matrix. To verify it, we have applied the developed wavefield separation method to synthetic data obtained from the velocity model including a horizontal layer and dipping layers. Also, we compared the migrated image by using P-wave with that by using PS-wave. As a result, the PS-wave migrated image has higher resolution and wide coverage than P-wave migrated image. Finally, we have applied the prestack phase-screen migration to the synthetic data from the velocity model simulating oil sand reservoir in Canada. The results show that the PS-wave migrated image describe the top and bottom boundaries of the thin oil sand reservoir more clearly than the P-wave migrated image.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.4
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• pp.165-173
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• 1998

Analytical solutions to predict the movement rate of submerged mound are derived using the convection coefficient and the joint distribution function of wave heights and periods. Assuming that the sediment is moved onshore due to the velocity asymmetry of Stokes' second order nonlinear wave theory, the micro-scale bedload transport equation is applied to the sediment conservation. The nonlinear convection-diffusion equation can then be obtained which governs the migration of submerged mound. The movement rate decreases exponentially with increasing the water depth, but the movement rate tends to increase as the spectral width parameter, $ u$ increases. In comparison of the analytical solution with the measured data, it is found that the analytical solution overestimates the movement rate. However, the agreement between the analytical solution and the measured data is encouraging since this over-estimation may be due to the inaccuracy of input data and the limitation of sediment transport model. In particular, the movement rates with respect to the water depth predicted by the analytical solution are in very good agreement with the estimated result using the discritization technique with the hindcast wave data.

• Geophysics and Geophysical Exploration
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• v.13 no.4
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• pp.315-322
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• 2010

The phase-screen and the split-step Fourier migrations, which are implemented in both the frequency-wavenumber and frequency-space domains by using one-way scalar wave equation, allow imaging in laterally heterogeneous media with less computing time and efficiency. The generalized-screen migration employs the series expansion of the exponential, unlike the phase-screen and the split-step Fourier migrations which assume the vertical propagation in frequency-wavenumber domain. In addition, since the generalized-screen migration generalizes the series expansion of the vertical slowness, it can utilize higher-order terms of that series expansion. As a result, the generalized-screen migration has higher accuracy in computing the propagation with wide angles than the phase-screen and split-step Fourier migrations for media with large and rapid lateral velocity variations. In this study, we developed a 2D prestack generalized-screen migration module for imaging a complex subsurface efficiently, which includes various dips and large lateral variations. We compared the generalized-screen propagator with the phase-screen propagator for a constant perturbation model and the SEG/EAGE salt dome model. The generalized-screen propagator was more accurate than the phase-screen propagator in computing the propagation with wide angles. Furthermore, the more the higher-order terms were added for the generalized-screen propagator, the more the accuracy was increased. Finally, we compared the results of the generalizedscreen migration with those of the phase-screen migration for a model which included various dips and large lateral velocity variations and the synthetic data of the SEG/EAGE salt dome model. In the generalized-screen migration section, reflectors were positioned more accurately than in the phase-screen migration section.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.36 no.6
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• pp.749-756
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• 2003

Hydroacoustic and open-closing zooplankton net survey were conducted to understand the characteristics of the sound scattering layer (SSL) and to estimate the density of an euphausiid (Euphausia pacifica) in the SSL, in the northwestern part of the East China Sea. The survey was carried out during July 6-9 2002 at 8 sampling stations for zooplankton. The virtual echogram technique was used to identify E. pacifica from all acoustic scatters. Mean volume backscattering strength difference $(MVBS_{120kHz-38kHz})$ and target strength equation for E. pacifica were derived from the Distorted-wave Born Approximation (DWBA) model. Although vertical migration of the SSL is similar to the general pattern, dispersion at night shows some differences. Estimated mean density using acoustic data ranged from $20.4-221.4\;mg/m^3$ over the whole depth, and $87.1-553.5\;mg/m^3$ in the SSL. The density using the zooplankton net ranged from $0.2-362.4\;mg/m^3$ and was not related to net deploying method. The results from the acoustic and net survey suggest that E. pacifica might be an important zooplankton community in the northwestern part of the East China Sea.

• Journal of Digital Convergence
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• v.18 no.8
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• pp.21-27
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• 2020

This paper studies the impact of domestic and foreign economic activity on mobility among regions. The shortage of human resources and demand continues in Eastern Europeans. Especially Ukrainians, have entered the Polish labor market to make up for the scarce areas. As a result, Poland's supply and demand in Ukraine is disproportionate. Minimum wage increases are putting continued pressure on employers. Therefore, the regression equation in the form of job-seeker's economic activity ratio, y= AX²+B,(x=settlers) can be used to grasp the relationship between curves. According to the domestic and foreign workers who migrated, economic activities was rather than increasing the local population, the settlers of nearby large cities is more proportional. Empirical analysis has shown that the human resource hub has increased migration to large cities and industrial. The hub 'A'nation has been created for mobility in 4th wave re-industry, and the same re-industrialization (N₂) in other cities has attracted nearby human resources, but not settle. After all, the hub relationship between N₁ and N₂ is a mobile relationship. Due to wage inequality or a positive wellbeing chasm, workers are not settled plant area but a nearby city, or commuting between borders is easy to go into the hub central city. However, this proved on emerging from the relatively temporary settlers in the AI era.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.89-97
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• 2021

Fault detection in seismic data is well suited to the application of machine learning algorithms. Accordingly, various machine learning techniques are being developed. In recent studies, machine learning models, which utilize synthetic data, are the particular focus when training with deep learning. The use of synthetic training data has many advantages; Securing massive data for training becomes easy and generating exact fault labels is possible with the help of synthetic training data. To interpret real data with the model trained by synthetic data, the synthetic data used for training should be geologically realistic. In this study, we introduce a method to generate realistic synthetic seismic data. Initially, reflectivity models are generated to include realistic fault structures, and then, a one-way wave equation is applied to efficiently generate seismic stack sections. Next, a migration algorithm is used to remove diffraction artifacts and random noise is added to mimic actual field data. A convolutional neural network model based on the U-Net structure is used to verify the generated synthetic data set. From the results of the experiment, we confirm that realistic synthetic data effectively creates a deep learning model that can be applied to field data.