• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.1245-1246
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• 2015

광대역 표면 탄성파(Surface Acoustic Wave)를 이용하여 도파로 층의 빛을 특정 각도로 변조하여 편향 휴대용 홀로그램 디스플레이를 구현하기 위한 음향 광학(Acoustic-Optic) 장치를 개발했다. 개발된 시스템은 프리즘, 도파로층, 표면탄성파를 일으키는 IDT 및 스크린으로 구성된다. 도파로내에서 전파하는 빛은 표면탄성파에 에너지가 가해지지 않으면 도파로층의 진행중 경로 변화가 발생하지 않지만 표면 탄성파에 에너지를 가하면 빛의 편향된다. 큰 편향 각도와 고효율을 위해서 표면탄성파의 파워, 표면탄성파의 중심주파수, IDT aperture length, waveguide thickness 등을 조절하여 빛 편향각도 및 효율변화를 관찰하였다.

• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.125.2-125.2
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• 2011

청정 에너지원으로 높은 잠재력을 가지고 있는 가스하이드레이트는 상업적 기술개발이 미확보된 상태이다. 현재 전 세계적으로 가스하이드레이트 개발 및 생산에 관한 연구가 활발히 진행되고 있으며 이에 대한 기초자료로서 가스하이드레이트가 함유된 퇴적층의 물성자료가 필요하다. 특히, 현장 시료에 대한 물성 측정은 향후 가스하이드레이트 개발 및 생산 계획을 수립하는데 있어서 매우 중요하다. 탄성파 측정 결과는 다른 물성 들에 비하여 하이드레이트 함유 시료의 성형과정에 큰 영향을 받는다. 또한 그 외의 실험 경계조건과 취득 자료의 처리 과정에도 매우 민감하게 반응한다. 따라서 측정을 하는 과정은 물론 측정 후 자료의 활용 과정에서 다양히 고려해야 할 점들이 있다. 본 연구에서는 인공 모래를 이용하여 다양한 조건에서 탄성파 속도를 측정한 후 그 결과를 토대로 하여 기존의 연구 결과와 비교하여 음파 측정연구 시 고려해야 할 기술적 사항 들을 정리해 보았다. 실험에 사용된 장비는 고압의 퇴적층을 모사할 수 있는 압력셀과 메탄과 염수 주입에 사용되는 유체 주입장비, 하이드레이트 형성을 위한 온도조절장비, 자료 획득 장비로 구성되어 있다. p파 속도는 음파 송수신장비를 사용하였다.

• Journal of the Korean Geotechnical Society
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• v.21 no.5
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• pp.215-223
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• 2005

Piezo-ceramics are special materials which transform energy from mechanical to electrical forms and vice versa. Bender elements are composite materials consisting of thin piezo-ceramics and elastic shims, and are widely used as actuators and transducers in the field of electronics, robotics, autos and mechatronics utilizing the effectiveness of energy transformation capability. In geotechnical engineering, commercial bender elements are used in laboratory as source and receiver in the measurements of soil stiffness. The elements were built by using various metal shims sandwiched between piezo-ceramics and coating over the composite in the research. A pair of elements were buried in a concrete block and used as source and receiver to measure the stiffness of the concrete. The test results were verified by comparing with the resonant column testing results. In a preliminary stage of the development of an in-situ seismic testing equipment using bender elements for soft clay materials, shear waves were generated and measured by burying the elements in the barrel of kaolinite and water mixture. The measured shear wave signals were so distinct for the first-arrival pick that applicability of the elements in the field measurements could be very promising.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.227-236
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• 1997

Quantitative analysis and imaging of elastic wave propagation are very important for the materials evaluation as well as flaw detection. The elastic wave propagation in an anisotropic media is more complex, and analysis and imaging become essential for flaw detection and materials evaluation. In the anisotropic media, the wave velocity is dependent on the propagation direction. In addition, the direction of group velocity is different from that of phase velocity, the direction of energy flow is not same as the propagation direction of wavefront (beam skewing effect). Especially, this effect becomes critical for the large anisotropic media such as fiber composite materials, and the results using elastic waves for those materials have to be analyzed considering the wave propagation mechanism. Since the analytical approach for the wave propagation in the anisotropic materials is limited, the numerical analysis such as finite difference method (FDM) have been used for these case. Therefore, 2-dimensional FDM program for the elastic wave propagation is developed, and wave propagation in anisotropic media are simulated.

• Economic and Environmental Geology
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• v.46 no.6
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• pp.485-494
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• 2013

$CO_2$ Monitoring, Mitigation and Verification (MMV) is the essential part in the Carbon Capture and Storage (CCS) project in order to assure the storage permanence economically and environmentally. In large-scale CCS projects in the world, the seismic time-lapse survey is a key technology for monitoring the behavior of injected $CO_2$. In this study, we developed a basic process procedure for 3-D seismic baseline data from the Aquistore project, Estevan, Canada. Major target formations of Aquistore CCS project are the Winnipeg and the Deadwood sandstone formations located between 1,800 and 1,900 ms in traveltime. The analysis of trace energy and similarity attributes of seismic data followed by spectral decomposition are carried out for the characterization of $CO_2$ injection zone. High trace energies are concentrated in the northern part of the survey area at 1,800 ms and in the southern part at 1,850 ms in traveltime. The sandstone dominant regions are well recognized with high reflectivity by the trace energy analysis. Similarity attributes show two structural discontinuities trending the NW-SE direction at the target depth. Spectral decomposition of 5, 20 and 40 Hz frequency contents discriminated the successive E-W depositional events at the center of the research area. Additional noise rejection and stratigraphic interpretation on the baseline data followed by applying appropriate imaging technique will be helpful to investigate the differences between baseline data and multi-vintage monitor data.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.489-492
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• 2007

The P-wave velocity at the formation which contains gas hydrate varies very wide upon gas hydrate existence. These features on seismic shot gather can not be simulated normally by numerical modeling of homogeneous medium so that we need that of random inhomogeneous medium instead. We, in this study generated random inhomogeneous medium using gaussian ACF, exponential ACF and von Karman ACF and that we supposed the random inhomogeneous medium be gas hydrate formation to execute numeric modeling. The modeling result shows the typical effect by scattering caused by random hydrate formation as is observed from seismic shot gather where hydrate exist.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.84-93
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• 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
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• v.25 no.4
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• pp.203-213
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• 2022

To understand an underlying geological structure via seismic imaging, the velocity information of the subsurface medium is crucial. Although the full-waveform inversion (FWI) method is considered useful for estimating subsurface velocity models, 3D FWI needs a lot-of computing power and time. Herein, we compare the calculation efficiency and accuracy of frequency-domain 2D and 3D acoustic FWIs. Thereafter, we demonstrate that the artifacts from 2D approximation can be partially suppressed via frequency-domain 2D FWI by employing diffraction angle filtering (DAF). By applying DAF, which employs only big reflection angle components, the impact of noise and out-of-plane reflections can be reduced. Additionally, it is anticipated that the DAF can create long-wavelength velocity structures for 3D FWI and migration.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.672-675
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• 2009

동해 울릉분지에서 취득된 다중채널 탄성파자료 해석에 의하면 이 지역에는 가스하이드레이트 부존가능성을 지시하는 해저모방반사면, 탄성파침니/칼럼, 음향공백대, 증폭반사면, 가스분출 구조 등을 포함하는 5가지 탄성파 지시자가 존재한다. 가장 대표적인 지시자인 해저모방반사면은 연구지역의 남쪽사면의 경우 연속성이 양호하고 강한 진폭을 갖는 반면, 북쪽 중앙분지에서는 상대적으로 진폭이 약하고 연속성이 불량하다. 반사도 감소 및 속도 풀업 특징을 갖는 탄성파 침니/칼럼구조는 중앙분지와 북동쪽해역에 주로 분포하며 가스하이드레이트 혹은 가스유체의 부존가능성을 시사해준다. 반사강도가 약화되어 나타나는 음향공백대는 저탁류/원양성 퇴적물이 분포하는 중앙분지에 부분적으로 발달하며, 칼럼과 연계된 음향공백대는 북동쪽 사면저부에 주로 분포한다. 해저모방반사면의 하부에 위치하는 증폭반사면은 연구지역의 서쪽 사면에 분포하며 강한 음의 진폭특성으로 보아 자유가스를 함유한 층으로 해석된다. 가스분출구조는 주로 쇄설성 퇴적물이 우세한 조사지역의 남쪽 대륙사면지역에 광범위하게 분포하며 돔구조 혹은 폭마크 등을 수반한다.